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Home My WebLink AboutD-2.1. AB 2021 Energy Efficiency Targets 2018-2027UB-9 APPROVED UTILITY BOARD 2/27/17 UB-10 UB-11 DOCUMENT FOR PUBLIC REVIEW RELATED TO: UTILITY BOARD AGENDA THE ATTACHED DOCUMENTS ARE RELATED TO ITEM D-2 ON FEBRUARY 27, 2017 AGENDA OF THE AZUSA UTILITY BOARD REPORT ENTITLED: ADOPTION OF AB 2021 ENERGY CONSERVATION TARGETS NOTE: THIS DOCUMENT MAY BE REVIEWED IN THIS OFFICE ONLY AND NOT TAKEN FROM PUBLIC DESK. AZUSA CITY CLERK POSTED: FEBRUAR Y 23, 2017 NAVIGANT Energy Efficiency Potential Forecasting for California's Publicly Owned Utilities - Draft Prepared for: California Municipal Utilities Association ‘‘oil I A A1gp/ h calts' .4111 Pe, ry \ t ‘kb.. 4* ASSOc.‘*�` 111111 Prepared by: Assisted by: Navigant Consulting, Inc. Tierra Resource Consultants, LLC 1001 Officers Row 1501 North Broadway, Suite 300 Vancouver, WA 98661 Walnut Creek, CA 94596 360-828-4001 408-209-3296 February 22, 2017 ©2017 Navigant Consulting, Inc. NAVIGANT Table of Contents 1. Introduction 1 2. Key Issues and Updates Since the 2012 Potential Study 3 2.1 Relationship of ELRAM to the Current CPUC Model 3 2.2 Ability to Claim Codes and Standards (C&S) Savings 5 2.3 Emerging Technologies 6 2.4 Electric Vehicles (EV) and Solar Photovoltaic (PV) 7 3. Modeling Methodology 11 3.1 Key Design Elements 11 3.2 Potential Estimates 11 3.3 Approach to Estimating DSM Potential 13 3.4 Model Structure and Flow 13 3.5 Calculating Energy Efficiency Potential 15 3.6 Creating Scenarios Based on Modifying the Incentive Level 25 4. Summary of Results 27 4.1 2018 Through 2027 Targets 27 4.2 Comparison of the Current Targets with the 2012 Targets and Identifying Utilities that Claim Net or Gross Saving Targets and C&S Claims 30 Appendix A. Utility ELRAM Results 33 Appendix B. Utility Summary Memorandums 75 Page i NAVIGANT 1. Introduction The Navigant Consulting, Inc. team (the Navigant team) developed this study to provide 10-year Demand Side Management (DSM) Potential target goals for 39 California Municipal Utility Association (CMUA) utilities. These utilities include: • Alameda Municipal Power • Anaheim, City of • Azusa, City of • Banning, City of • Biggs, City of • Burbank Water and Power • Colton Public Utilities • Corona, City of • Glendale Water and Power • Gridley Electric Utility • Healdsburg, City of • Imperial Irrigation District • Lassen Municipal Utility District • Lodi Electric Utility • Lompoc, City of • Los Angeles Department of Water & Power • Merced Irrigation District • Modesto Irrigation District • Moreno Valley Electric Utility • Needles, City of • Palo Alto, City of • Pasadena Water and Power • Pittsburg, City of • Plumas-Sierra Rural Electric Cooperative • Port of Oakland NAVIGANT • Rancho Cucamonga Municipal Utility • Redding Electric Utility • Riverside, City of • Roseville Electric • Sacramento Municipal Utility District • San Francisco Public Utilities Commission • Shasta Lake, City of • Silicon Valley Power • Trinity Public Utilities District • Truckee Donner Public Utilities District • Turlock Irrigation District • Ukiah, City of • Vernon, City of • Victorville, City of Target goals were developed for the years 2018 through 2027. The model used to develop these goals is an updated version of the one utilized by the Navigant team in 2012 for CMUA and is similar in design, utilizing much of the same measure data information, as the California Public Utilities Commission's (CPUC) Potential Goals (PG) Model used for California's Investor Owned Utilities (IOUs). Assembly Bill 2021 directed the California Energy Commission (CEC)to identify all potentially achievable cost-effective electricity and natural gas efficiency savings and establish 10-year statewide energy efficiency savings targets. Originally intended to occur every three years, Assembly Bill 2227 changed the frequency of the energy efficiency 10-year target setting requirements to once every four years. CMUA engaged the Navigant team to assist the 38 CMUA members meet the CEC requirement to receive from CMUA members their 10 year DSM program targets. NAVIGANT 2. Key Issues and Updates Since the 2012 Potential Study This study provides an update to the 2012 Potential Study. The 2012 Potential Study developed estimates of technical, economic, and market potential for participating CMUA members. For both the current and 2012 Potential Study, Navigant utilized its Electricality Resource Assessment Model (ELRAM) as well as the related Natural Gas Resource Assessment Model (NGRAM)for the City of Palo Alto. The 2012 model was the basis for the current CPUC Potential Goals (PG) model with both ELRAM and the CPUC PG models evolving over the years since 2012. The new ELRAM is more powerful in its computational capabilities and agile in its scenario development capabilities. It also now includes a robust and easy to use output viewer, which allows the client to view potential savings estimates in a variety of ways without loading the entire ELRAM. Other improvements include: • Improved savings target calibration —the model calibrates using actual savings per end- use category by program as identified in the SB 1037 reports. • The capability to adjust potential either to meet specific budget limitations or to meet specific target goals by program. • Increased decision type flexibility and existing baseline capabilities—the model structure now allows for dual baseline measures and "to code" measures that exist from an existing baseline of a measure rather than a code baseline. • Expanded building types— ELRAM provides model results at the building type level for both the residential and commercial segments. The 2012 model only provided a rolled up commercial result. • Expanded industrial and agricultural assessments - ELRAM provides model results for up to 15 industrial and 9 agricultural NAICS categories. The 2012 model only provided a roll up industrial results and no agricultural measures. • Improved documentation — ELRAM is extensively documented in a Word document and within the model. Each sheet of the model contains a concise explanation of each formula and the purpose of each sheet. 2.1 Relationship of ELRAM to the Current CPUC Model Since 2011, Navigant has been conducting the CPUC's PG study; Navigant is currently on contract to continue supporting the study through 2018. The CPUC model creates forecasts of the technical, economic, and market potential across four utilities, 16 climate zones, and six sectors. The study is publically vetted through a stakeholder process and is used by the CPUC to set Investor Owned Utilities (IOU) goals, used by the CEC to inform Integrated Energy Policy Report (IEPR) demand forecast, and relied upon by the California Independent System Operator Corporation (CAISO)for planning purposes NAVIGANT The PG Model currently used by the CPUC to establish potential goals for the California IOUs is similar to the CMUA ELRAM. The PG model primarily differs in two ways: • The PG model platform is Analytica and ELRAM is Excel • The PG model market adoption algorithm is similar to the ELRAM approach in that they both use payback based Bass diffusion curves. However, the PG curves are based on lifecycle full equipment costs and paybacks while ELRAM is based on first cost measure payback. Results are similar but with ELRAM more responsive to changes in incentive levels when performing scenarios based on adjusting incentive levels. Analytica was chosen as the platform for the PG model because it can handle larger datasets within one model run (it runs all the IOUs at one time). Navigant has found that client preference to platform varies and therefore provides both an Analytica and Excel Potentials Model. For CMUA, Excel is considered the better platform as each model application (the 38 POUs) will each require unique adjustments and considerations. Excel is more amenable to making multiple modifications quickly. The basis for the change in the adoption algorithm between ELRAM and the PG model was the decision to include a financing option within the PG model. Simple payback doesn't work well with financing. Table 2-1 provides a comparison of model attributes between ELRAM and the PG model. Table 2-1. Comparison between EL RAM and the 2015 CPUC Model Model Attribute 2015 CPUC Model Proposed CMUA Model Residential, Commercial, Sectors Included Industrial, Agriculture, Mining, Same (as applicable) Street lighting Same (as applicable) and +170 current and emerging expanded to include some Technologies Included energy efficiency measures from the POU technologies, Technical Reference Manual (TRM) IOU rebate programs, codes POU rebate programs, codes Sources of Energy Efficiency and standards, behavior and standards, behavior Included programs, impacts of EE programs, impacts of EE financing financing Model Platform Analytica Excel NAVIGANT Model Attribute 2015 CPUC Model Proposed CMUA Model Forecast using a bass diffusion model calibrated to historic program activity. Adoption forecast is based on Similar with the primary economic attractiveness of difference being that the Forecasting Approach Bass diffusion curves are EE measures; considers the entire cost of owning and based on first cost measure operating baseline equipment payback vs. EE equipment in the consumer decision algorithm CPUC EM&V studies, Database for Energy Efficiency Resources Same as well as each utility Key Data Sources (DEER), CEC IEPR, utility's SB 1037 data and California Saturation Studies selected data from the POU (CLASS, CSS), and CPUC TRM Incremental Cost Study Low/Mid/High energy prices Start with this same data Energy Prices Used from the CEC IEPR forecast source. Can be modified after by sector. No consideration discussions with utility of tiered rates. representatives Same and additionally, Address SB 370 Goals Scenario Modifications ELRAM has capability to adjust program budgets by year to meet certain targets Model runs one scenario at a Scenarios Capabilities time. Multiple scenarios are same possible based on the user's inputs. Source:Navigant 2.2 Ability to Claim Codes and Standards (C&S) Savings Codes and standards affect energy efficiency programs in two different ways. Codes and standards increase overall energy savings because they require customers to install high- efficiency measures in lieu of baseline equipment. The mandates can cause markets (a)to achieve higher levels of adoption and (b) to achieve those levels faster than possible in the absence of the legal mandate. NAVIGANT However, codes and standards also reduce the savings potential from traditional utility programs. C&S updates increase the baseline efficiency of utility program measures, thus reducing the savings that POUs can claim as a result of the program. The effects of state and federal standards on voluntary programs are quantified by the percentage impact to unit energy savings of affected voluntary program measures. The energy savings impact is quantified as the ratio of the measure unit energy savings (UES) under the new standard to the measure UES using the baseline efficiency, as shown in the following equation: UES under new standard Impact Percentageyear = UES under the baseline Impact percentages vary by year because standards take effect in different years. Therefore, "vectors" of impact percentages were developed for utility program measure affected by C&S to capture the impact in each future year. For utility program measures not affected by any new C&S, values of the impact percentages are 100%. The energy savings potential of the CPUC PG model C&S advocacy program is determined based on the C&S energy savings defined in the CPUC 2006-2008 C&S program evaluation report'. ELRAM included within its modeling structure the ability of POUs to also claim C&S energy savings if they participate in some way with C&S advocacy. The method involves taking the C&S claims by sector for the closest IOU and pro-rating those savings based on sector sales. 2.3 Emerging Technologies The Navigant team depended on the analysis of emerging technologies (ETs) as defined in the 2015 CPUC PG modeling effort. ETs are defined as meeting one or more of the following criteria: • Not commercially available in today's market but expected to be available in the next 3-5 years • Commercially available but representing less than 5% of the existing market share • Costs and/or performance are expected to improve in the future The measures identified as ET in the CPUC PG model and included in ELRAM are: • Residential, commercial, industrial, and street lighting LEDs • MEF 2.87 Clothes Washers • EF 1.19 Dish Washers Final Evaluation Report, Codes&Standards(C&S) Programs Impact Evaluation, California Investor Owned Utilities' Codes and Standards Program Evaluation for Program Years 2006-2008. Prepared by KEMA, Inc., The Cadmus Group, Inc., Itron, Inc., and Nexus Market Research, Inc. Utilities' Codes and Standards Program Evaluation for Program Years 2006-2008. Prepared by KEMA, Inc., The Cadmus Group, Inc., Itron, Inc., and Nexus Market Research, Inc. NAVIGANT • Heat Pump Clothes Dryers • Refrigerators 35% above code • SEER 22A/C • SEER 21 HP 2.4 Electric Vehicles (EV) and Solar Photovoltaic (PV) The Navigant team's approach to modeling EV/PV adoption rates, and corresponding potential, was established in recognition of the following study considerations: 1.) There does not currently exist a unified and/or approved approach for estimating EV/PV potential across utilities within CMUA. 2.) The subsequent methodology must, to the extent possible, leverage data available to all utilities to facilitate both consistency and transparency in modeled results. Subsequently, individual utilities should have the opportunity to refine the models with utility-specific information and growth projections. In support of these objectives, the Navigant team leveraged utility-specific information from the California Energy Commission (CEC) Integrated Resource Planning (IRP) process; specifically, we developed regression models to forecast EV/PV adoption rates and potential using data from the 2016 Integrated Energy Policy Report (IEPR).2 Regression modeling is a form of analysis that attempts to quantify the behavior of an uncertain parameter relative to other observable, and potentially influential, variables. The most commonly used approach to capture this relationship is the linear regression3 model. For a set of predictive variables: [X,,X2,...,X„],4 and constants, The linear regression model is expressed by, Y = Q0 +f X, +...+u3„X„ In this study, the parameter"Y" represents a modeled adoption rate and/or sector-level 2 https://efilinq.energy.ca.gov/Lists/DocketLoq.aspx?docketnumber=l5-IEPR-03(Mid Demand Case) 3 Nonlinear regression is another form of regression analysis in which the relationship between the dependent and independent variables are characterized by a nonlinear combination of model parameters. However, there is generally no closed-form expression for the best-fitting parameters, as there is in linear regression, and the data are fitted by a heuristic of successive approximations. 4 In this case,the predictive variable would be previous years for which the IEPR forms provided former Electricity Consumption by Sector(GWh), Peak Demand (MW),etc. NAVIGANT consumption target per year by EV/PV, while the predictive variables "X;" represent the influencing parameters (i.e., years). The most common method of estimation, being the focus of this discussion, is the ordinary least squares approach. This method calculates values for the regression constants by minimizing the sum of squared residuals - a residual being the difference between a regression output and known value: n SSE=E(Y,. —Y,.)2 In this equation, Y,. and Y, represent the regression output and known data points, respectively. Minimization of this function results in a set of simultaneous linear equations which can be solved for the estimator constants. Figure 2-1 provides an illustrative example of the components involved in a least squares analysis. The linear curve represents a regression model output, while the discrete data points (i.e., blue diamonds) correlate to known data. The vertical bars in red represent the calculated residuals, the squared minimization of which will provide the best fit regression model. Figure 2-1. Method of Least Squares5 Method of Least Squares 7 6 • 5 4 3 2 1 0 0 1 2 3 4 5 6 7 Source:Navigant: It is hardly obvious why one would choose the best fit model by using the least squared 5 For the sake of visual practicality, Exhibit 1 represents a regression model with two unknown constants—or more precisely:Y=/30+/31X.This equation generates a linear curve,whereas a model with"n"constants would be characterized by a"hyperplane"in n-space which would be much more difficult illustrate. NAVIGANT approach. Minimizing the sum of errors in absolute value6 seems more readily intuitive. However, there are many qualities that make the least squared approach both computationally and statistically attractive. For one, it is very easy to calculate from a software perspective. Expressing the sum of squared errors mathematically, and employing calculus theory to derive the set of constants to minimize this sum, yields "n" equations and "n" unknowns to solve. The approach also possesses significant statistical properties that may be used to gauge the accuracy of regression findings. The calculation of the R2 value,' or coefficient of determination, represents the proportion of variability in a data set that is accounted for by a statistical model and is defined to be: n E(Y, -Y,.)2 R2 =1— n A E(Y—Y,)2 where Y represents the mean of the observed data. Overall, a larger R2 value indicates a more accurate regression model. When modeling EV/PV adoption / potential, the Navigant team developed linear, polynomial, exponential, etc. regression models for each utility using data from the 2016 IEPR. To maximize the accuracy of modeled findings, the model with the highest R2 value was used to forecast the first estimate of EV/PV adoption rates and potential for each utility. Figure 2-2 provides an example of the Navigant Team's modeling output for EV Sales (GWH) within the residential sector. Once the first set of forecasted estimates were provided to each utility, we collaborated with utility representatives to identify whether the source data could be improved through more recent or more utility-specific information. In these cases, the models were updated with improved / more accurate data and a new set of forecasting outputs were provided to each utility. It should be noted that the value of a regression model is directly dependent on the quality of data included. Accordingly, the Navigant team strives for transparency when detailing the sources of information included through each analysis, and to remain cognizant of outliers which may bias results. This transparency also ensures that individual utilities are aware of where updated / utility-specific data would provide the most value to the regression model. 6 The absolute value prevents large negative and positive errors from canceling out; yielding a model with minimum error that fits the data poorly. 'Under this definition, R2 assigns a metric to the unexplained variance, as the second term compares the model's variance with the variance of the observed data. Under this definition, R2 assigns a metric to the unexplained variance, as the second term compares the model's variance with the variance of the observed data. NAVIGANT Figure 2-2. Example Regression Modeling Results for EV Sales (GHW)8 EV Sales (GWH) - Res 600.0 y=4.0816639198x -16,449.5290381840x +16,573,347.9298435000 500.0 R2=0.9990507765 • 400.0 • • 300.0 1 *' 200.0 r' • 100.0 x 0.0 2014 2016 2018 2020 2022 2024 2026 2028 Source: Navigant 2.4.1 Photovoltaic System Dampening Effect A Solar PV dampening methodology is added to the model based on the forecast of PV generation in a POU service territory expressed as a percent of utility sales. The dampening adjustment is applied to the consumer's willingness to install measures by reducing the willingness as the share of PV generation to utility sales increases. Unfortunately, the Navigant team found no supporting research for calibrating this dampening factor. The dampening effect may in fact be minimal giving that those who install PV are generally more inclined to make their homes energy efficient and thus install a deeper level of efficiency measures. Additionally, the installation of PV may act as a prod to learn more about energy efficiency, therefore potentially increasing installation of energy efficiency measures. Given the lack of evidence one way or another, this dampening effect has been set to 0.0% with no dampening occurring. 8 TN210040 20160127T151013 LADWPMid Demand Case.xlsx NAVIGANT 3. Modeling Methodology The Electricity Resource Assessment Model (ELRAM) is an electricity energy efficiency potential model designed to estimate technical, economic, and program (market) energy efficiency potential for a utility's service area. Developed by Navigant, the model forecasts energy savings and demand reduction potential within the residential, commercial, and industrial sectors over a forecast period of typically 20 years. Since its initial development in 2007, the model has been used by over 50 different electric utilities across the country to identify future energy efficiency potential. 3.1 Key Design Elements ELRAM is a stock/flow Excel spreadsheet model based on the integration of energy efficiency measure impacts and costs, utility customer characteristics, utility load forecasts, and utility avoided costs and rate schedules. ELRAM utilizes Excel as the modeling platform due to the transparency in the DSM potential estimation process, and because of the ubiquitous knowledge of the platform in general. Excel also allows the team to customize ELRAM to accommodate the client's unique set of input characteristics and utility data. The model utilizes a "bottom-up" approach, beginning with study area building stocks, equipment saturation estimates, forecasts of building stock decay and new construction, energy efficiency technology data, past energy efficiency program accomplishments, and decision maker variables that influence the program scenarios. A key component of ELRAM is the decision maker function used to estimate annual participation in utility programs. ELRAM develops "Measure Payback Response Curves"that are calibrated to historical utility program achievements. These measure level curves are founded on the Bass Diffusion Model developed by Dr. Frank Bass. The Bass Diffusion Model describes the process of the adoption of products as an interaction between users and potential users. The decision maker function estimates a measure by measure elasticity response to first cost measure payback. The elasticity coefficient is calculated for these measures in the base calibration year using measure-level utility program achievements and first cost measure payback. Utilizing this elasticity based decision process allows for easy to create scenario options based on changing the size of measure level incentives. In addition, other input variable flexibilities are included within ELRAM to allow for many different scenario considerations. 3.2 Potential Estimates The model develops estimates of technical, economic, and market potential. Figure 3-1 illustrates these types of energy conservation potential, as defined below: NAVIGANT Technical Potential. ELRAM calculates technical potential as the product of a measure savings per unit, the quantity of applicable units in each facility, and the number of facilities in a utility's service area. This potential savings assessment includes measures that may not be cost- effective, and therefore provides an upper bound of efficiency potential regardless of cost or market penetration. All baseline units are considered available regardless of measure life. No net-to-gross adjustments occur with technical potential. Economic Potential. ELRAM estimates economic potential as the amount of technical potential that is cost-effective, as defined in this case by the results of the Total Resource Cost (TRC) test. The TRC test is a cost-benefit analysis of relevant energy efficiency measures, excluding market barriers such as lack of consumer knowledge. Benefits include the avoided costs of generation, transmission and distribution investments, avoided fuel costs, and other benefits that may accrue to participants and/or to the utility. Costs vary by economic test but may include incremental technology cost, incentives, administrative costs, and/or lost revenue. The economic screen is set to 1.0 to determine Economic Potential. There are no net-to-gross adjustments. Maximum Market Potential. ELRAM screens the amount of economic potential that utility programs could capture over the forecast period. The measure level economic screening value for maximum market potential can be set to less than 1.0, but results at the program level have a goal of having an overall economic screen of 1.0 or better. This allows the program to include a mix of measures above and below the 1.0 screening threshold. This adjustment factor can vary by program. In addition to the economic screening value, maximum market potential includes the effects of decision maker awareness of each measure and if aware, their willingness to install the measure. Market Potential. ELRAM uses a fourth step for calculating achievable energy savings at the market level using simple payback elasticity. The achievable market potential uses the remaining maximum market potential at the measure level available each year and applies a decision maker simple payback elasticity coefficient to identify yearly savings available in the marketplace. The model calculates this payback elasticity based on historical program achievements and the identified incentive levels by measure. This step provides realistic forecasts of market potential given incentive and program budget levels, which can change over the forecast period. NAVIGANT Figure 3-1. Diagram of Types of Energy Efficiency Potential Technical Potential ( Economic ( , Potential Maximum Market Market Potential , Rf Source:Navigant 2015 3.3 Approach to Estimating DSM Potential ELRAM utilizes "Measure Payback Response Curves" to calculate market potential by year. The method for creating these curves comes from the methodology used for the Bass Diffusion Model developed by Dr. Frank Bass. The Bass Diffusion Model describes the process of the adoption of products as an interaction between users and potential users. The decision maker function estimates a measure's elasticity response to first cost measure payback calculated in the base calibration year. This base year uses measure-level utility program achievements and first cost measure payback. First cost measure payback does not include any savings from extended measure life of changes in maintenance costs. Utilizing this elasticity based decision process allows the model to create scenario options based on changes to measure level incentives. In addition, ELRAM includes other input variable flexibilities to allow for many different scenario considerations including program budget levels and program promotion costs. 3.4 Model Structure and Flow ELRAM includes nearly 40 distinct worksheets including input, calculation, and output pages, as well as a Scenario Dashboard that offers modelers a quick way to interact with the model and produce different scenario runs. The variables available on the dashboard include: • Economic test screens • Beyond first measure life considerations • Fiscal variables including: o Incentive level o Administrative costs o Program budget limitations NAVIGANT There is also an "output viewer" connected to the results of the model which allows the client to view potential savings estimates in a variety of ways. Figure 3-2 provides a general overview of the data flow through the ELRAM model. The model structure can vary from client to client depending on available data and output needs. Figure 3-2. ELRAM Data Flow Overview Technical Utility Measure Data Economic - Data Max Mkt f Customer - Measure DataAvailability I � Model Outputs ., • kWh and kW savings forecasts by '4040 P:WO' `- �> potential type, sector, end-use, and other variables � • Scenario development using changes to measure incentives • Scenario supply curves • Top 50 energy saving technologies for program design Source: Navigant Successful potential savings forecasts rely on high quality and accurate data inputs into ELRAM. These inputs fall into four categories including: • Utility Data. Navigant worked closely with the CMUA utilities to gather all utility specific data such as energy (kWh) and demand (kW)forecast estimates, avoided costs, past program savings achievements for use in calibrating ELRAM, customer rate classes, and discount rates. Navigant also relied on the Quarterly Fuels and Energy Reports submitted by the utilities to the California Energy Commission for commercial and industrial sales information by NAICS. • Customer Data. Navigant relied on the CPUC PG model inputs byclimate zone to provide customer characteristic data by measure. The CPUC data relied on statewide Residential and Commercial building saturation surveys. • Measure Data. Navigant relied on the CPUC PG model dataset of energy efficiency measures as well as the POU Technical Reference Manual (TRM) to characterize the measures included in the study. These characteristics include costs, energy and NAVIGANT demand use impacts, and measure life for both baseline and energy efficient technologies. • Measure Availability. ELRAM uses building stock inputs along with the availability of technology density each year to estimate potential energy savings throughout the forecast period. Navigant relied on the CPUC PG model inputs by climate zone for this information. The outputs from ELRAM accomplish multiple objectives, including: • Determining the total technical, economic, and market potential of energy savings available over the forecast period, both annually and cumulatively; the model calculates these potential estimates at the sector, building type, program type, and end-use classification levels • Providing guidance for identifying 10-year energy efficiency program goals at an aggregate level, as well as at the measure category level. ELRAM calibrates calculations to past utility achievement levels to ensure continuity with past utility efforts • Identifying cost-effectiveness using multiple cost effectiveness tests • Identifying specific costs and benefits, including administrative, incentive, and technology costs, along with avoided cost and reductions in other resource requirement benefits (such as water use reduction) 3.5 Calculating Energy Efficiency Potential The results of ELRAM are designed to accomplish multiple objectives, including: • Determining the total cost-effective energy savings available over the forecast period, both annually and cumulatively. The model provides estimates at the sector, program type, and end-use classification levels. • Providing guidance for the utility's energy efficiency goals at an aggregate level and at the measure category level, where appropriate. As discussed, the ELRAM calculations are calibrated to past utility achievement levels to ensure continuity with past program achievements. The model partitions its assessment of each measure into technical, economic and achievable potential. Each assessment includes building stock estimates, technology densities, and measure impacts, with each using a different algorithm. 3.5.1 Measure Types Addressed ELRAM recognizes the following measure types: • Replacement on Burnout (ROB): Implementation of an energy efficient measure after the existing equipment fails. • Retrofit (RET): Immediate installation of an energy efficient measure that improves the efficiency of an existing technology. The lifetime of the base technology is not a factor as NAVIGANT retrofit measures generally do not replace existing technologies. The energy impact is therefore only the amount of improvement to the existing technology. • Dual Baseline (DUB): The dual baseline measure type is an early replacement that replaces an existing technology before the end of useful life. However, savings is calculated using a less efficient "as found condition" baseline for the first part of the remaining useful life (RUL), and a "code condition" for the second portion of the RUL. These results in higher initial energy savings under the first baseline, and lower savings under the second baseline once the measure would have reached the end of its effective useful life (EUL). Measure costs are also adjusted to reflect the change in baselines. 9 • Behavioral Programs (BEH): Programs designed to influence consumer behavior through the provision of training and/or information. As with emerging technologies, achievable potential is calculated using a Bass diffusion model rather than the traditional measure payback. • Low Income (Low): Measures that are implemented as part of a low-income program. • New Construction (NEW): Installation of a measure or package of measures at the time of construction. • Demand Response (DR): Strategies specifically designed to reduce peak demand. There is generally very little energy savings associated with these strategies. 3.5.2 Financial Tests Calculated ELRAM calculates several financial tests and measurements, including: • Total Resource Cost (TRC): This test includes all quantifiable costs and benefits of an energy efficiency measure that may accrue to participants or the utility. For example, a measure passing the TRC test is cost effective from this perspective if the sum of its avoided costs and other benefits accruing to participants or the utility are greater than the sum of the measure costs and the utility's administrative costs. • Program Administrator Cost Test (PAC): This test measures the costs of an energy efficiency program based on the costs incurred by the utility (including incentive costs) and excluding any net costs incurred by the participant. For example, a measure passing the PAC test is cost effective from this perspective if the sum of the avoided costs (costs avoided by the measure's energy and demand savings) and other utility benefits are greater than the utility's costs to promote the measure, including incentives provided to customers. • Ratepayer Impact Measure Test (RIM): This test measures what happens to a dwelling or business' electric bills or rates due to changes in utility revenue and operating costs caused by the program. For example, a measure passing the RIM test is cost effective from this perspective if its avoided costs are greater than the sum of the utility's costs and the"lost revenues" caused by the measure. • Participant Cost Test (PCT): This test measures the quantifiable benefits and costs to the customer due to participation in the program. For example, a measure passing the PCT test is cost effective from this perspective if the reduced electric costs to the 9 See the Dual Baseline section 3.5.6 for more detail. NAVIGANT participating customer from the measure exceed the after-incentive cost of the measure to the customer. • Simple Customer Payback: This measurement calculates the incremental technology cost divided by the incentive and the reduction in the electric bill. If multi-life benefits and costs are considered, it also includes the PV of future technology costs and future incentives and bill reductions. • Levelized Measure Cost/kWh: This measure multiplies the energy efficiency measure costs by the Capital Recovery Factor, and divides by the first-year kWh savings. ELRAM calculates measure, program, end-use, building type, and overall portfolio level costs and benefits, and when applicable at both the net and gross levels. Net values take into account free riders by using net-to-gross adjustment values. The costs and benefits calculated include: • Administrative costs (always gross) • Avoided cost benefits (always net) • Other utility benefits (always net) • Other participant benefits (always net) • Incentive costs (always gross) • Incremental technology costs (gross or net) • Utility bill reductions (gross or net) Within the "Financial Tests"worksheet, these streams of costs and benefits are converted to a net present value using the discount rate. With this data, four financial tests identified above are calculated. Total Resource Cost (TRC)10'11'12: The TRC test measures the net resource benefits from the perspective of all ratepayers by combining the net benefits of the program to participants and non-participants. The benefits are meant to be the sum of the avoided costs of the supply-side resources avoided or deferred, and other benefits that accrue to participants or the utility. The TRC costs encompass the cost of the measures/equipment installed, and the costs incurred by the utility. The formulation: TRC = Benefits / Costs where: • Benefits = net avoided costs + net other utility benefits + net other participant benefits • Costs = gross administrative costs + net incremental technology costs 1° California Standard Practice Manual:Economic Analysis of Demand-Side Programs and Projects. October 2001. http://www.energy.ca.gov/greenbuildi ng/documents/background/07- J CPUC_STANDARD_PRACTICE_MANUAL.PDF "CPUC D0606063,Attachment 9. http://www.cpuc.ca.gov/NR/rdonlyres/101 F0713-7277-43A8-883D- 8EF2712EFA8A/0/NumericalExamplesNTGAdjtoTRCD0709043.pdf 12 CPUC http://docs.cpuc.ca.gov/published/final_decision/73172-10.htm NAVIGANT Program Administrator Cost Test (PAC) 10: Sometimes referred to as the utility cost test, this test compares the utility's avoided cost benefits with energy efficiency program expenditures (incentives plus administrative costs). The formulation: PAC = Benefits/ Costs where: • Benefits = net avoided costs + net other utility benefits • Costs = gross administrative costs + gross incentives Ratepayer Impact Test (RIM): 13 This test measures what happens to customer bills or rates due to changes in utility revenue and operating costs caused by the program. The formulation: RIM = Benefits/ Costs where: • Benefits = net avoided costs • Costs = gross administrative costs + gross incentives + net bill reductions Participant Cost Test (PCT): 14 This test measures the quantifiable benefits and costs to the customer due to participation in the program. The formulation: PCT = Benefits/ Costs where: • Benefits = gross incentives + gross bill reductions • Costs = gross incremental technology costs Table 3-1 presents the formula for each of the four benefit/cost tests. Table 3-1. Benefit/Cost Test Formulas Cost Test Formula Key of Terms Program A= PV Avoided Costs E= PV Incentive Administrator Cost PAC=(A+ B)/(D+E) Test(PAC) (always net) Costs(always gross) Participant PCT=(E+gross G)/ B= PV Other Utility F= PV Technology Cost Test(PCT) gross F Benefits Costs(gross or net) (always net) Rate Impact C= PV Other Participant G=PV Bill Measure Cost Test RIM=A/(D+ E+net G) Benefits Reductions(gross or (RIM) (always net) net) 13 California Standard Practice Manual:Economic Analysis of Demand-Side Programs and Projects. October 2001. http://www.energy.ca.gov/greenbuilding/documents/background/07- JCPUC_STAN DARD_PRACTI CE_MAN UAL.PDF 14_Ibid. NAVIGANT Total Resource TRC=(A+ B+C)/(D+ D=PV Administrative PV= Present Value Cost Test(TRC) net F) Costs(always gross) 3.5.3 Approach to Multi-Life Benefits 3.5.3.1 Multi-Life Benefits The ELRAM model has the capability of recognizing that the impacts of DSM measures may extend beyond the initial estimate of measure life. Taking this possibility into account can affect benefit/cost ratios, such as the TRC, PCT, PAC, and RIM, by incorporating future expectations of avoided costs, as well as changes in measure costs and impacts, and cumulative energy and demand impact estimates. The estimation of multi-life benefits and determined by the variable: • Measure Re-Engagement. This variable estimates the share of measure installations that continue to provide efficiency benefits at least equal to the initial DSM measure installed. The complimentary share of installations not part of re-engagement is returned to the population totals of available stock for program participation. There are no new incremental savings accruing from the re-engaging population. However, cumulative savings must be adjusted in two ways. Using as an example a re-engagement rate of 85%, the first adjustment is for the 15% not re-engaging. This 15% goes back to the baseline population and their savings removed from cumulative savings. The second adjustment is for the 85% assumed to be re-engagers. For this group, adjustment to cumulative potential is dependent upon whether the savings are different from what was achieved at the time of the original participation. If unchanged, no changes to cumulative potential. If savings are different, then the cumulative potential is adjusted by this delta difference. At the point in time of re- engagement, factors may exist that affect the estimate of continuing DSM measure saving and costs. • A code or standard (C&S) may have come into effect since the initial point of participation. The effects of the C&S become an attribution issue. Since C&S are mandatory, savings affected by C&S are attributed to the C&S. The share of savings may be 100% or may be a share lower than 100%. If 100%, then no further savings or costs are attributed to the DSM program measure. If the attribution is less than 100%, then the attribution share still applicable to the utility is accounted. • A measure's estimated energy savings may increase or decrease in the future. For example, LED lighting is still improving in efficacy and, as it does, savings per measure increase. In contrast, appliance recycling programs, such as refrigerator recycling, are expected to have lower savings per unit over time as the population of refrigerators becomes a more recent (more efficient) vintage each passing year. • A measure's estimated cost may increase or decrease in the future. For example, LEDs and other, newer technologies are expected to decline in cost as these become more NAVIGANT popular in the marketplace. The declining cost of CFLs over the past decade is an example of such an effect. Any changes in energy savings at the point of re-engagement are calculated. These changes in energy savings are applied to the Cumulative Potential and do not affect the Achievable Incremental Potential. Avoided cost of energy, capacity, and any externality that is quantified are all calculated per measure unit. The impacts are separated into "first life" avoided costs and "beyond first life" avoided costs. The "first life" values are the present value of avoided costs using measure life, the utility discount rate, and the utility's avoided cost stream. The "beyond first life" estimate of avoided cost is calculated only for the population of"re-engagers". For this population, the present value of future avoided costs beyond the first life15 is calculated starting at this future point in time. This calculation uses any revised future estimate of measure impact, along with measure life, the utility discount rate, and the avoided cost stream appropriate for that time frame. In a similar manner, the future cost for incremental technology is calculated. 3.5.3.2 Codes and Standards Modified Baseline Effects on Cumulative Potential The effects of codes and standards within the ELRAM model are viewed as an attribution issue between what is credited to codes and standards and what is credited to the DSM program. The "Code Based Impact Change" identifies the specific codes and standards expected to affect measure savings over the forecast period. The effects to measure savings are in the form of time vectors where a specific code and standard is associated with the measures it is expected to affect. The measure effect is in the form of a percent change in savings starting at the point when the code and standard goes into force. As an example, if a specific code and standard effectively reduces saving by 50% starting in the year 2015, the DSM program's first year incremental measure impact would be 100% of the estimated program impact up to the year 2015. Starting in 2015 and thereafter, the utility's share of the measure savings is reduced by 50%, with the other 50% being attributed to the code and standard. Treating the savings achieved by the DSM program after a code and standard goes into force is done in two parts. First addressed, at the moment the code and standard going into force, is whether there are any adjustments to the first measure lifetime savings, costs, and benefits. The ELRAM model treats these already exiting program achievements, benefits, and costs as unchanged (maintained) over the remaining first lifetime of the measure. However, at the time of re-engagement, adjustments do occur. For those measures assumed to re-engage after the first lifetime is complete, the measure impacts, benefits, and costs are calculated based on the code and standard adjusted savings level. It is assumed that attribution of the savings transfers to the code and standard at this point forward. To accommodate this, the Cumulative Potential is adjusted downward to reflect the lowered savings resulting from the 15 Several lifetimes may be calculated, depending on the measures estimated life and the length of the forecast period. NAVIGANT impact of the code and standard at the time of re-engagement. Additionally, post first lifetime benefits and costs are calculated to reflect the lower savings. 3.5.4 Mutually Exclusive Measures Two or more measures that each can replace the same base technology are considered to be mutually exclusive. Examples of mutually-exclusive measures are LED and CFL lamps of the same efficacy being in competition to replace an incandescent lamp. Mutually-exclusive measures are placed into competition groups with separate competition group identifiers for each group. Within the competition groups, the mutually-exclusive measures share the same base population, but each measure uses its own unique decision- maker adoption rate algorithm to estimate year-by-year achievable potential. The base population is reduced each year by the sum of the mutually-exclusive measures participation. 3.5.5 Interactive Effects The energy and demand impacts form DSM measures can be affected by other measures or actions taken. ELRAM recognizes two forms of interactive effects. The first are interactive effects among measures within the same fuel type and end use. An example of a set of DSM measures that would be considered having interactive effects would be ceiling insulation, wall insulation, a high efficiency furnace, and energy efficient windows. Alone, each of these measures would have a specific energy savings impact. As a group or part of a group, the individual measures have lower savings. Within ELRAM, a unique interactive effects code is assigned to the set of measures considered to be interactive in this manner. The stand-alone measure impacts are identified as well as the savings if the entire set of interactive measures were implemented. The measure savings used in ELRAM is the pro-rated share of the individual measure savings to the group total. For example, if an interactive measure group included two measures, one with a stand-alone savings of 100 kWh and the other 200 kWh with a group implementation total of 250 kWh, the first measure's model savings is 100/300*250 or 83.3 kWh and the second measure model savings is 200/300*250 or 166.7 kWh. The second type of interactive effect is among measures from different end-uses that impact the savings of the other. An example would be lighting measures. More efficient lighting produces less waste heat. This results in lower cooling but higher heating loads. The lighting measure energy savings would be increased by how much it reduces electric cooling and increased by how much it increases electric heating. The saturation of electric cooling and heating is taken into account. Effects on other fuels or commodities, such as increased natural gas heating loads or reduced water use, are accounted within the cost effectiveness calculations through increases or decreases in the billing for that fuel or commodity. NAVIGANT 3.5.6 Dual Baseline Measures Certain DSM measures are candidates for an early replacement program that utilizes a dual baseline.A dual baseline approach calculates energy savings using a more complex method than is used by the majority of North American DSM administrators. Most jurisdictions use the effective useful life(EUL), or assumed average life of the new measure to calculate the annual savings of the new measure. An example is the replacement of an air conditioning system with one that uses energy more efficiently. For the EUL of the new system (for example,25 years), the difference in energy use between the new system and the replaced one is claimed as the energy savings. A dual baseline approach uses, in addition to EUL, the remaining useful life (RUL) of the replaced equipment,which is the length of time the equipment is expected to remain in operation(the length of time until its EUL is at an end).Using a dual baseline approach in the example of the air conditioning system, the difference in energy use between the replaced and new system is claimed as savings only for the RUL of the replaced system.After the RUL (for example 10 years) of the replaced equipment and until the end of the EUL of the new equipment(15 years, if the new system is assumed to have an EUL of 25 years), the difference in energy use between the new system and the standard of equipment at that time is claimed as energy savings.This method takes into account improvements in technology and the market over time;even without an incentive,energy savings for some equipment will occur when old equipment is replaced,because the standard version of newer equipment uses less energy. In the year an energy-efficient measure is installed,if the replaced measure is still in working order, its RUL must be calculated based on its EUL and the length of time it has been in use prior to replacement. Figure 3-3 illustrates the two-step process. NAVIGANT Figure 3-3. Two-part Calculation of Energy Savings Using a Dual Baseline Approach Annual Consumption(kWh/yr) 100 90 80 Savings 70 for RUL 60 50 Savings for EUL minus RUL 40 30 20 10 0 Exisisting Equipment Efficient Equipment Standard Equipment Efficient Equipment � Y Step 1:Savings Step 2:Savings calculated calculated for the RUL for the remaining EUL of of a replaced measure the new measure Once calculated, energy savings are affected in the following ways: • When a measure is replaced and it has a RUL, the full unitary savings value (the replaced measure's estimated annual kWh usage minus the new measure's estimated annual kWh usage) is calculated. These savings can be claimed for each year of the RUL of the measure (Figure 3-3, step 1). • When the RUL of the replaced measure expires in the future, a new baseline for annual kWh savings must be used. This baseline is calculated using the most common energy use values for replacement products: either those legislated through codes and standards or those installed by common practice (Figure 3-3, step 2). • If the replaced measure has reached the end of its EUL at the time of replacement, then the current code or most commonly used measure is used to calculate the energy savings, rather than the difference between the new measure and the replaced one. 3.5.7 Appliance Recycling Appliance recycling measures need special treatment because of the unique characteristics of the base population. Unlike other base technologies, the used appliance stock available for recycling is constantly being refreshed with new populations of appliances. Due to past NAVIGANT improvements to appliance efficiencies (primarily codes and standards), the constantly refreshing population of available appliances for recycling is more efficient (and thus saves less energy) from year to year. Available populations of appliances for recycling may not change significantly from year to year, but the time vector of savings per unit does decline. The cumulative savings are accounted only within the timeframe of the estimated remaining life of the recycled appliance. The re-engagement calculations do not take place for appliance recycling measures. 3.5.8 Behavior Based Energy Savings Potential Savings potential from behavior-based initiatives can be included in the ELRAM model by initiative and by building sector. Within ELRAM, behavior-based initiatives are defined as those providing information about energy use and efficiency actions, rather than financial incentives, equipment, or services. These initiatives use a variety of implementation strategies including mass media marketing, community-based social marketing, competitions, training, and feedback.16 Outcomes from behavior-based initiatives that result in energy savings can be broadly characterized as equipment-based and usage-based: • Equipment-based behavior—Savings from the purchase and installation of higher efficiency equipment, relative to baseline conditions.17 Examples of equipment-based behavior include the replacement of lights with higher efficiency lights, purchasing Energy Star°-qualified appliances, and purchasing premium efficiency motors. In the ELRAM Model, these savings are modeled at the equipment level as contributions to the percentages of the population that are aware of the measure and that are willing to adopt this measure. Equipment-based behavior can be sub-categorized as: o Non-incented equipment-based behavior—The purchase of higher efficiency equipment for which no incentives are provided. o Incented equipment-based behavior—The purchase of higher efficiency equipment for which incentives are provided. • Usage-based behavior—Savings from changes in usage and maintenance of existing equipment. Examples of usage-based behavior include turning off lights, unplugging electronics and chargers, programming thermostats, and improving the efficiency of equipment through modified maintenance practices. In the ELRAM model, these savings are modeled as an equipment-independent module with savings unassociated with equipment improvement. 16 Evaluation of Consumer Behavioral Research, Navigant(Summit Blue Consulting)for the Northwest Energy Efficiency Alliance,April 6, 2010, Page 4. 17 This could be either the early retirement of older equipment or the installation of high-efficiency equipment at the natural time of installation or replacement. NAVIGANT The behavior measure savings used within ELRAM reflect estimates of usage-based and non- incented based behavior. The incented equipment-based behavior is assumed to be addressed by the utility's other incentive-based DSM programs. Currently, the measure life is assumed to be one year for the residential sector based on enhanced billing programs, reflecting the need to continually reinforce the behavior program's message to conserve and use energy efficiently. The commercial and industrial sector programs are assumed to have a measure life of five years based on the extensive training received by building operators. For the commercial sector, the program is based on a Building Operator Certification Program. For the industrial sector, the program is based on a Strategic Energy Management Program. 3.6 Creating Scenarios Based on Modifying the Incentive Level A fundamental element of ELRAM is the decision-maker algorithm. The function of measure calibration is to establish for each measure a baseline "Market Factor", which is estimated based on first-cost measure payback and the achieved savings in the base year. This value is an elasticity coefficient used in the forecast period to estimate measure adoption. These incentive levels by measure are generally the actual incentives provided by the utility or they default to an input value, such as 50% of incremental cost. Once the baseline Market Factor is established, the incentive during the forecast period can be modified up or down. Changing the incentive changes the first cost measure payback with corresponding changes in measure adoption rates. These changes in adoption rates are established using the baseline Market Factor, which is unchanged, and the modified first cost measure payback. The scenario incentive level is expressed as a multiplier to the base scenario incentive. If the base incentives are expressed solely as a percent of incremental technology cost (such as 50%), then a scenario expressed as 25% would represent incentives being cut in half and 75% would represent incentives increasing 1.5 times. However, if the base incentives include actual incentive levels, then the base case could represent a mix of incentives that are above or below 50% of incremental technology cost. In this situation, the base percentage (such as 50%)would only be applied to measures where either the incentive is unknown or the measure is not yet part of the utility portfolio. For those measures with incentives set at the base case percentage (such as 50%), then a scenario expressed as 25% would represent incentives being cut in half, and 75%would represent incentives increasing 1.5 times. For those measures using actual incentive levels, the scenario expressed as 25% would also represent incentives being cut in half, and 75% would represent incentives increasing 1.5 times. If the current base incentive of 50% represented 25% of incremental cost, the 75% incentive scenario would represent an incentive of 37.5% of incremental cost. Additionally, incentives are capped at 100% of incremental cost. The exception is if the base incentive is already above 100% of incremental cost; in this instance, the incentive does not change. NAVIGANT The year in which the higher or lower incentive level goes into effect is a variable. For instance, if a utility has a mandated goal to achieve about 1.5% of sales of incremental energy efficiency each year, it may be necessary to increase the incentive in some future year in the forecast when the forecast of market potential begins to fall below the 1.5% of sales goal. 3.6.1 Scenario Adjustments to Consumer Awareness and Willingness The estimates of future decision maker measure awareness and willingness to install the measure are also affected by changes in the incentive and administrative cost levels. Increased incentive and administrative cost levels correspond to increased awareness and willingness, while decreased incentive and administrative cost levels translate to lower awareness and willingness. Changes to administrative cost is used as a proxy to simulate changes in promotional/education efforts. Modifications to these two costs can be considered independently The calculations in ELRAM assume that consumer awareness of energy efficiency measures and willingness to install the measures improves over time as long as an incentive is being offered. If no incentive or only a very small incentive is offered, consumer awareness and willingness grows very slowly and reaches a lower maximum awareness and willingness rate compared to the base case. Conversely, higher incentives generally reflect greater marketing of the utility program, which increases consumer awareness and willingness. As the scenario incentive approaches 100%, both the rate of growth in consumer willingness and awareness grow, as do the maximum awareness and willingness values as compared to the base case. NAVIGANT 4. Summary of Results Navigant developed estimates of conservation potential for each of the 39 participating utilities for the target years 2018 through 2027. The process for developing these targets included: • A Base Case was developed representing a continuation of existing utility program efforts. • Scenarios were created for each utility. Typically, these scenarios were characterized as follows: 1. Base Scenario (no change to existing programs) 2. Increase administrative/promotion by 1.5 starting 2018 3. Increase incentive by 1.5 starting 2018 4. For appropriate measures, convert from Replace on Burnout (ROB) to Early Retirement in 2018 5. Add measures not currently in program portfolio in 2018 6. Do all the above combined 7. All the above and add Behavioral Programs starting 2018 • Meetings were held with each utility to discuss the Base Case results as well as options that each utility could consider(based on the scenario runs). • At this point, the utility either wanted to accept the Base Case or have Navigant run specialized scenarios based on the utility's input. • If scenarios were created, additional runs were made; often several additional runs. • The utility made a decision as to what it wanted included in their 10 year targets. Once program considerations were finalized, two additional decisions were made by each utility: • Did the utility want to claim, as part of their ten-year targets, savings from Codes and Standards in a manner similar to how the investor owned utilities claimed these savings as part of their goals. • Did the utility wish to express their claim as Gross savings or Net savings? 4.1 2018 Through 2027 Targets Using the results of ELRAM and Navigant's discussions with each utility, the POUs adopted updated annual energy savings targets for the ten-year period of 2018-2027. The combined targets from the 39 utilities averages over 690,000 MWh in energy savings annually. Figure 4-1 NAVIGANT illustrates the incremental energy potential and Figure 4-2 the cumulative energy potential. Table 4-1 provides the inputs into these two graphs. Figure 4-1.All Utilities Ten-Year Incremental Energy Goals(MWh): 2018—2027 800.000 1.25% 700,000 _.. 1.05% 600.000 a85% 500000 0.65% 3 i 400.000 045% 300,000 `c 0.25% 200,000 100,000 0.0.5% 0 -0.15% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential Non-Res Incremental Market Potential MID C&S(If Claimed.Estimates not available after 2024) —o—Total Incremental Potential as a%of Total Sales Source: Navigant NAVIGANT Figure 4-2. All Utilities Ten-Year Cumulative Energy Goals(MWh): 2018- 2027 6,030,000 9.00% 8.00% 5.000.000 -^""'" 7.0396 4,000,000 6.00% 5.00%L3 1L R 090.000 4.00% .0 2.000,000 3.0006 2.00% 1000.000 1.00% 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Cumulative Market Potential =I Non-Res Cumulative Market Potential CAS(If Clamed.Estimates not available after 2024) -o-Total Cumulative Potential as a 96 of Total Sales Source: Navigant Table 4-1. Inputs into the All Utilities Incremental and Cumulative Energy Goals 10-Year Energy Goals(MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 730,604 743,103 748,003 731,926 719,424 692,637 665,495 648,551 618,758 584,662 Res Incremental Market Potential 220,455 223,669 224,061 238,800 254,873 263,322 261,937 254,221 247,101 239,894 Non-Res Incremental Market Potential 267,494 275,766 280,439 276,669 266,777 250,271 233,905 218,811 203,325 183,251 C&S(If Claimed.Estimates not available after 2024) 242,655 243,668 243,502 216,456 197,774 179,044 169,654 175,520 168,331 161,516 Total Incremental Potential as a%of Total Sales 1.13% 1.14% 1.14% 1.10% 1.07% 1.02% 0.97% 0.93% 0.88% 0.82% Res Incremental Potential as a%of Res Sales 1.03% 1.04% 1.02% 1.07% 1.12% 1.14% 1.12% 1.07% 1.02% 0.98% Non-Res Incremental Potential as a%of Non-Res Sales 0.61% 0.63% 0.63% 0.62% 0.59% 0.55% 0.51% 0.47% 0.44% 0.39% 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 730,604 1,366,953 2,006,544 2,621,203 3,216,761 3,744,385 4,228,033 4,690,318 5,118,861 5,503,266 Res Cumulative Market Potential 220,455 344,178 466,801 598,290 743,374 881,896 1,005,803 1118,851 1,219,832 1,305,885 Non Res Cumulative Market Potential 267,494 536,453 809,918 1,076,633 1,329,332 1,539,390 1,729,476 1,903,194 2,062,425 2,199,261 C&S(If Claimed.Estimates not available after 2024) 242,655 486,322 729,824 946,281 1,144,055 1,323,099 1,492,753 1,668,273 1,836,604 1,998,120 Total Cumulative Potential as a%of Total Sales 1.13% 2.10% 3.04% 3.94% 4.78% 5.50% 6.15% 6.75% 7.30% 7.76% Res Cumulative Potential as a%of Res Sales 1.03% 1.59% 2.13% 2.68% 3.28% 3.83% 4.30% 4.71% 5.05% 5.32% Non Res Cumulative Potential as a%of Non-Res Sales 0.61% 1.22% 1.82% 2.40% 2.94% 3.38% 3.77% 4.13% 4.44% 4.70% As in the case when describing any feature of the public power community, the range of energy saving targets vary significantly. Generally, the larger the retail sales, the higher the energy savings targets as expressed as a percent of retail sales. However, even between utilities of similar size, trend lines of savings differ, indicating unique economic conditions customer mix, unique weather patterns, and other factors of each utility and the efforts of POUs to tailor programs to meet the needs of their respective customers. Table 4-1 provides the year by year NAVIGANT targets for each utility. Overall, the POUs are forecasted to save nearly 7,000,000MWh over the ten-year target period, averaging about 1% of retail sales each year. Table 4-2. Ten-Year Energy Savings Targets(MWh)by Utility, 2018-2027 Utility 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 10-year %of Sales Total Forecast Alameda Municipal Power 1,459 1,614 832 823 818 858 818 818 756 740 9,537 0.28% Anaheim,City of 28,098 28,104 26,801 26,140 25,830 25,071 23,855 23,053 21,812 20,458 249,221 1.00% Azusa,City of 2,813 3,089 2,943 2,824 2,769 2,682 2,565 2,512 2,410 2,257 26,863 1.01% Banning,City of 328 367 399 445 490 502 492 463 428 404 4,316 0.30% Biggs,City of 7 7 7 8 8 8 8 8 8 8 78 0.05% Burbank Water and Power 10,874 11,207 11,385 12,052 12,818 13,072 13,516 13,668 13,251 12,711 124,554 1.03% Colton Public Utilities 4,252 4,137 4,163 4,108 4,201 4,121 3,852 3,462 3,133 2,852 38,281 1.03% Corona,City of 9 9 7 6 5 5 4 4 3 3 56 0.00% Glendale Water and Power 14,801 14,723 14,634 14,160 13,998 13,528 12,447 11,534 10,682 9,966 130,474 1.16% Gridley Electric Utility 108 107 96 108 124 124 113 104 96 84 1,064 0.29% Healdsburg,City of 490 486 469 466 438 393 358 331 296 257 3,984 0.52% Imperial Irrigation District 33,475 33,760 33,952 32,232 30,894 28,668 27,685 26,708 25,027 22,435 294,836 0.79% Lassen MUD 353 371 318 339 356 359 352 350 332 320 3,450 0.25% _ Lodi Electric Utility 1,227 1,313 1,399 1,496 1,575 1,604 1,612 1,618 1,587 1,534 14,965 0.34% Lompoc,City of 213 236 249 266 282 300 313 324 326 320 2,829 0.20% Los Angeles DWR 377,701 382,463 377,413 351,678 331,494 307,521 293,832 297,211 287,665 277,376 3,284,355 1.25% Merced Irrigation District 1,258 1,346 1,452 1,551 1,597 1,586 1,525 1,455 1,392 1,350 14,512 0.30% Modesto Irrigation District 9,144 10,060 11,062 12,052 12,879 13,385 13,700 13,714 13,149 11,883 121,028 0.43% Moreno Valley Electric Utility 1,734 1,748 1,752 1,630 1,427 1,227 1,106 1,007 909 833 13,372 0.65% Needles,City of 19 20 22 25 27 29 27 21 15 10 216 0.04% Palo Alto,City of 7,280 7,284 7,760 7,757 8,253 8,146 8,631 8,647 9,139 9,152 82,049 0.85% Pasadena Water and Power 16,306 15,999 15,476 15,242 15,172 14,684 13,979 13,032 12,203 11,403 143,495 1.34% Pittsburg,City of 119 105 94 86 79 72 68 62 58 55 798 0.31% Plumas-Sierra REC 146 149 146 153 162 146 120 93 74 70 1,258 0.08% Port of Oakland 512 517 521 526 528 530 532 533 534 535 5,268 0.88% Rancho Cucamonga 288 293 313 347 388 411 416 409 393 375 3,634 0.46% Redding Electric Utility 3,336 3,466 3,666 3,858 3,629 3,439 3,438 3,352 3,234 2,695 34,113 0.45% Riverside,City of 20,594 20,815 20,309 19,451 18,492 17,505 16,426 15,403 14,310 12,968 176,275 0.76% Rose ille Electric 8,413 8,549 8,995 9,578 10,063 10,000 9,275 8,556 7,977 7,895 89,302 0.76% Sacramento MUD 149,626 154,902 164,286 175,198 183,687 187,401 181,428 168,982 157,634 145,870 1,669,015 1.40% San Francisco PUD 2,736 2,853 2,764 2,657 2,596 2,524 2,435 2,324 2,255 2,209 25,352 0.24% Shasta Lake,City of 487 519 550 579 600 635 635 601 551 482 5,639 0.30% Silicon Valley Power 12,851 13,032 14,015 14,928 15,129 14,565 13,333 12,192 11,528 10,590 132,163 0.42% Trinity PUD 7 6 6 6 6 6 6 6 6 6 61 0.01% Truckee Donner PUD 730 639 654 672 689 693 693 686 685 679 6,820 0.45% Turlock Irrigation District 12,994 12,987 12,909 12,143 11,615 10,893 10,536 10,316 10,152 9,479 114,024 0.49% Ukiah,City of 398 441 484 520 550 575 599 617 625 626 5,437 0.48% Vernon,City of 5,268 5,218 5,523 5,618 5,544 5,145 4,536 4,147 3,900 3,557 48,457 0.40% Victonille,City of 149 163 178 196 212 223 228 228 223 214 2,012 0.22% Total 730,604 743,103 748,003 731,926 719,424 692,637 665,495 648,551 618,758 584,662 6,883,162 1.02% Source: Navigant • 4.2 Comparison of the Current Targets with the 2012 Targets and Identifying Utilities that Claim Net or Gross Saving Targets and C&S Claims Table 4-3 identifies which utilities claim Gross vs Net saving targets and whether they claim savings from C&S. Most of the POUs claim Net saving targets (77%) and most do not claim savings from C&S (69%). NAVIGANT Navigant approached the comparison of the targets developed in 2012 to the current targets by comparing the years 2018-2023, which are the overlap years between the two 10-year study periods. The comparisons are between the goals as expressed as % of retail sales as Navigant discovered that the forecast of retail sales changed for many of the utilities. Overall, the most recent targets are on average 138% of the 2012 goals. About 56% of the POUs have higher goals than 2012. The POUs with lower goals are generally the smaller utilities. Some of the utilities have higher goals because they now claim C&S savings and/or claim Gross rather than Net savings. However, the calibration targets for many of the utilities are lower in this round of target setting, reflecting their actual achievements over the past three years. NAVIGANT Table 4-3. Identifying Utilities Net or Gross Saving Targets, C&S, and Comparison to 2012 Targets Utility Net or Gross Includes C&S? Compare to 2012 Savings Targets Alameda Municipal Power Net No Higher Anaheim,City of Gross Yes Higher Azusa,City of Net Yes Higher Banning,City of Net No Lower Biggs,City of Net No Lower Burbank Water and Pow er Gross No Higher Colton Public Utilities Net Yes Higher Corona,City of Net No Lower Glendale Water and Pow er Net Yes Higher Gridley Electric Utility Net No Lower Healdsburg,City of Net No Higher Imperial Irrigation District Net Yes Higher Lassen Municipal Utility District Net No Lower Lodi Electric Utility Net No Lower Lompoc,City of Gross No Higher Los Angeles Department of Water&Pow er Gross Yes Higher Merced Irrigation District Net No Lower Modesto Irrigation District Net No Lower Moreno Valley Electric Utility Net Yes Higher Needles,City of Net No Lower Palo Alto,City of Net No Higher Pasadena Water and Power Net Yes Higher Pittsburg,City of Net No Lower Plumas-Sierra Rural Electric Cooperative Net Nb Higher Port of Oakland Gross No Higher — Rancho Cucamonga Municipal Utility Gross No Lower Redding Electric Utility Net No Higher Riverside,City of Net Yes Higher Roseville Electric Gross No Higher Sacramento Municipal Utility District Gross Yes Higher San Francisco Public Utilities Commission Net No Lower Shasta Lake,City of Net No Higher Silicon Valley Power Net No Lower Trinity Public Utilities District Net No Lower Truckee Donner Public Utilities District Gross No Lower Turlock Irrigation District Net Yes Higher Ukiah,City of Net No Higher Vernon,City of Net Yes Within+1-2.5% Victorville,City of Net No Lower Total Net=77% No=69% Higher by 138% Source: Navigant NAVIGANT Appendix A. Utility ELRAM Results Results for the following utilities are provided: • Sum of All Utilities • Alameda Municipal Power • Anaheim, City of • Azusa, City of • Banning, City of • Biggs, City of • Burbank Water and Power • Colton Public Utilities • Corona, City of • Glendale Water and Power • Gridley Electric Utility • Healdsburg, City of • Imperial Irrigation District • Lassen Municipal Utility District • Lodi Electric Utility • Lompoc, City of • Los Angeles Department of Water& Power • Merced Irrigation District • Modesto Irrigation District • Moreno Valley Electric Utility • Needles, City of • Palo Alto, City of • Pasadena Water and Power • Pittsburg, City of • Plumas-Sierra Rural Electric Cooperative • Port of Oakland NAVIGANT • Rancho Cucamonga Municipal Utility • Redding Electric Utility • Riverside, City of • Roseville Electric • Sacramento Municipal Utility District • San Francisco Public Utilities Commission • Shasta Lake, City of • Silicon Valley Power • Trinity Public Utilities District • Truckee Donner Public Utilities District • Turlock Irrigation District • Ukiah, City of • Vernon, City of • Victorville, City of NAVIGANT All Utilities Ten Year Incremental Goals -(2018-2027) 800,000 1.25% 700,000 1.05% 600,000 i 0.85 500,000 0.65% 400,000 7. 0.45 300,000 i a 200,000 0.25% o 100,000 0.05% 0 -0.15% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 NM Res Incremental Market Potentia I I=Non-Res Incremental Market Potential IIIMC&S(If Claimed.Estimates not available after 2024) —4—Total Incremental Potential as a%of Total Sales 10-Year Energy Goals(MWh( ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 730,604 743,103 748,003 731,926 719,424 692,637 665,495 648,551 618,758 584,662 Res Incremental Market Potential 220,455 223,669 224,061 238,800 254,873 263,322 261,937 254,221 247,101 239,894 Non-Res Incremental Market Potential 267,494 275,766 280,439 276,669 266,777 250,271 233,905 218,811 203,325 183,251 C&S(If Claimed.Estimates not available after 2024) 242,655 243,668 243,502. 216,456 197,774 179,044 169,654 175,520 168,331 161,516 Total Incremental Potential as a%of Total Sales 1.13% 1.14% 1.14% 1.10% 1.07% 1.02% 0.97% 0.93% 0.88% 0.82% Res Incremental Potential as a%of Res Sales 1.03% 1.04%. 1.02% 1.07% 1.12% 1.14% 1.12% 1.07% 1.02% 0.98% Non-Res Incremental Potential as a%of Non-Res Sales 0.61% 0.63% 0.63% 0.62% 0.59% 0.55% 0.51% 0.47% 0.44% 0.39% 10-Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 915,208 877,439 894,304 924,355 942,234 803,442 716,813 2,022,581 1,935,838 1,857,823 Res Incremental Market Potential 29,733 29,870 31,226 34,144 37,074 38,744 39,557 37,772 37,499 36,536 Non-Res Incremental Market Potential 821,424 782,008 796,235 825,248 842,441 702,934 617,260 316,255 295,479 281,370 C&S(If Claimed.Estimates not available after 2024) 64,050 65,561 66,843 64,964 62,718 61,764 59,996 1,668,554 1,602,860 1,539,917 All Utilities Ten-Year Cumulative Goals -(2018-2027) 6,000,000 9.00% HH 5,000,000 °i 4,000,000 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 MN Res Cumulative Market Potential Non-Res Cumulative Market Potential -C&S(If Cla imed.Estimates not available after 2024) --Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumul ative Market Potential. 730,604 1,366,953 2,006,544 2,621,203 3,216,761 3,744,385 4,228,033 4,690,318 5,118,861 5,503,266 Res Cumulative Market Potential 220,455 344,178 466,801 598,290 743,374 881,896 1,005,803 1,118,851 1,219,832 1,305,885 Non-Res Cumulative Market Potential 267,494 536,453. 809,918 1,076,633 1,329,332 1,539,390 1,729,476 1,903,194 2,062,425 2,199,261 C&S(If Claimed.Estimates not available after 2024) 242,655 486,322 729,824 946,281 1,144,055 1,323,099 1,492,753 1,668,273 1,836,604 1,998,120 Total Cumulative Potential as a%of Total Sales 1.13% 2.10% 3.04% 3.94% 4.78% 5.50% 6.15% 6.75% 7.30% 7.76% Res Cumulative Potential as a%of Res Sales 1.03% 1.59% 2.13% 2.68% 3.28% 3.83% 4.30% 4.71% 5.05% 5.32% Non Res Cumulative Potential as a%of Non-Res Sales 0.61% 1.22% 1.82% 2.40% 2.94% 3.38% 3.77% 4.13% 4.44% 4.70% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative 6W) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 913,518 1,723,251 2,548,307 3,401,417 4,273,423 4,707,877 5,040,554 6,667,053 6,580,818 6,461,173 Res Cumulative Market Potential 29,733. 59,476 90,566 124,654 161,661 196,452 228,987 259,554 289,400 317,675 Non Res Cumulative Market Potential W..._ 819,734 1,598,215. 2,390,897 3,211,798 4,049,043 4,449,662 4,751,572 4,738,945 4,688,558 4,603,581 C&S(If Claimed.Estimates not available after 2024) 64,050 65,561 66,843 64,964 62,718, 61,764 59,996 1,668,554 1,602,860 1,539,917 NAVIGANT Alameda Ten Year Incremental Goals -Net(2018-2027) Incremental Market Potential by Sector 2,000 All Sectors Energy Potential(MWh)and%of Sales 0.50% 1,500 0.40% i. 0.30% 3 t 0 g1,000 - - -- — - - ------- - - - - -- - - - ----- - 50: _.. . ... II I0.10% * 0 0.00 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential Non-Res Incremental Market Potential MINC&S(If Claimed.Estimates not ava ih ble after 2024) -y—Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net(1/1Wh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,459 1,614 832 823 818 858 818 818 756 740 Res Incremental Market Potential 305 296 170 168 169 209 175 185 131 135 Non-Res Incremental Market Potential 1,154 1,317 661 655 649 649 643 633 626 605 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.43% 0.48% 0.25% 0.25% 0.25% 0.26% 0.24% 0.24% 0.22% 0.22% Res Incremental Potential as a%of Res Sales 0.25% 0.24% 0.14% 0.13% 0.14% 0.17% 0.14% 0.14% 0.10% 0.10% Non-Res Incremental Potential as a%of Non-Res Sales 0.55% 0.63% 0.31% 0.31% 0.31% 0.31% 0.31% 0.30% 0.30% 0.29% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 242 367 158 151 147 149 147 149 146 143 Res Incremental Market Potential 26 24 15 9 8 10 8 10 6 8 Non-Res Incremental Market Potential 216 343 143 142 139 139 139 139 139 136 C&5(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Alameda Ten Year Cumulative Goals -Net(2018-2027) Cumulative Market Potential by Sector 10,000 All Sectors Energy Potential(MWh)and%of Sales 3.00% 8,000 2.50% 2.00% t 6,000 3 31.50°i — 4,000 1.00% a` 2,000 0.50% • 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 INIIIIIRes Cumulative Market Potential Non-Res Cumulative Market Potential IIMIC&S(If Claimed_Estimates not available after 2024) ...41.-Total.Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1,459 3,073 3,905 4,728 5,546 6,361 7,082 7,805 8,472 9,133 Res Cumulative Market Potential 305 601 772 940 1,109 1,299 1,421 1,559 1,648 1,769 Non-Res Cumulative Market Potential 1,154 2,472 3,133 3,788 4,437 5,062 5,661 6,246 6,824 7,364 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.43% 0.92% 1.16% 1.41% 1.66% 1.90% 2.11% 2.32% 2.51% 2.70% Res Cumulative Potential as a%of Res Sales 0.25% 0.48% 0.62% 0.75% 0.89% 1.04% 1.12% 1.22% 1.27% 1.35% Non-Res Cumulative Potential as a%of Non-Res Sales 0.55% 1.17% 1.49% 1.80% 2.12% 2.42% 2.71% 3.00% 3.29% 3.56% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 202S 2026 2027 Total Cumulative Market Potential 242 609 767 918 1,065 1,210 1,345 1,482 1,617 1,752 Res Cumulative Market Potential 26 50 65 74 82 91 91 93 93 101 Non-Res Cumulative Market Potential 216 559 702 844 983 1,119 1,254 1,389 1,524 1,652 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Anaheim Ten Year Incremental Goals -Gross(2018-2027) Incremental Gross Market Potential by Sector 40000 All Sectors Energy Potential(MWh)a nd%of Sales 0.015 30000 3 20000 0.01 t7 0.005 T. 0000 i3 le."'".'""."411"'"'""n"."."""""""4ii""''.""e".""""""Il""'""'""""S""""""""S"."""""lbTlrlill0 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential I♦Non-Res Incremental Market Potential IIIIMIC&S(If Claimed.Estimates not available after 2024) tTotal Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 28,098 28,104 26,801 26,140 25,830 25,071 23,855 23,053 21,812 20,458 Res Incremental Market Potential 4,040 4,176 2,906 3,026 3,031 3,111 2,583 2,836 2,712 2,638 Non-Res Incremental Market Potential 14,717 15,062 15,550 16,062 16,446 16,466 16,237 15,601 14,869 13,941 C&S(If Claimed.Estimates not avai!able after 2024) 9,342 8,866 8,345 7,051 6,353 5,494 5,036 4,616 4,231 3,878 Total Incremental Potential as a%of Total Sales 1.15% 1.15% 1.09% 1.06% 1.04% 1.00% 0.95% 0.91% 0.86% 0.80% Res Incremental Potential as a%of Res Sales 0.64% 0.66% 0.46% 0.48% 0.47% 0.48% 0.40% 0.44% 0.42% 0.40% Non-Res Incremental Potential as a%of Non-Res Sales 0.80% 0.82% 0.84% 0.87% 0.88% 0.88% 0.86% 0.83% 0.78% 0.73% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 6,303 6,404 6,347 6,548 6,792 6,508 6,479 6,429 6,216 5,954 Res Incremental Market Potential 741 774 691 715 725 737 699 725 724 725 Non-Res Incremental Market Potential 3,067 3,220 3,489 3,853 4,200 4,027 4,135 4,154 4,032 3,853 C&S(If Claimed.Estimates not available after 2024) 2,494 2,411 2,166 1,980 1,866 1,744 1,644 1,549 1,460 1,376 Total Incremental Potential as a%of Demand 1.13% 1.12% 1.16% 1.20% 1.15% 1.14% 1.13% 1.09% 1.05% Anaheim Ten Year Cumulative Goals-Gross(2018-2027) Cumulative Market Potential by Sector 250000 All Sectors Energy Potential(MWh)a nd%of Sales 0.1 200000 0.08 d 16 kn 150000 0.06 2 0.04 100000 `o 50000 0.02 0 0 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Cumulative Market Potential I=Non-Res Cumulative Market Potential 1.1111C&S(If Claimed.Estimates not available after 2024) -Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross MWh) ALL Sectors(Cumulative MW6) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 28,098 54,010 78,619 102,567 126,204 149,021 169,780 189,696 208,332 225,464 Res Cumulative Market Potential 4,040 8,216 11,122 14,148 17_179 20,248 22,298 24,560 26,662 28,660 Non Res Cumulative Market Potential 14,717 27,587 40,945 54,815 69,068 83,322 96,996 110,034 122,337 133,592 C&5(If Claimed.Estimates not available after 2024) 9,342 18,207 26,552 33,604 39,957 45,451 50,486 55,102 59,333 63,212 Total Cumulative Potential as a%of Total Sales 1.15% 2.20% 3.19% 4.15% 5.08% 5.97% 6.76% 7.52% 8.22% 8.85% Res Cumulative Potential as a%of Res Sales 0.64% 1.30% 1.76% 2.22% 2.69% 3.15% 3.46% 3.79% 4.09% 4.38% Non-Res Cumulative Potential as a%of Non-Res Sales 0.80% 1.50% 2.22% 2.95% 3.71% 4.45% 5.15% 5.82% 6.44% 7.00% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 6,303 10,213 14,149 18,531 23,342 27,974 32,589 37,245 41,774 46,115 Res Cumulative Market Potential 741 1,515 2,207 2,922 3,647 4,375 4,957 5,555 6,144 6,727 Non Res Cumulative Market Potential 3,067 6,287 9,776 13,628 17,829 21,854 25,988 30,140 34,170 38,011 C&S(If Claimed.Estimates not available after 2024) 2,494 2,411 2,166 1,980 1,866 1,744 1,644 1,549 1,460 1,376 NAVIGANT Azuza Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector 4,000 All Sectors Energy Potential(M Wh)a nd%of Sales 1.50% 43 3,000 — 1.00% , 3 c9 2,000 050% a` 1,000 'o g 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 MINIRes Incremental Market Potential Non-Res Incremental Market Potential C&5(If Claimed.Estimates not ava ila Isle after 2024) ••Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 2,813 3,089 2,943 2,824 2,769 2,682 2,565 2,512 2,410 2,257 Res Incremental Market Potential 358 373 397 424 449 470 485 495 496 470 Non-Res Incremental Market Potential 1,242 1,233 1,263 1,281 1,272 1,217 1,187 1,162 1,117 1,046 C&S(If Claimed.Estimates not available after 2024) 1,213 1,482 1,283 1,119 1,047 995 892 856 797 741 Total Incremental Potential as a%of Total Sales 1.07% 1.17% 1.11% 1.07% 1.04% 1.00% 0.96% 0.93% 0.90% 0.84% Res Incremental Potential as a%of Res Sales 3.06% 3.18% 3.38% 3.60% 3.80% 3.96% 4.07% 4.13% 4.15% 3.93% Non-Res Incremental Potential as a%of Non-Res Sales 0.49% 0.49% 0.50% 0.50% 0.50% 0.48% 0.46% 0.45% 0.43% 0.41% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Icremental Market Potential 2,034 2,144 2,157 2,203 2,238 1,917 1,937 1,959 1,974 1,979 Res Incremental Market Potential 7 8 8 9 9 10 10 10 10 10 Non-Res Incremental ncrementa Market Potential 1,794 1,831 1,877 1,927 1,977 1,680 1,716 1,744 1,766 1,783 C&S(If Claimed.Estimates not available after 2024) 232 306 272 267 251 228 212 206 197 187 Azuza Ten Year Cumulative Goals-Net(2018-2027) • 8. 1..8 M•MAI ks t Plat sn11r.31 try Sak:1(H an nn All Sectors Enor fly Potnnlial(MWh)and%al Saks prune 25.000 tlxrr. to«xl adi cnes t N.C.:, 2.cn., • • l.00 a 0.00% 2013 2019 2020 1021 2022 2023 2021 2020 2020 2027 IlHns r.,muiat,ve Mars.,vntnrx,ai INIMINnn Iles..untulatt.,e Marler Y70entui CCB,tit C'uutatJ t•0 i,r,alvs nut ava1al7.att...2070 yt..Tut,Ctontalutiw eutotitlial as a"a a T.,lal Sats 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 2,813 5,902 8,845 11,668 14,433 16,677 18,791 20,787 22,658 24,345 Res Cumulative Market Potential 358 731 1,128 1,552 1,997 2,298 2,606 2,914 3,212 3,472 Non-Res Cumulative Market Potential 1,242 2,475 3,737 5,018 6,290 7,238 8,152 8,985 9,761 10,447 C&S(If Claimed.Estimates not available after 2024) 1,213 2,696 3,979 5,099 6,146 7,141 8,033 8,889 9,685 10,426 Total Cumulative Potential as a%of Total Sales 1.07% 2.24% 3.35% 4.40% 5.43% 6.25% 7.01% 7.73% 8.42% 9.05% Res Cumulative Potential as a%of Res Sales 3.06% 6.23% 9.60% 13.16% 16.88% 19.35% 21.87% 24.35% 26.85% 29.02% Non-Res Cumulative Potential as a%of Non-Res Sales 0 49% 0.98% 1.48% 1.97% 2.47% 2.83% 3.17% 3.50% 3.80% 4.06% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 2,034 3,946 5,797 7,727 9,696 8,737 7,753 6,710 5,619 4,473 Res Cumulative Market Potential 7 15 23 32 41 51 61 70 80 90 Non-Res Cumulative Market Potential 1,794 3,625 5,502 7,429 9,404 8,459 7,481 6,434 5,341 4,196 C&S(If Claimed.Estimates not available after 2024) 232 306 272 267 251 228 212 206 197 187 NAVIGANT Banning Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector 600 All Sectors Energy Potential(MWh)and%of Sales 040% 500 0.30% 400 kD300 0.20%A 200 ic 0.10%`o 100 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential MIMI Non-Res Incremental Market Potential t Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 328 367 399 445 490 502 492 463 428 404 Res Incremental Market Potential 163 179 183 196 213 228 239 247 253 259 Non-Res Incremental Market Potential 165 188 216 249 277 274 252 216 175 144 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.23% 0.26% 0.28% 031% 034% 0.34% 033% 031% 0.29% 0.26% Res Incremental Potential as a%of Res Sales 0.24% 0.27% 0.27% 0.29% 0.31% 0.33% 0.35% 0.36% 0.36% 0.37% Non-Res Incremental Potential as a%of Non-Res Sales 0.21% 0.24% 0.28% 0.32% 0.35% 0.34% 0.31% 0.26% 0.21% 0.17% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 84 92 100 110 122 126 123 115 108 106 Res Incremental Market Potential 55 58 60 64 69 74 77 79 81 82 Non-Res Incremental Market Potential 29 34 40 47 53 52 46 36 28 24 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Banning Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector a All Sectors Energy Potential(MWIh)and%ol Sales <»„ a„rl w. ,ar, tr ger_isris----t-i----i-iiiirlill 'r`A r'• MIR :fin 70, >n)I 7o77 >MI CNet .rm.rlar we Mnrl.et vrvemral MIMINnn Iter.I tim.rlative MarAet Pntmrxrl C&5 nl C4irrwU.f st•reutrs IAA availa4M atter 10:41 -total Cunwlativr Pulxnt,al as a S W Total sa M, 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumul0ive MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 328 694 1,094 1,539 2,029 2,529 3,000 3,441 3,845 4,220 Res Carnal ative Market Potential 163 342 525 722 934 1,161 1,381 1,606 1,837 2,075 Non-Res Cumulative Market Potential 165 352 568 817 1,094 1,368 1,619 1,834 2,007 2,146 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.23% 0.49% 0.76% 1.07% 1.40% 1.73% 2.04% 2.32% 2.56% 2.75% Res Cumulative Potential as a%of Res Sales 0.24% 0.51% 0.79% 1.07% 1.38% 1.70% 2.01% 2.32% 2.62% 2.92% Non-Res Cumulative Potential as a%of Non-Res Sales 0.21% 0.45% 0.73% 1.04% 1.38% 1.71% 2.01% 2.25% 2.43% 2.56% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 84 176 275 386 507 633 752 862 966 1,067 Res Cumulative Market Potential 55 112 172 236 305 378 452 527 603 681 Non-Res Cumulative Market Potential 29 63 103 150 202 254 300 335 363 387 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Biggs Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector 10 All Sectors Energy Potential(M Wh)a nd%of Sales 0.08% s 0.06% 3 0.04% 4 a` 0.02% 0 0.00 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Mill Res Incremental Market Potential MI Non-Res Incremental Market Potential IMINIC&S(If Claimed.Estimates not available after 2024) Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 7 7 7 8 8 8 8 8 8 8 Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Incremental Market Potential 6 7 7 7 8 8 8 8 8 8 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.05% 0.05% 0.05% 0.05% 0.05% 0.06% 0.06% 0.06% 0.06% 0.06% Res Incremental Potential as a%of Res Sales 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% Non-Res Incremental Potential as a%of Non-Res Sales 0.07% 0.07% 0.07% 0.07% 0.08% 0.08% 0.08% 0.08% 0.08% 0.08% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2026 2026 2027 Total Incremental Market Potential 1 1 1 1 1 1 1 I 1 1 Res Incremental Market Potential 0 0 0 0 0 0 0 0 1 1 Non-Res Incremental Market Potential 1 1 1 1 1 1 I 1 1 1 C&5(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Biggs Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector cer All Sectors Energy Potential(MWh)and%of Sales Q »< tui 60 0.40% c S0 40 30 0.20`e O.ttPri 10 C.U4 -Cllfl ]01'1 :WO )021 LO.'b 2023 1AIa 1b>5 2lYti 202) =MIR.,Lill,Maine Market 1,1w:f :at INun:Rr•a Cumulate.Market Potentia: M.Grin Of Claimer,envy:ate,not available after 10241 -0-tot,CurnuralivC rolvntial ar.a%of Total SaM: 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 7 14 21 29 37 45 53 61 70 78 Res Cumulative Market Potential 0 1 1 1 2 2 3 3 3 4 Non-Res Cumulative Market Potential 6 13 20 27 35 43 50 58 66 74 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.05% 0.10% 0.14% 0.20% 0.25% 0.31% 0.37% 0.42% 0.48% 0.54% Res Cumulative Potential as a%of Res Sales 0.01% 0.01% 0.02% 0.03% 0.04% 0.05% 0.05% 0.06% 0.07% 0.08% Non-Res Cumulative Potential as a%of Non-Res Sales 0.07% 0.13% 0.20% 0.28% 0.35% 0.43% 0.51% 0.60% 0.68% 0.76% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) _ 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1 2 3 4 6 7 8 9 11 12 Res Cumulative Market Potential 0 1 1 2 2 3 3 4 4 5 Non-Res Cumulative Market Potential 1 1 2 3 3 4 5 6 7 7 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Burbank Ten Year Incremental Goals -Gross(2018-2027) Incremental Gross Market Potential by Sector 15,000 All Sectors Energy Potential(MWh)and%of Sales 1.20% io,000 L00% -u2,63 0.80% 8 5,000 00.4200: 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 IMERes Incremental Market Potential Non-Res Incremental Market Potential NMI C&S Of Claimed) --Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL.Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 10,874 11,207 11,385 12,052 12,818 13,072 13,516 13,668 13,251 12,711 Res Incremental Market Potential 4,021 4,194 4,017 4,176 4,338 4,479 4,492 4,551 4,541 4,523 Non-Res Incremental Market Potential 6,853 7,013 7,368 7,876 8,481 8,593 9,023 9,117 8,710 8,188 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.94% 0.96% 0.96% 1.01% 1.06% 1.07% 1.10% 1.10% 1.06% 0.99% Res Incremental Potential as a%of Res Sales 1.41% 1.46% 1.38% 1.42% 1.46% 1.49% 1.48% 1.49% 1.47% 1.45% Non-Res Incremental Potential as a%of Non-Res Sales 0.77% 0.78% 0.81% 0.86% 0.91% 0.92% 0.95% 0.95% 0.90% 0.84% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential • 4,150 4,331 4,504 4,716 4,944 4,739 4,951 5,063 5,028 4,895 Res Incremental Market Potential 1,107 1,175 1,222 1,300 1,380 1,452 1,506 1,547 1,569 1,546 Non-Res Incremental Market Potential 3,043 3,155 3,282 3,416 3,564 3,286 3,445 3,516 3,459 3,349 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Burbank Ten Year Cumulative Goals-Gross(2018-2027) Cumulative Market Potential by Sector 100000 All Sectors Energy Potential(MWh)and%of Sales 0.08 80000 To 'ai 0.06 in 60000 k9 0.04 76 m 40000 •iI 0.02 'i5 20000 " 0 0 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 MI1Res Cumulative Market Potential Non-Res Cumulative Market Potential IMMIIC&S(If Claimed) .41..Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 10,874 19,538 28,355 37,813 48,011 56,895 66,084 75,178 83,782 91,703 Res Cumulative Market Potential 4,021 5,672 7,121 8,703 10,421 12,250 13,985 15,746 17,467 19,133 Non-Res Cumulative Market Potential 6,853 13,866 21,233 29,109 37,590 44,645 52,099 59,432 66,315 72,570 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.94% 1.67% 2.40% 3.17% 3.98% 4.67% 5.37% 6.05% 6.68% 7.18% Res Cumulative Potential as a%of Res Sales 1.41% 1.97% 2.45% 2.96% 3.51% 4.08% 4.62% 5.15% 5.65% 6.13% Non-Res Cumulative Potential as a%of Non-Res Sales 0.77% 1.54% 2.33% 3.17% 4.05% 4.76% 5.50% 6.22% 6.87% 7.44% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 4,150 8,480 12,985 17,701 22,646 26,038 29,564 33,065 36,495 39,749 Res Cumulative Market Potential 1,107 2,282 3,505 4,805 6,185 7,637 9,089 10,578 12,086 13,568 Non-Res Cumulative Market Potential 3,043 6,198 9,480 12,896 16,460 18,401 20,475 22,487 24,409 26,182 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 • NAVIGANT Colton Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector 5,000 All Sectors Energy Potential(MWh)a nd%of Sales 1.50% 4,000 1.00%, 3,000 3 2,000 cc 0.50% a 0 1,000 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 ti Res Incremental Market Potentbl MN Non-Res Incremental Market Potential t•C&S(If Claimed.Estimates not available after 2024) —Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 4,252 4,137 4,163 4,108 4,201 4,121. 3,852 3,462 3,133 2,852 Res Incremental Market Potential 149 166 153 170 194 225 264 291 293 292 Non-Res Incremental Market Potential 2,457 2,429 2,541 2,617 2,734 2,710 2,481 2,138 1,877 1,661 C&S(If Claimed.Estimates not available after 2024) 1,646 1,542 1,469 1,322 1,272 1,186 1,106 1,032 964 899 Total Incremental Potential as a%of Total Sales 1.16% 1.13% 1.13% 1.11% 1.13% 1.11% 1.03% 0.93% 0.84% 0.76% Res Incremental Potential as a%of Res Sales 1.07%. 1.19% 1.10% 1.21% 1.38% 1.60% 1.87% 2.06% 2.07% 2.07% Non-Res Incremental Potential as a%of Non-Res Sales 0.69% 0.69% 0.71% 0.73% 0.76% 0.75% 0.69% 0.59% 0.52% 0.46% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,013 1,007 1,010 1,012 1,028 973 944 904 870 835 Res Incremental Market Potential 28 30 30 33 37 41 46 51 53 54 Non-Res Incremental Market Potential 597 612 643 666 686 639 621 591 568 545 C&S(If Claimed.Estimates not available after 2024) 388 365 336 313 305 293 277 262 249 235 Colton Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector 40,000 All Sectors Energy Potential(MWh)a nd%of Sales 1 12.00% 30,000 10.00'/0 F imr.......irilutt 8.00 -g 20,000 • 6.00% 2.00% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 ti Res Cumulative Market Potential MIIINon-Res Cumulative Market Potential tiC&S(If Claimed.Estimates not available after 2024) —Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulat(ve MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 4,252 8,389 12,552 16,660 20,799 24,853 28,623 32,013 35,079 37,857 Res Cumulative Market Potential 149 315 468 637 831 1,054 1,302 1,576 1,852 2,127 Non-Res Cumulative Market Potential 2,457 4,886 7,428 10,044 12,717 15,362 17,778 19,862 21,688 23,292. C&S(If Claimed.Estimates not available after 2024) 1,646 3,188 4,657 5,978 7,251 8,436 9,543 10,575 11,539 12,438 Total Cumulative Potential as a%of Total Sales 1.16% 2.29% 3.41% 4.51% 5.61% 6.68% 7.67% 8.56% 9.38% 10.11% Res Cumulative Potential as a%of Res Sales 1.07% 2.27% 3.36% 4.56% 5.92% 7.49% 9.22% 11.13% 13.08% 15.02% Non-Res Cumulative Potential as a%of Non-Res Sales 0.69% 1.38% 2.09% 2.81% 3.55% 4.27% 4.93% 5.51% 6.02% 6.46% 10 Year Demand Goats(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1,013 1,632 2,277 2,952 3,659 4,318 4,959 5,576 6,174 6,749 Res Cumulative Market Potential 28 58 89 122 158 199 242 289 339 389 Non-Res Cumulative Market Potential 597 1,209 1,852 2,518 3,196 3,827 4,440 5,024 5,586 6,124 C&S(If Claimed.Estimates not available after 2024) 388 365 336 313 305 293 277 262 249 235 NAVIGANT Corona Ten Year Incremental Goals-Net(2018-2027) Net Incremontal Market Potential by Sector All Sectors!new Potential(MVO))and%"I Sall_, 10 R 7 0 01N AV ... 1 o.colv 7..' n 00, ., I 70in NM 10-•kIrr,rnkr,sal Market 1,troataal =MN Non Itr.ainemrnr-ras,Mark,aMate.M.ai min c.8.s(II,Ialirnel,(Mitfmtka Mat Wv..11-alk•+(Lei.43,..0 -411,1 0141 illtIct manta]P014,0141 as a 4.W ILA..yeles 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 9 9 7 6 S 5 4 4 3 3 Res Incremental Market Potential 9 9 7 6 5 5 4 4 3 3 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Esti mates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incrernental Potential as a%of Total Sales 0.01% 0.01% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Res Incremental Potential as a%of Res Sales 0.22% 0.23% 0.18% 0.16% 0.13% 0.11% 0.10% 0.09% 0.08% 0.07% Non-Res Incremental Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1 1 1 1 1 1 1 1 1 0 Res Incremental Market Potential 1 1 1 1 1 1 1 1 1 0 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Corona Ten Year Cumulative Goals-Net(2018-2027) Nei Cumulative Mae ket Poteillial by Sector .• Mr All Sectors E nergy Potential(MWh)and%of Sales 0 fail, 010, . ,I • allitkc. v • • ("1,,.• • II .3:Iti, AV I I., Ilb.1 10, SEMI 1-0,l mallow',rkirorkrq VoMrrrea; MEM Nnn%N.a‘ktreat.karmr.Mark.,kantentvii OEM CAS(II r'lamonal tat irrul aa IAA avaikalstr.ft..J024) ...II....TW al Cugrmiativr OkstoMial 4,a%a Tula.Sala, 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 9 18 26 32 38 42 47 50 53 56 Res Cumulative Market Potential 9 18 26 32\ 38 42 47 50 53 56 Non-Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.01% 0.01% 0.02% 0.02% 0.02% 0.03% 0.03% 0.03% 0.03% 0.04% Res Cumulative Potential as a%of Res Sales 0.22% 0.45% 0.63% 0.78% 0.91% 1.02% 1.11% 1.20% 1.28% 1.34% Non-Res Cannulation Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1 2 3 4 5 6 6 7 7 8 Res Cumulative Market Potential 1 2 3 4 5 6 6 7 7 a Non-Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 C8)5(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 • NAVIGANT Glendale Ten Year Incremental Goals-Net(2018-2027) Net if..o.netttal lkAarki_it Potential by Sector All Sectors Fnergy Potential(mwily and%of Sales 'neon i.nok. 141,1111 1-1,,, „ /018 /.1,1 J<V2.1 /0.13 1,,,,S Jil), "If/ ,,,,e,n•erl,1 vote•tat •••••11,••oes irxr•r.,,e1Nnterl,•1 Pole•irol MEM 0,,i",..”,.1 -0-,t, ,,,,,,,"`".^,,,o.,,%,..,..,,.,,.,, 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 14,801 14,723 14,634 14,160 13,998 13,528 12,447 11,534 10,682 9,966 Res Incremental Market Potential 3,778 3,809 3,841 3,878 3,928 3,957 3,967 3,986 3,990 3,993 Non-Res Incremental Market Potential 4,952 5,000 5,228 5,507 5,727 5,797 4,927 4,202 3,543 3,007 C&S(If Claimed) 6,070 5,914 5,565 4,774 4,343 3,774 3,553 3,346 3,150 2,966 Total Incremental Potential as a%of Total Sales 1.34% 1.33% 1.31% 1.26% 1.24% 1.19% 1.09% 1.01% 0.93% 0.87% Res Incremental Potential as a%of Res Sales 0.95% 0.96% 0.96% 0.96% 0.97% 0.97% 0.97% 0.97% 0.97% 0.97% Non-Res Incremental Potential as a%of Non-Res Sales 0.69% 0.70% 0.73% 0.76% 0.78% 0.79% 0.67% 0.57% 0.48% 0.41% 10 Year Demand Goals(kW) ALL Redo!,(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 5,392 5,640 6,125 6,831 7,549 6,891 6,832 1,108,974 1,065,294 1,023,445 Res Incremental Market Potential 156 162 167 170 170 170 169 168 167 166 Non-Res Incremental Market Potential 3,694 3,953 4,497 5,310 6,097 5,522 5,513 5,428 5,307 5,186 C&5(If Claimed) 1,542 1,526 1,461 1,351 1,282 1,200 1,149 1,103,378 1,059,820 1,018,093 Glendale Ten Year Cumulative Goals-Net(2018-2027) Net C.66666 LILO ivy Markel Poles trial by Senior All Sect OM I nergy Potential(MWh)and%at Sales Hilt, 1 1.„oitt A :•'.5.: “1"11(1 ci Ref Cu.r WI et nee M•rfel.>ote,,a1 11111•111‘.•,-Res ivr•ubt•••Markct Fote,,tts• IMMICS.S111C4••••••) -0-TottO Cornuldmve Potent,a,•a•.•ot Tota So,ea 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 14,801 25,984 37,066 47,661 58,075 67,865 76,573 84,386 91,327 97,422 Res Cumulative Market Potential 3,778 4,047 4,336 4,649 4,992 5,333 5,657 5,990 6,311 6,623 Non-Res Cumulative Market Potential 4,952 9,952 15,181 20,688 26,415 32,090 36,921 41,056 44,527 47,343 C&S(If Claimed) 6,070 11,985 17,550 22,324 26,667 30,441 33,995 37,340 40,490 43,456 Total Cumulative Potential as a%of Total Sales 1.34% 2.34% 3.32% 4.25% 5.13% 5.97% 6.72% 7.38% 7.97% 8.47% Res Cumulative Potential as a%of Res Sales 0.95% 1.02% 1.08% 1.16% 1.23% 1.31% 1.38% 1.46% 1.53% 1.61% Non-Res Cumulative Potential as a%of Non-Res Sales 0.69% 1.39% 2.11% 2.85% 3.62% 4.38% 5.02% 5.57% 6.03% 6.40% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 5,392 9,483 14,067 19,416 25,588 31,151 36,725 1,144,494 1,106,352 1,069,902 Res Cumulative Market Potential 156 310 462 611 755 895 1,020 1,142 1,262 1,380 Non-Res Cumulative Market Potential 3,694 7,647 12,144 17,454 23,551 29,056 34,556 39,974 45,270 50,429 C&S(If Claimed) 1,542 1,526 1,461 1,351 1,282 1,200 1,149 1,103,378 1,059,820 1,018,093 NAVIGANT Gridley Ten Year Incremental Goals-Net(2018-2027) Net Incremental Mar b31 Potential by Sector w MI Sector, nrvgy Potential(MWh)and 96 of Sale o m,a. 120 1Elt o'�,- -inci 1ITurii _ s n xw.. o ts. 40 o.n;b r�rie,10..1440401,Market PUte,tle ii t-r' „`J 1 X 11 .1111110N00-Pe.10,,,otel,I.,Merkel PVtenti., y••i..t..1In.r0,,r.r.i 40,r,,,.,..820 t t..r.'.S.1... 10 Year Energy Goals(Net MWS) • ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 108 107 96 108 124 124 113 104 96 84 Res Incremental Market Potential 53 47 28 29 32 34 33 34 30 26 Non-Res Incremental Market Potential 55 61 69 79 92 90 80 70 65 59 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.30% 0.30% 0.27% 0.30% 0.33% 0.33% 0.31% 0.28% 0.26% 0.23% Res Incremental Potential as a%of Res Sales 0.34% 0.30% 0.18% 0.19% 0.20% 0.21% 0.21% 0.21% 0.19% 0.16% Non-Res Incremental Potential as a%of Non-Res Sales 0.27% 0.30% 0.33% 0.37% 0.44% 0.43% 0.38% 0.33% 0.31% 0.28% 10 Year Demand Goals(kW) ALL Sectors(NW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 25 26 27 30 33 32 31 29 28 27 Res Incremental Market Potential 11 10 9 10 10 11 11 11 11 10 Non-Res Incremental Market Potential 14 16 18 20 23 22 20 18 17 17 C&5(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Gridley Ten Year Cumulative Goals-Net(2018-2027) Net I:rannrlal M>M.alast Potential by Sortie r txr All Sector,F new Potential(MIAOW and%of Salt", nrn.. 1000 am t r.,,,7: • aoo 0.'20, 0 0.00, turn 1U6r IOSu ton 1011 roti 1Wa tato 1014 tul� =NM K.,curnu0av e M..rk.t Pot.nt,ai Non Nit r i.mwt.g.Markt 1,0,,,a. roc&s Ot,1280.J-estilrralsr 00E.82.8.128.•100 2014) .a. rut.1 C20821.08v PO0,ti.l 45 a%W 1u1.1 8a., 30 year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 108 215 312 420 544 667 780 884 979 1,061 Res Cumulative Market Potential 53 100 128 157 189 223 256 290 320 345 Non Res Cumulative Market Potential 55 115 184 263 355 444 524 .594 659 716 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.30% 0.60% 0.87% 1.17% 1.47% 1.80% 2.11% 2.39% 2.65% 2.86% Res Cumulative Potential as a%of Res Sales 0.34% 0.64% 0.82% 1.01% 1.18% 1.39% 1.60% 1.81% 2.00% 2.16% Non Res Cumulative Potential as a%of Non-Res Sales 0.27% 0.56% 0.90% 1.25% 1.68% 2.11% 2.49% 2.82% 3.13% 3.40% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 25 51 78 109 142 ,-,175 205 234 261 288 Res Cumulative Market Potential 11 22 31 41 51 62 72 83 93 103 Non-Res Cumulative Market Potential 14 29 47 68 91 113 133 151 168 185 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Healdsburg Ten Year Incremental Goals-Net(2018-2027) Nel Inert nionirrl Markel Polentu,l by Secim vm All Sectors I-porgy thalenl i:d(NAVA')and 96 of%.,k. e.0_< moom. 400 TT 200 O A04 ? u.ao 7 .cv, u 0.10% O 0.004 2018 2019 2020 2021 2022 20.21 2021 2025 2020 2027 - 1,,-r tncrnmental Mar.,Pnta.,5a1 Non Ner kr,.....,.-,a-,•40 Markt P,>t.,ti.i1 INEMCGti lit Cia,r044.Estirrrato.nu,avaiia Lie all•r:0,4) -Tutal P,0.414-14a1 Pulvrtral aka_.of total salt, 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 490 486 469 466 438 393 358 331 296 257 Res Incremental Market Potential 39 48 40 45 51 57 62 64 63 59 Non-Res Incremental Market Potential 451 438 429 421 387 336 296 268 233 198 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.65% 0.65% 0.62% 0.61% 0.57% 0.51% 0.46% 0.42% 0.38% 0.33% Res Incremental Potential as a%of Res Sales 0.08% 0.10% 0.08% 0.10% 0.11% 0.12% 0.13% 0.13% 0.13% 0.12% Non-Res Incremental Potential as a%of Non-Res Sales 1.54% 1.47% 1.44% 1.39% 1.28% 1.10% 0.97% 0.88% 0.76% 0.65% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 98 103 102 101 94 85 79 67 52 38 Res Incremental Market Potential 9 12 13 16 20 25 30 26 19 10 Non-Res Incremental Market Potential 89 91 89 84 74 60 49 41 34 28 C&5(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Healdsburg Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector a�x%e All Sectors 1 energy Potential(MWh)and%of Sales ,,.lee s x, 4.00%1 [...K.) 2 2.(X30 3.CO% 4 ,.. r :.004 a 1.{320 ! 4131 11104 O 0 00^4 • 1001 1010 ,0,0 nut 1112 101 1114 von mer, ro,e tIMI Re%LYr1,0141N,M.olos Putee,tial Nun Rvs 4.atlutalrre Markel PWentul 1(:8,S(11 I-LPnMa.I:Ornate:net Avail-10W atter 2014) -10-torsi Cumulative Potential a:a%or Total Salo: SOYear Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 490 976 1,445 1,894 2,312 2,675 2,999 3,294 3,553 3,785 Res Cumulative Market Potential 39 87 126 154 186 221 259 295 329 375 Non-Res Cumulative Market Potential 451 890 1,319 1,740 2,126 2,454 2,740 2,999 3,225 3,410 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.65% 1.30% 1.90% 2.49% 3.00% 3.47% 3.84% 4.22% 4.56% 4.80% Res Cumulative Potential as a%of Res Sales 0.08% 0.19% 0.27% 0.33% 0.39% 0.46% 0.54% 0.61% 0.68% 0.78% Non-Res Cumulative Potential as a%of Non-Res Sales 1.54% 2.99% 4.43% 5.76% 7.04% 8.03% 8.96% 9.81% 10.54% 11.15% 10 Year Demand Goals(Cumulative kW) All Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 98 201 303 403 497 579 655 718 768 805 Res Cumulative Market Potential 9 21 34 50 70 94 122 146 163 174 Non-Res Cumulative Market Potential 89 180 268 353 427 485 533 573 605 631 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT IID Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector 41,0.1All Sectors P nergy Potential(MWh)and%of Sake. 4,000n.wt 0 70.0 X -..vua !,,rv., :f. 15.0:74.1 0.40% ',: u.Orb <451JIr21JIi1II$ IiJiirJ rotialSNI. -nrl i,w,e, ,11 Merkel Putset.r.4.41v.Ir•,Joan) -y-rvt.rl1.•.,„,alba Wleri4.1 w..lw tura•lialek 10 Year EnergyGoals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 33,475 33,760 33,952 32,232 30,894 28,668 27,685 26,708 25,027 22,435 Res Incremental Market Potential 8,174 7,999 8,493 8,910 9,013 8,923 8,646 8,312 7,818 6,766 Non-Res Incremental Market Potential 7,500 8,076 8,716 9,141 9,212 8,994 8,786 8,618 7,885 6,777 C&S(If Claimed.Estimates not available after 2024) 17,801 17,685 16,743 14,181 12,669 10,751 10,252 9,777 9,324 8,892 Total Incremental Potential as a%of Total Sales 0.9S% 0.95% 0.94% 0.88% 0.82% 0.75% 0.71% 0.68% 0.63% 0.55% Res Incremental Potential as a%of Res Sales 0.52% 0.50% 0.52% 0.54% 0.53% 0.52% 0.50% 0.47% 0.43% 0.37% Non-Res Incremental Potential as a%of Non-Res Sales 0.38% 0.40% 0.43% 0.44% 0.44% 0.42% 0.40% 0.39% 0.35% 0.30% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 15,878 15,778 16,105 16,242 16,422 15,033 15,063 15,040 14,856 14,471 Res Incremental Market Potential 3,550 3,086 3,290 3,477 3,537 3,515 3,357 3,151 3,006 2,788 Non Res Incremental Market Potential 7,630 7,941 8,202 8,479 8,823 7,704 7,999 8,286 8,347 8,278 C&S(If Claimed.Estimates not available after 2024) 4,698 4,751 4,612 4,286 4,062 3,814 .3,707 3,603 .3,503 3,405 IID Ten Year Cumulative Goals-Net(2018-2027) li Net Curti lative Market troter dial by Sector A00,000 All Sectors C nergy Potential(MWh)and%of Sales rn"a i- .)e.xl Jw J a 100,00 •.a.nw , 1 wa:. 0 0.00% 2019 2019 2020 2021 2022 2023 2024 2025 2026 2027 t•RP% rrm,2,r..•Market Potentnl r111111•Nnn Ile:rrrm,a.4r•ve Market r'trtrnmW MIMIC&s Ill C.leilxerd.Es ti,rwtwa,,,4.va.141w.ltei 20:4) ...N.-ivt.I Cu4fwr4trve hta-r,tia1.a.%yr tet.,$41e, 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 33,475 67,236 101,187 132,879 163,119 187,339 210,277 232,333 252,506 269,391 Res Cumulative Market Potential 8,174 16,173 24,665 33,035 41,437 46,509 51,077 55,435 59,152 61,302 Non-Res Cumulative Market Potential 7,500 15,577 24,292 33,433 42,602 51,000 59,117 67,037 74,169 80,012 C&S(If Claimed.Estimates not available after 2024) 17,801 35,486 52,229 66,411 79,080 89,830 100,083 109,860 119,185 128,077 Total Cumulative Potential as a%of Total Sales 0.95% 1.88% 2.79% 3.61% 4.35% 4.91% 5.42% 5.90% 6.32% 6.62% Res Cumulative Potential as a%of Res Sales 0.52% 1.01% 1.51% 2.00% 2.46% 2.71% 2.93% 3.13% 3.29% 3.36% Non-Res Cumulative Potential as a%of Non-Res Sales 0.38% 0.78% 1.19% 1.61% 2.02% 2.38% 2.71% 3.03% 3.30% 3.51% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 .2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 15,878 26,959 38,316 50,042 62,257 65,498 68,709 71,819 74,534 76,538 Res Cumulative Market Potential 3,550 6,635 9,923 13,486 17,108 18,389 19,534 20,635 21,576 22,153 Non-Res Cumulative Market Potential 7,630 15,573 23,781 32,270 41,087 43,296 45,468 47,581 49,455 50,981 C&S(If Claimed.Estimates not avai lable after 2024) 4,698 4,751 4,612 4,286 4,062 3,814 3,707 3,603 3,503 3,405 .............. NAVIGANT Lassen MUD Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector 400 umn........ffilAllSectors Energy Potential(M Wh)a nd%of Sales 0.30% 0.25% „ 300 0.20%t 200 °.15% 1 n 0.10% a IOD `o 0.05% * 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential Non-Res Incremental Market Potential IIIIMC&5(If Claimed) +Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 353 371 318 339 356 359 352 350 332 320 Res Incremental Market Potential 256 267 '205 214 221 228 222 221 206 201 Non Res Incremental Market Potential 97 104 114 125 134 131 130 129 126 120 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.27% 028% 0.24% 0.25% 0.26% 0.26% 0.26% 0.25% 0.24% 0.23% Res Incremental Potential as a%of Res Sales 1.84% 1.92% 1.46% 1.51% 1.55% 1.59% 1.55% 1.53% 1.43% 1.39% Non Res Incremental Potential as a%of Non Res Sales 0.08% 0.09% 0.10% 0.10% 0.11% 0.11% 0.11% 0.11% 0.10% 0.10% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 79 86 87 96 104 104 103 102 98 92 Res Incremental Market Potential 35 39 35 39 41 44 44 44 42 41 Non-Res Incremental Market Potential 44 47 52 58 63 60 59 58 56 51 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Lassen MUD Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector 3,500 All Sectors Energy Potential(MWh)and%of Sales 2.50% 3,000 2,500 2.00% v 3 2,000 - 1.50% i 2 1,500 1.00% '= 1,000 `o 500 0.50% ;e 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Cumulative Market Potential Non-Res Cumulative Market Potential MIIC&S(If Claimed) t Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 353 724 1,043 1,381 1,737 2,030 2,294 2,550 2,785 3,001 Res Cumulative Market Potential 256 523 728 942 1,163 1,374 1,553 1,726 1,881 2,029 Non-Res Cumulative Market Potential 97 201 315 439 573 656 741 824 903 971 C845(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.27% 0.54% 0.78% 1.02% 1.28% 1.48% 1.67% 1.85% 2.02% 2.17% Res Cumulative Potential as a%of Res Sales 1.84% 3.75% 5.18% 6.66% 8.16% 9.57% 10.81% 11.93% 13.01% 14.03% Non-Res Cumulative Potential as a%of Non-Res Sales 0.08% 0.17% 0.26% 0.37% 0.47% 0.54% 0.61% 0.67% 0.74% 0.79% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 79 165 252 348 453 532 608 681 749 808 Res Cumulative Market Potential 35 74 109 148 189 232 272 311 346 379 Non-Res Cumulative Market Potential 44 91 143 200 263 300 336 371 403 429 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 NAVIGANT LADWP Ten Year Incremental Goals -Gross(FY17-18 tp FY26/27) Incremental Gross Market Potential by Sector 500000 All Sectors Energy Potential(MWh)and%of Sales 0.02 400000 0.I!! 300000 0.2000000. W0000 a` 0 0 1317-18 F118-19 FY19-20 1320-21 F021-22 FY22-23 1923-24 1924-25 F125-26 FY26-27 Res Incremental Market Potentia I I=Non-Res Incremental Market Potential IC&S(If Claimed.Estimates not avails ble after 2024) 4 Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) Alt Sectors(MWh) FY17-18 FY18-19 F919-20 FY20-21 F921-22 F922-23 FY23-24 FY24-25 F925.26 FY26-27 Total Incremental Market Potential 377,701 382,463 377,413 351,678 331,494 307,521 293,832 297,211 287,665 277,376 Res Incremental Market Potential 107,463 111,287 115,098 120,022 124,472 128,198 131,141 135,093 139,236 142,807 Non-Res Incremental Market Potential 112,823 116,466 116,058 107,696 96,009 83,369 72,112 62,932 53,821 44,297 C&S If Claimed 157,414 154,711 146,256 123,960 111,013 95,953 90,579 99,187 94,607 90,272 Total Incremental Potential as a%of Total Sales 1.51% 1.51% 1.47% 1.35% 1.26% 1.15% 1.09% 1.09% 1.04% 0.99% Res Incremental Potential as a%of Res Sales 1.25% 1.27% 1.29% 1.31% 1.33% 1.35% 1.35% 1.36% 1.38% 1.38% Non-Res Incremental Potential as a%of Non-Res Sales 0.68% 0.70% 0.69% 0.63% 0.56% 0.48% 0.42% 0.36% 0.31% 0.25% 10 Year Demand Goals(kW) ALl Sectors(kW) FY17-18 FY18-19 P119-20 F920-21 FY21-22 FY22-23 F923-24 FY24-25 1325.26 FY26-27 Total Incremental Market Potential 148,879 156,439 164,531 171,031 177,851 159,664 163,496 167,205 169,652 170,677 Res Incremental Market Potential 8,163 8,842 9,968 11,399 12,693 13,754 14,453 15,078 15,727 16,277 Non-Res Incremental Market Potential 98,985 105,729 113,536 121,391 128,799 111,666 115,872 119,670 122,362 123,700 C&S If Claimed 41,730 41,869 41,027 38,241 36,359 34,243 33,171 32,457 31,563 30,700 LADWP Ten Year Cumulative Goals-Gross(FY17-18 tp FY26/27) Cumulative Market Potential by Sector _ 3000000 AllSectorsEnergy Potentia)(MWh)and%of Sales 01 2500000 008 y 2000000 310.06 3 500000 - 0.04 1000000 a 500000 I o.oz ae 0 0 FY17-18 1918-19 1919-20 1920-21 FY21-22 1922-23 F923-24 1924-25 F925-26 1926-27 yes Cumulative Market Potential MN Non-Res Cumulative Market Potential C&5(If Claimed.Estimates not available after 2024) -Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross MWh) ALL Sectors(Cumulative MWS) FY17-18 FY18-19 FY19-20 9320-21 FY21-22 F122-23 FY23-24 FY24-25 FY25-26 F926-27 Total Cumulative Market Potential 377,701 691,753 999,209 1,276,323 1,527,776 1,738,632 1,924,804 2,111,810 2,287,862 2,449,800 Res Cumulative Market Potential 107,463 150,339 195,650 244,261 295,741 348,875 395,477 443,297 492,489 542,311 Non Res Cumulative Market Potential 112,823 229,289 345,178 449,721 538,680 600,449 649,440 689;440 721,692 743,536 C&S If Claimed 157,414 312,125 458,381 582,342 693,355 789,308 879,887 979,074 1,073,681 1,163,953 Total Cumulative Potential as a%of Total Sales 1.51% 2.74% 3.90% 4.92% 5.81% 6.53% 7.14% 7.74% 8.29% 8.77% Res Cumulative Potential as a%of Res Sales 1.25% 1.72% 2.18% 2.67% 3.17% 3.66% 4.07% 4.47% 4.87% 5.25% Non-Res Cumulative Potential as a%of Non-Res Sales 0.68% 1.38% 2.05% 2.65% 3.15% 3.49% 3.74% 3.95% 4.10% 4.19% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) F117.18 F118-19 FY19-20 FY20-21 FY21-22 FY22-23 FY23-24 F924-25 FY25-26 F926-27 Total Cumulative Market Potential 148,879 263,587 386,226 515,519 653,612 643,999 629,020 607,617 575,460 528,273 Res Cumulative Market Potential 8,163 17,005 26,973 38,372 51,064 64,698 77,325 90,333 103,754 117,502 Non Res Cumulative Market Potential 98,985 204,714 318,227 438,906 566,188 545,058 518,525 484,827 440,142 380,071 C&S If Claimed 41,730 41,869 41,027 38,241 36,359 34,243 33,171 32,457 31,563 30,700 NAVIGANT Lodi Ten Year Incremental Goals-Net(2018-2027) Net Increrriental Markel Potential by Sector I.luxAll Sortnrs Fnorgy Potential(MWh)and'X,of Soles t y14, t.a<x? 1.4,24, — 1,(rra i 4015 O 15^ TW 0.0,, tl ,ulrr buil 4iVOrjii liii tt,.re,+rn rev rvtnl Mn.E•t l.�n,tiu 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,227 1,313 1,399 1,496 1,575 1,604 1,612 1,618 1,587 1,534 Res Incremental Market Potential 361 380 387 408 427 443 453 458 458 454 Non-Res Incremental Market Potential 866 933 1,011 1,089 1,147 1,161 1,160 1,160 1,130 1,079 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.28% 0.30% 0.32% 0.34% 0.36% 0.36% 0.36% 0.36% 0.35% 0.34% Res Incremental Potential as a%of Res Sales 0.24% 0.25% 0.26% 0.27% 0.28% 0.29% 0.29% 0.30% 0.29% 0.29% Non Res Incremental Potential as a%of Non-Res Sales 0.31% 0.33% 0.35% 0.38% 0.40% 0.40% 0.40% 0.40% 0.38% 0.36% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 372 394 418 440 457 465 472 480 470 452 Res Incremental Market Potential 171 183 194 205 213 218 221 220 218 214 Non-Res Incremental Market Potential 201 212 224 235 244 246 252 259 252 238 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Lodi Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector 16.o0o All Sectors n 1- ergy Potential(MWh)and 76 of Sakes 3.501, 141(1441 a.05% 12.000 10.000 s /33.1.1 ..: t R c;. .n,. •1.000 1.1are „T' 1 ; " utr C.. Tule Tniti TOTO TU.i 10:2 :cue :'074 0 :ON. 1027 R...Cuu,ctlatvv 1,Irtet eutenlnal IIMIMM Nun Res(:ul:l(.L.t:vv Mar See Pune ul MOO CRS III CSs n ett.E:lutwit,nut.1Vallaill„an,TOTa) —4S—Iu1.11 Cunas1.4net!MA4,11.41 a:a%of/0,0 Salo, 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1,227 2,540 3,939 5,411 6,958 8,529 10,085 11,640 13,159 14,609 Res Cumulative Market Potential 361 741 1,129 1,512 1,912 2,322 2,734 3,147 3,556 3,954 Non-Res Cumulative Market Potential 866 1,799 2,810 3,899 5,046 6,207 7,351 8,493 9,603 10,656 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a Y f Total Sales 0.28% 0.58% 0.90% 1.23% 1.58% 1.92% 2.26% 2.60% 2.92% 3.23% Res Cumulative Potential as a%of Res Sales 0.24% 0.49% 0.75% 1.00% 1.26% 1.52% 1.78% 2.04% 2.29% 2.53% Non-Res Curnulative Potential as a%of Non-Res Sales 0.31% 0.63% 0.98% 1.36% 1.75% 2.14% 2.52% 2.89% 3.26% 3.60% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 372 766 1,185 1,624 2,081 2,544 3,008 3,478 3,937 4,378 Res Cumulative Market Potential 171 354 548 752 964 1,182 1,393 1,604 1,812 2,016 Non-Res Cumulative Market Potential 201 413 637 872 1,116 1,363 1,614 1,874 2,125 2,362 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Lompoc Ten Year Incremental Goals -Gross(2018-2027) Incremental Gross Market Potential by Sector 350 All Sectors Energy Potential(MWh)and9'n of Sales 0.25% 300 0.20% w 250 72 t 200 0.15% g - 2 150 0.10% a 100 15 0.05% a° 50 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 I•Res Incremental Market Potential NM Non-Res Incremental Market Potential C&S(If Claimed) tTotal Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL Sectors(MW6) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 213 236 249 266 282 300 313 324 326 320 Res Incremental Market Potential 109 115 114 118 122 125 128 131 133 129 Non-Res Incremental Market Potential 104 120 134 148 160 175 185 193 193 191 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.16% 0.17% 0.18% 0.19% 0.20% 0.21% 0.22% 0.23% 0.23% 0.22% Res Incremental Potential as a%of Res Sales 0.20% 0.21% 0.21% 0.21% 0.22% 0.22% 0.23% 0.23% 0.23% 0.23% Non-Res Incremental Potential as a%of Non-Res Sales 0.13% 0.14% 0.16% 0.17% 0.19% 0.21% 0.22% 0.22% 0.22% 0.22% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 34 37 39 42 45 48 50 53 53 52 Res Incremental Market Potential 11 12 12 13 13 14 14 14 14 14 Non-Res Incremental Market Potential 23 24 26 29 31 34 36 38 38 38 C&5(If Claimed) 0 0 0 0 0 0 0 0 0 0 Lompoc Ten Year Cumulative Goals-Gross(2018-2027) Cumulative Market Potential by Sector 2,500 All Sectors Energy Potential(MWh)a nd%of Sales 2.00% 2,000 1.50% m 1.500 3 V' 1.00% 7,- 2 2 1,000 0.50%.i.........ir,,,esotlrrt""tlo 500 e 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 I Res Cumulative Market Potential Non-Res Cumulative Market Potential C&S(If Claimed) Notal Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 213 449 697 963 1,246. 1,422 1,626 1,835 2,042 2,240 Res Cumulative Market Potential 109 225 339 457 579 580 601 622 641 654 Non-Res Cumulative Market Potential 104 224 358 506 666 841 1,024 1,214 1,401 1,586 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.16% 0.33% 0.51% 0.70% 0.90% 1.02% 1.16% 1.30% 1.45% 1.57% Res Cumulative Potential as a%of Res Sales 0.20% 0.41% 0.61% 0.82% 1.03% 1.03% 1.06% 1.09% 1.12% 1.15% Non-Res Cumulative Potential as a%of Non-Res Sales 0.13% 0.27% 0.43% 0.60% 0.78% 0.99% 1.19% 1.41% 1.63% 1.84% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 34 70 109 151 195 243 301 361 420 479 Res Cumulative Market Potential 11 23 36 49 62 76 98 120 141 163 .._._._. _._.___ .....__ ._.....- Non-Res Cumulative Market Potential 23 47 73 102 133 167 203 241 279 316 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Merced Ten Year Incremental Goals-Net(2018-2027) Net Incremental Markel entential by Sector Alt Sector-.F nerey Prater-Mal(MWh)and%no Sales ifi _...._ 1600 ... :NJ 111 I Rill .;_, 0 25.e 0- ,..g A 3 0 ....-,, , Jo J00, J0J l INI RV,1,4,,,,e0,1 M4004.1,0,1,0 IMIllNuo-ge,I ok.oe0,0,t,10J1ket Pute0tio, 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,258 1,346 1,452 1,551 1,597 1,586 1,525 1,455 1,392 1,350 Res Incremental Market Potential 14 15 16 19 23 24 25 26 26 26 Non-Res Incremental Market Potential 1,244 1,330 1,436 1,532 1,574 1,562 1,500 1,429 1,366 1,324 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.27% 0.28% 0.30% 0.32% 0.33% 0.32% 0.31% 0.29% 0.28% 0.27% Res Incremental Potential as a%of Res Sales 0.02% 0.03% 0.03% 0.03% 0.04% 0.04% 0.04% 0.04% 0.04% 0.04% Non-Res Incremental Potential as a%of Non-Res Sales 0.30% 0.32% 0.34% 0.36% 0.37% 0.36% 0.34% 0.32% 0.31% 0.29% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 219 236 255 273 281 279 265 248 234 229 Res Incremental Market Potential 1 1 1 1 1 1 1 1 1 1 Non-Res Incremental Market Potential 219 235 254 272 281 278 264 248 233 228 C&S(If Claimed.Esti rnates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Merced Ten Year Cumulative Goals-Net(2018-2027) Nut tanntalabve Mar ken l Potertleal by Stein;; All Sectors E runny Potential(IVIIN/t)and X 01 Saki, , ifi.Oilc, i;re, 14.000 IIJI 2.54% 1 12.0M) uy, ,71 .10.400 -., 0: .2 000 /01,, J004 /WO JO/1 JOJJ J0J-1 It,. ./(4.• .1014 J11.1 I inn/if,f 01,41,aVve.,,,rnt Potent.. inls100 Ile,[i ar,u1.0..Marla et 1,00..%i4. MIN C.2.15(II(14000.)e0,04.0-...00l.1,0WD le.0,1:014) tul-al,Utra.041.••••P0.0tIJI J,a ba 01 101.r 521.1, 10 Year Energy Goals(Cumulative Net MWh) ALL sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1,258 2,603 4,055 5,607 7,203 8,789 10,313 11,766 13,151 14,481 Res Cumulative Market Potential 14 29 45 65 87 112 137 163 189 215 Non-Res Cumulative Market Potential 1,244 2,575 4,010 5,542 7,116 8,678 10,176 11,603 12,962 14,265 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.27% 0.55% 0.85% 1.16% 1.48% 1.79% 2.09% 2.36% 2.62% 2.85% Res Cumulative Potential as a%of Res Sales 0.02% 0.05% 0.08% 0.11% 0.14% 0.18% 0.22% 0.26% 0.30% 0.34% Non-Res Cumulative Potential as a Soften-ten Sales 0.30% 0.61% 0.95% 1.30% 1.65% 2.00% 2.33% 2.63% 2.91% 3.18% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 219 455 710 983 1,264 1,543 1,808 2,056 2,289 2,512 Res Cumulative Market Potential 1 1 2 3 4 4 5 6 7 8 Non-Res Cumulative Market Potential 219 454 708 980 1,261 1,538 1,803 2,050 2,281 2,504 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Modesto Ten Year Incremental Goals-Net(2018-2027) Net tract erne,dal Mar 6,1 Potential by Sc iw <xx) All Sectors[clergy Potential(MWh)and%of Sales n.rm 14.001 , .r.. 1!.000 0 40% 7 1X1 0.0 ,11 t,01.0 0.1U4e 4 000 a, 0atl, 2111,. loll JIUI l,UI / il lot"t Al.. till. .104, /Ill/ MEN, .,n/re.mrnl,l M.4•.,4 Pottnnttl, am Non¢n Icm-,c,rnr,rl.,t 101.,r1t,1v,.rn,.1 IIIMMI Cns In c uu,..a tvu,ul.,not.v..,..k..all,111'4) freta n,u.,n.v,:.l!blob.!a,..a 01100i Soh, 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 9,144 10,060 11,062 12,052 12,879 13,385 13,700 13,714 13,149 11,883 Res Incremental Market Potential 464 489 495 526 559 585 603 615 622 624 Non-Res Incremental Market Potential 8,680 9,570 10,567 11,526 12,320 12,800 13,096 13,098 12,527 11,259 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.34% 0.37% 0.41% 0.44% 0.46% 0.47% 0.48% 0.48% 0.45% 0.41% Res Incremental Potential as a%of Res Sales 0.05% 0.05% 0.05% 0.05% 0.06% 0.06% 0.06% 0.06% 0.06% 0.06% Non-Res Incremental Potential as a%of Non-Res Sales 0.49% 0.54% 0.59% 0.63% 0.67% 0.69% 0.70% 0.69% 0.65% 0.58% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 2,181 2,374 2,640 2,972 3,287 3,242 3,344 3,371 3,313 3,155 Res Incremental Market Potential 173 176 176 179 182 184 186 188 190 192 Non-Res Incremental Market Potential 2,008 2,197 2,464 2,793 3,105 3,058 3,158 3,182 3,122 2,963 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Modesto Ten Year Cumulative Goals-Net(2018-2027) Net C bel iw Mar kel Peden dial by tiecm et I-011.ix All Sectors Energy Potential(MWh)and%of Sales 1 4 1.n.. 20.000 100.000 l. s but.. /,rn.. 90.010 I ♦,. 1 20,01/0 " /01,1 Anti !41,41 )02.I /11, /t)ll eq.,4 11/`. !WI, till/ MEN lira,.,miaalw.MarY.r 1 rv.m,41 fliNnn-0,..,t uml,la,..MarY.r 1,,r.nt,a. 61.1.1,4,114t l.,r,.,a Fs1i„u1vs 002,r2101.4.21t.120:4) .111..l.l121Cu,ral,al,v.,6u1..00212s a%of10141Sal, 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 9,144 19,204 30,266 42,318 55,197 68,543 82,034 95,522 108,444 120,029 Res Cumulative Market Potential 464 954 1,448 1,975 2,534 3,111 3,612 4,117 4,626 5,136 Non Res Cumulative Market Potential 8,680 18,250 28,817 40,343 52,663 65,432 78,423 91,405 103,818 114,893 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.34% 0.71% 1.11% 1.53% 1.98% 2.43% 2.88% 3.32% 3.73% 4.09% Res Cumulative Potential as a%of Res Sales 0.05% 0.10% 0.15% 0.21% 0.26% 0.32% 0.36% 0.41% 0.46% 0.50% Non-Res Cumulative Potential as a%of Non-Res Sales 0.49% 1.02% 1.60% 2.22% 2.86% 3.52% 4.17% 4.82% 5.42% 5.94% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 2,181 4,555 7,194 10,167 13,454 16,691 .20,012 23,358 26,645 29,764 Res Cumulative Market Potential 173 350 526 704 886 1,068 1,234 1,401 1,569 1,739 Non Res Cumulative Market Potential 2,008 4,205 6,669 9,462 12,568 15,623 18,778 21,957 25,075 28,025 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Moreno Valley Ten Year Incremental Goals-Net(2018-2027) Not Incrrvrr•n1.rl Marlin Prllrnti,al isy Sorlew u 1 All Sectors Energy Potential(MWh)and%of Sales 1 1 1.soo 0 90•. 1 400 O.fq'� 1.200 8. ICI. . .1,00 2. 201n. 201n. 20/0 -p:•1 .U. :023 JU 1 Ul, trb 2011 MONNgo-c in.ree,eel."rekwk r 1.........01 Ma c:X5 In 1.Wit.,1.0ignat.-,.,,uv.,1414-.1c1-,2024( ...0-1,4111.0.0.1.1a11,11.111,11 s.a,.4 1 ut..,lea 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,734 1,748 1,752 1,630 1,427 1,227 1,106 1,007 909 833 Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Incremental Market Potential 752 753 761 761 617 501 417 354 290 245 C&S(If Claimed.Estimates not available after 2024) 982 994 991 869 809 726 689 653 620 588 Total Incremental Potential as a%of Total Sales 0.87% 0.87% 0.86% 0.79% 0.69% 0.59% 0.52% 0.47% 0.42% 0.38% Res Incremental Potential as a%of Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Non-Res Incremental Potential as a%of Non-Res Sales 0.46% 0.46% 0.46% 0.45% 0.36% 0.29% 0.24% 0.20% 0.16% 0.14% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 413 419 416 400 359 321 296 275 255 239 Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Incremental Market Potential 164 163 164 164 132 104 85 72 58 48 C&S(If Claimed.Estimates not available after 2024) 249 256 252 236 228 218 210 204 197 191 Moreno Valley Ten Year Cumulative Goals-Net(2018-2027) Net Curnuloliva Market Potential by Sector 14<x10 All Sectors I nergy Potential(MWh)and%of Sales l po-a 1,0110 e.000 F c.x, 1, 4u; 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 , MIN Ilea i.,miavr.r 1,10.1 Preen,en Nen net rllm,r14r.v.Mnrker Pnr-n1141 MINIM C&S Ill c.lai,.N EO,nwt..,,u1.e e1.l+k..10-,20241 Huta,Cull,ui..11..•',rut',.1,4%J lutat 5.k-a 10Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1,734 3,482 5,233 6,864 8,287 9,494 10,583 11,576 12,470 13,278 Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Cumulative Market Potential 752 1,505 2,266 3,028 3,641 4,123 4,523 4,863 5,138 5,357 C&S(If Claimed.Estimates not available after 2024) 982 1,976 2,967 3,836 4,645 5,371 6,060 6,713 7,333 7,920 Total Cumulative Potential as a%of Total Sales 0.87% 1.73% 2.57% 3.34% 3.99% 4.53% 5.00% 5.41% 5.77% 6.09% Res Cumulative Potential as a%of Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Non-Res Cumulative Potential as a%of Non-Res Sales 0.46% 0.92% 1.37% 1.81% 2.15% 2.41% 2.62% 2.79% 2.92% 3.01% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 413 583 744 892 1,015 1,104 1,178 1,240 1,287 1,323 Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Cumulative Mrket Potential 164 328 492 656 787 886 968 1,036 1,090 1,132 C&S(If Claimed.Estimates not available after 2024) 249 256 252 236 228 218 210 204 197 191 NAVIGANT Needles Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential bySector 35 All Sectors Energy Potential(MWh)and%of Sales 0.06% 30 0.05% 25 0.04% _ r 20 0.03% `3 els 0.02% 10 5 0.01 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential INon-Res Incremental Market Potential tTotal Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 19 20 22 25 27 29 27 21 15 10 Res Incremental Market Potential 19 20 22 25 27 29 27 21 15 9 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.04% 0.04% 0.04% 0.05% 0.05% 0.05% 0.05% 0.04% 0.03% 0.02% Res Incremental Potential as a%of Res Sales 0.30% 0.31% 0.33% 0.37% 0.40% 0.43% 0.39% 0.30% 0.21% 0.14% Non-Res Incremental Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 19 20 21 24 26 27 24 18 13 7 Res Incremental Market Potential 17 17 18 21 23 25 22 16 11 5 Non-Res Incremental Market Potential 2 2 3 3 3 2 2 2 2 2 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Needles Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector 200 All Sectors Energy Potential(MWh)and%of Sales 0.40% 150 0.30% m 3 100 0.20% , a 50 0.10% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 I Res Cumulative Market Potential I•Non-Res Cumulative Market Potential IAC&S(If Claimed.Estimates not available after 2024) Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 19 40 62 87 114 137 157 171 179 180 Res Cumulative Market Potential 19 39 61 86 113 135 155 169 176 177 Non-Res Cumulative Market Potential 0 1 1 1 2 2 2 3 3 3 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.04% 0.07% 0.11% 0.16% 0.20% 0.25% 0.28% 0.30% 0.31% 0.32% Res Cumulative Potential as a%of Res Sales 0.30% 0.61% 0.93% 1.30% 1.68% 2.02% 2.27% 2.47% 2.58% ' 2.60% Non-Res Cumulative Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.01% 0.01% 0.01% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 19 39 60 83 109 130 147 159 165 165 Res Cumulative Market Potential 17 34 52 73 96 115 130 140 144 142 Non-Res Cumulative Market Potential 2 5 7 10 13 15 17 19 21 23 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Palo Alto Ten Year Incremental Goals -Net(2018-2027) Incremental Market Potential bySector 10,000 ri....uAll Sectors Energy Potential(MWh)and 90 of Sales 1.00% 8,000 - 0.80% T, Tji 6,000 0.60% 3 3 2 4,000 oQ 2,000 0.20% 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential MIN Non-Res Incremental Market Potential MEM(If Claimed.Estimates not availa ble after 2024) t Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 7,280 7,284 7,760 7,757 8,253 8,146 8,631 8,647 9,139 9,152 Res Incremental Market Potential 1,879 1,802 1,804 1,768 1,924 1,997 2,209 2,245 2,433 2,570 Non-Res Incremental Market Potential 5,401 5,482 5,956 5,989 6,330 6,149 6,421 • 6,402 6,706 6,581 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.75% 0.75% 0.80% 0.80% 0.85% 0.85% 0.90% 0.90% 0.95% 0.95% Res Incremental Potential as a%of Res Sales 0.19% 0.19% 0.19% 0.18% 0.20% 0.21% 0.23% 0.23% 0.25% 0.27% Non-Res Incremental Potential as a%of Non-Res Sales 0.56% 0.56% 0.61% 0.62% 0.65% 0.64% 0.67% 0.67% 0.70% 0.68% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,697 1,698 1,783 1,785 1,925 1,865 1,865 1,684 1,587 1,580 Res Incremental Market Potential 113 109 99 103 125 126 147 149 162 170 Non-Res Incremental Market Potential 1,584 1,589 1,684 1,682 1,800 1,740 1,718 1,535 1,426 1,410 C8.5(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Palo Alto Ten Year Cumulative Goals -Net(2018-2027) Cumulative Market Potential by Sector 100,000 All Sectors Energy Potential(MWh)and%of Sales 10.00% 80,000 8.00% 60,000 6.00% ir....i........nrii.isamill L' 2 40,000 4.00% a` `o 20,000 2.00% ae 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 IMIRes Cumulative Market Potential I•Non-Res Cumulative Market Potential INIIIIC&S(If Claimed.Estimates not available after 2024) Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross(VIWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 7,280 14,564 22,324 30,081 38,335 46,480 55,111 63,758 72,898 82,049 Res Cumulative Market Potential 1,879 3,681 5,485 7,254 9,177 11,174 13,383 15,628 18,061 20,631 Non-Res Cumulative Market Potential 5,401 10,883 16,839 22,828 29,157 35,307 41,728 48,130 54,837 61,418 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.73% 1.46% 2.24% 3.02% 3.84% 4.71% 5.59% 6.47% 7.42% 8.35% Res Cumulative Potential as a%of Res Sales 0.92% 1.81% 2.69% 3.56% 4.50% 5.54% 6.65% 7.77% 9.00% 10.30% Non-Res Cumulative Potential as a%of Non-Res Sales 0.68% 1.37% 2.12% 2.86% 3.71% 4.49% 5.31% 6.14% 7.01% 7.87% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1,697 1,698 1,783 1,785 1,925 1,865 1,865 1,684 1,587 1,580 Res Cumulative Market Potential 113 109 99 103 125 126 147 149 162 170 Non-Res Cumulative Market Potential 1,584 1,589 1,684 1,682 1,800 1,740 1,718 1,535 1,426 1,410 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Pasadena Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector All Sectors t nergy Potential(MWII)and 96 of Ss*, 111.114..o.o44.4,44u...e................,w........ ................,...a.„..............ei...i 14011, $ I ,V4, l0,6 anni Re,.4,rm441,s,Mai ke.1 f5314.,941 NOJN Pea 1...4,4,t,t,t a.Movkvl P.t<tAta I C4.519 Clsonx.1) —0—rotel in,..4.1‘4414180144,1,,la a"0.1 Tat4,5414.4 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 16,306 15,999 15,476 15,242 15,172 14,684 13,979 13,032 12,203 11,403 Res Incremental Market Potential 6,711 6,652 6,330 6,288 6,306 6,325 6,343 6,361 6,366 6,372 Non-Res Incremental Market Potential 6,661 6,547 6,508 6,660 6,757 6,491 5,873 5,007 4,267 3,550 C&5(If Claimed) 2,933 2,800 2,638 2,293 2,109 1,869 1,763 1,664 1,570 1,481 Total Incremental Potential as a%of Total Sales 1.48% 1.47% 1.44% 1.43% 1.42% 1.38% 1.31% 1.22% 1.14% 1.07% Res Incremental Potential as a%of Res Sales 2.16% 2.17% 2.10% 2.10% 2.11% 2.11% 2.11% 2.12% 2.12% 2.12% Non-Res Incremental Potential as a%of Non-Res Sales 0.85% 0.85% 0.85% 0.87% 0.88% 0.85% 0.76% 0.65% 0.55% 0.46% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 4,177 4,153 4,131 4,127 4,127 4,035 3,898 511,034 489,904 469,698 Res Incremental Market Potential 154 155 137 138 139 140 141 142 142 142 Non-Res Incremental Market Potential ' 3,303 3,302 3,324 3,369 3,400 3,342 3,227 3,074 2,954 2,874 C&S(If Claimed) 720 696 670 620 589 553 530 507,817 486,808 466,682 Pasadena Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector All Sectors t norgy Potential(MWh)and%of Sates con.000 10.00, ' 410.000 '1 00.4 60.000 6 01Y9 ,5 '.:144., ..t•.,.. ''' 40.000 30.000 3.005. `,•-). ,,,,,,, )141, 10,01.R, ,,,,,,, 0 0 00% • 2018 2019 2020 2021 2022 2023 2024 2025 2026 202, UMM1,47,,t)4,41144.54er5el 1,44.4,4$ 411111111,51oo-4es 4 k.),,441,4 444.1,411,444,, 11.11/..,4•5 Ill$_9.41,447 —49.4-1.11,lum9,41.ve,Olet.a.a,a..4 C.17241511 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 0026 2027 Total Cumulative Market Potential 16,306 26,733 36,717 46,540 56,343 65,434 73,693 80,985 87,450 93,031 Res Cumulative Market Potential 6,711 7,792 8,629 9,498 10,440 11,191 11,883 12,579 13,274 13,965 Non-Res Cumulative Market Potential 6,661 13,208 19,716 26,376 33,128 39,601 45,404 50,337 54,537 57,946 C&S(If Claimed) 2,933 5,734 8,372 10,665 12,774 14,643 16,406 18,069 19,639 21,120 Total Cumulative Potential as a%of Total Sales 1.48% 2.45% 3.42% 4.37% 5.29% 6.14% 6.90% 7.58% 8.18% 8.69% Res Cumulative Potential as a%of Res Sales 2.16% 2.54% 2.86% 3.18% 3.49% 3.73% 3.96% 4.19% 4.42% 4.64% Non-Res Cumulative Potential as a%of Non-Res Sales 0.85% 1.71% 2.58% 3.44% 4.32% 5.16% 5.91% 6.55% 7.08% 7.52% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 4,177 5,590 7,000 8,431 9,910 11,309 12,590 521,028 501,0%7 481,848 Res Cumulative Market Potential 154 306 439 571 703 819 921 1,023 1,125 1,227 Non-Res Cumulative Market Potential 3,303 4,587 5,892 7,240 8,618 9,937 11,139 12,187 13,114 13,939 C&S(If Claimed) 720 696 670 620 589 553 530 507,817 486,808 466,682 NAVIGANT Pittsburg Power Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector I err All Sectors Ln rgy Potential(MWh)and%of Salm ,,.,rv.. ti 4 at iw r.is 1 o �.n er uta zvn .on �02> nvv ,n2a n,-, xr�n .nvt rate._ t♦nn,rnwremental Matte,tvettntrli 101199111100 net rne+.nvtta:Marko rb:enfra: IlimisAi,in r Wrnratrl.Fstrerutt,1,01 avar4Uk altar 2t,t) y-totar Irtur ate r r...t311.00 ,1,n a sr ul 10,0 Sak+ 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 119 105 94 86 79 72 68 62 58 55 Res Incremental Market Potential 4 4 4 4 5 5 5 5 5 6 Non-Res Incremental Market Potential 115 101 90 82 74 68 63 57 52 49 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.49% 0.43% 0.37% 0.34% 0.31% 0.28% 0.26% 0.23% 0.21% 0.20% Res Incremental Potential as a%of Res Sales 0.19% 0.21% 0.21% 0.22% 0.23% 0.24% 0.25% 0.25% 0.26% 0.26% Non-Res Incremental Potential as a%of Non-Res Sales 0.50% 0.43% 0.38% 0.34% 0.30% 0.27% 0.25% 0.22% 0.20% 0.19% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 23 19 17 15 14 13 12 11 11 10 Res Incremental Market Potential 1 1 1 1 1 1 1 1 1 1 Non-Res Incremental Market Potential 22 18 16 15 13 12 11 10 9 9 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Pittsburg Power Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector .rx) All Sectors I nergy Potential(MWh)and%of Sales „ 2.50% X. 606 lar i .00II1 tilt••,, :71009. N • • 0 0.00% ' 2018 2019 3020 2021 3022 2023 2023 2025 2026 2027 1.0080 00)013,,Mnrter nntmr.tl WI=Nnn nn,Crrmutl t,,M:lrtnr',renrr.t: M CRS III[.Ian,arta tstirr utt:riot akarralrk after 202,0 -16131 Currrulwt•w P0M00a0a,a%ur tine$]aka 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 119 224 318 404 482 554 621 681 737 786 Res Cumulative Market Potential 4 8 12 16 21 26 31 36 41 47 Non-Res Cumulative Market Potential 115 216 306 388 461 529 590 645 695 739 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.49% 0.91% 1.27% 1.59% 1.87% 2.12% 2.34% 2.53% 2.70% 2.80% Res Cumulative Potential as a%of Res Sales 0.19% 0.40% 0.61% 0.83% 1.05% 1.28% 1.51% 1.75% 1.99% 2.23% Non-Res Cumulative Potential as a%of Non-Res Sales 0.50% 0.92% 1.28% 1.60% 1.88% 2.12% 2.34% 2.52% 2.68% 2.80% 10 Year Demand Goals(Cumulative kw) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 23 42 59 74 89 101 113 125 135 145 Res Cumulative Market Potential 1 2 2 3 4 6 7 8 10 11 Non-Res Cumulative Market Potential 22 41 57 71 84 96 107 116 125 134 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Plumas Sierra Ten Year Incremental Goals-Net(2018-2027) Net Incremental Mat last Potential by Sector All Sectors Energy Potential(MWh)and%of Sales 130 0.12', 100 1.41 120 I / IFFUTIUri r i 104. .. 0T ,1 0 4. 7 MO Q. ', 1, AO 2018 20/3 20211 21,21 JO, All i 10,0 1111, PI,, ISM R.:,13,03,40131 Mark.,0010ntill IMIMP4n4 P4o,10,0434n/31 hd..-orkrz 30140031 1111=1111,111 t.143034.34130214,133 444.1,23 41,r 20241 .11•1101...1314111,1Wfl..11141 PUICI11141.r.a,01102,15414, 10 Year Energy Goals(Net MWh) ALL Sectors(MINN 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 146 149 146 153 162 146 120 93 74 70 Res Incremental Market Potential 146 149 146 153 162 146 120 93 74 70 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.10% 0.10% 0.10% 0.10% 0.11% 0.09% 0.08% 0.06% 0.05% 0.04% Res Incremental Potential as a%of Res Sales 0.27% 0.27% 0.27% 0.28% 0.29% 0.26% 0.21% 0.17% 0.13% 0.12% Non-Res Incremental Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 72 77 84 90 94 88 79 73 69 72 Res Incremental Market Potential 72 77 84 90 94 88 79 73 69 72 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Plumas Sierra Ten Year Cumulative Goals-Net(2018-2027) • Net Cumulative Market Potential by Sector All Sectors I nesse,Potential(MWh)and%of Sales , 1,700 0 90, ' 0 t81111 ' 1.200 0 1044 . 1,0020 14 e00 tt.60.e ...I 0 12, t ::" 4311.1 0 311,.. .,r' SOO :, • ll 20, • 0.10.4 0 0.001.4 2018 2019 2020 2021 2027 2023 2028 2025 2026 2027 =On Re,Co/64W,,tviarIcrt relern/iat 111.1.1410.1 nesi-03033043 M,Irkrt Pmennai • ' OMB CAS 11111138.6,/81.99.18,0013,1036.311,200.41 -IF Total Cum.siat.v.r.Put«.‘04146 a%a 291,5alvs 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 146 294 440 593 755 901 1,021 1,113 1,187 1,257 Res Cumulative Market Potential 146 294 440 593 755 901 1,021 1,113 1,187 1,257 Non-Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 • Total Cumulative Potential as a%of Total Sales 0.10% 0.19% 0.29% 0.39% 0.49% 0.58% 0.65% 0.71% 0.76% 0.79% Res Consolation Potential as a%of Res Sales 0.27% 0.54% 0.81% 1.08% 1.37% 1.62% 1.83% 1.99% 2.11% 2.22% Non-Res Cumulative Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(Consolation kw) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 72 148 232 321 414 503 583 659 732 808 Res Cumulative Market Potential 72 148 232 321 414 503 583 659 732 808 Non-Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Port of Oakland Ten Year Incremental Goals -Gross(2018-2027) Incremental Gross Market Potential by Sector 600 All Sectors Energy Potential(MWh)and%of Sales 0.92% 500 0.90% i 400 0.88% 3 300 0 00 0.86% a` `o 100 0.84% 0 0.82% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential MIN Non-Res Incremental Market Potential I♦C&S(If Claimed.Estimates not ava iia ble after 2024) -Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 512 517 521 526 528 530 532 533 534 535 tete. .tette_. .tete_.. .tett_ ...._. Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 ___...._ _. _....__. _ tete_ ..tette_ Non Res Incremental Market Potential 512 517 521 526 528 530 532 533 534 535 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 • tette tett tette_ Total Incremental Potential as a%of Total Sales 0.90% 0.90% 0.90% 0.90% 0.89% 0.88% 0.88% 0.87% 0.86% 0.86% tete... .tete .tete... . ..tete.._ .tett Res Incremental Potential as a%of Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% tett Non-Res Incremental Potential as a%of Non-Res Sales 0.89% 0.89% 0 89% 0.89% 0.88% 0.87% 0.87% 0.86% 0.85% 0.85% tete_. tette tette _. tett...tette _. 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 110 112 112 112 114 114 114 114 113 113 tett tete_ ...tete_ tett - _. _. tete.tete__ tete_ _ tete Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Incremental Market Potential 110 112 112 112 114 114 114 114 ' 111 3 113 .... t _ _ C&S(If Claimed..Estimates nottavailable after 2024) 0 0 0 0 0 0 0 0 0 0 tett tett. ..tete ..tett_. _ ..tett ..tette Port of Oakland Ten Year Cumulative Goals-Gross(2018-2027) Cumulative Market Potential by Sector 6,000 All Sectors Energy Potential(MWh)and%of Sales 10.00% 5,000 8.00% _ 4,000 • 6.00% 3.000 2,000 4.00% c a `o 1,000 2.00% * 0 0.00 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 MIRe s Cumulative Market Potentia I =I Non-Res Cumulative Market Potential MIIIIC&S(If Claimed.Estimates not available after 2024) tTotal Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 512 1,029 1,550 tete 2,076 2,591 3,106 3,609 4,111 4,613 5,116 _tete_ tete_ .tenti._ tete..._. tett..__tete. tete _ Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 tette. tete_ tete_ Non-Res Cumulative Market Potential 512 1,029 1,550 2,076 2,591 3,106 3,609 4,111 4,613 5,116 -tete tete. tete.__ tete._ __. __......____ C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 tett. _._. Total Cumulative Potential as a%of Total Sales 0 90% 1 79% 2 67% 3.53% 4.37% 5.18% 5.97% 6.73% 7.47% 8.19% .._-_ tette_- tete tett. Res Cumulative Potential as a%of Res Sales 0.00% 0 00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% tette__ ._-._ tete.. ... tete__tett .tette__ Non-Res Cumulative Potential as a%of Non-Res Sales 0.89% 1.77% 2.64% 3.49% 4.32% 5.12% 5.90% 6.65% 7.39% 8.11% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 110 222 334 447 559 671 778 883 988 1,093 tete_. .tete_.__ tett .tete.. tette.. .tete._.. tete__. tete__ _...__.__ Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 tette_ ...tete_ .tete.. tett. Non-Res Cumulative Market Potential 110 222 334 447 559 671 778 883 988 1,093 tette ..tette tete__ _ tette_ tete_-tete_ C&5(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 tett_. _. .tett tette. NAVIGANT Rancho Cucamonga Ten Year Incremental Goals -Gross(2018-2027) Incremental Gross Market Potential by Sector 500 All Sectors Energy Potential(MWh)and%of Sales 0.60% 0.50% „ 400 0.40%t 300 0.30%n 200 ` 0.20% a` 00 0.10% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential En Non-Res Incremental Market Potential C&S(If Claimed.Estimates not available after 2024) --Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 288 293 313 347 388 411 416 409 393 375 Res Incremental Market Potential 2 3 5 7 10 13 15 17 19 19 Non-Res Incremental Market Potential 286 290 309 340 378 398 401 392 374 356 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.37% 0.38% 0.40% 0.45% 0.49% 0.52% 0.53% 0.51% 0.49% 0.47% Res Incremental Potential as a%of Res Sales 1.10% 2.00% 2.90% 4.27% 6.00% 7.77% 9.03% 9.95% 10.77% 11.26% Non-Res Incremental Potential as a%of Non-Res Sales 0.37% 0.37% 0.40% 0.43% 0.48% 0.50% 0.50% 0.49% 0.47% 0.44% 10 Year Demand Soak(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 53 53 55 60 66 71 74 76 76 75 Res Incremental Market Potential 1 2 2 3 4 6 7 8 8 9 Non Res Incremental Market Potential 52 51 53 57 62 66 68 68 68 66 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Rancho Cucamonga Ten Year Cumulative Goals-Gross(2018-2027) Cumulative Market Potential by Sector 4,000 All Sectors Energy Potential(MWh)a nd%of Sales 5.00% 4 l7 .00% 3,000 3.00% =i 2,000 2.00% a 1,000 0 1.00% 0 0.00 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 (♦Res Cumulative Market Potential MN Non-Res Cumulative Market Potential MillC&S(If Claimed.Estimates not available after 2024) Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 288 582 895 1,242 1,630 2,029 2,422 2,810 3,174 3,513 Res Cumulative Market Potential 2 5 10 17 27 41 56 73 92 111 Non-Res Cumulative Market Potential 286 576 885 1,225 1,603 1,988 2,366 2,737 .,.3,083 3,402 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.37% 0.75% 1.15% 1.59% 2.06% 2.57% 3.07% 3.51% 3.97% 4.38% Res Cumulative Potential as a%of Res Sales 1.10% 3.10% 6.00% 10.27% 16.13% 23.91% 32.93% 42.46% 53.22% 64.46% Non-Res Cumulative Potential as a%of Non-Res Sales 0.37% 0.74% 1.13% 1.55% 2.03% 2.51% 2.95% 3.42% 3.85% 4.25% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 53 107 162 222 288 357 425 494 561 626 Res Cumulative Market Potential 1 3 5 8 13 18 25 32 41 50 Non Res Cumulative Market Potential 52 104 157 213 275 339 400 461 520 576 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Redding Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector All Sectors I-energy Potential(MWh)and 36 of Sales 3.500 ,i.Y✓", saw ;..,2660 UR11 o4a•a f o L[x%) a .. 500 (' U10JJ UTI1 `t t,v., r♦Oet.,,.,,,,Ita,M.l,ket O3iie,lial r11111115,r,.Oe>„a,e.,e„441'Na,ket 6ule„v41 1111110C&S Of 41.-Tolat l.,re,,e„ta!466,i0a143...IA TOt4154I0 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 3,336 3,466 3,666 3,858 3,629 3,439 3,438 3,352 3,234 2,695 3333 3333_.. _.. _.__.. _._. Res Incremental Market Potential 587 608 639 678 721 748 760 760 751 736 Non Res Incremental Market Potential 2,749 2,858 3,027 3,179 2,908 2,691 2,678 2,593 2,483 1,958 3333. 3333 __ 3333.. C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.44% 0.45% 0.48% 0.51% 0.48% 0.45% 0.45% 0.0.44% 0.42% 0.37% 3333__. 8833 8333 Res Incremental Potential as a%of Res Sales 017% 0.18% 0.19% 0.20% 0.21% 0.22% 0.23% 0.23% 0.22% 0.22% 3333. 3383__ 8333. 8383 Non Res Incremental Potential as a%of Non-Res Sales 0.66% 0.68% 0.72% 0.76% 0.69% 0.64% 0.64% 0.62% 0.59% 0.46% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 836 879 944 1,012 1,065 1,066 1,071 1,053 1,028 893 8833 3833.8883 3333 Res Incremental Market Potential 240 250 266 288 305 319 328 332 333 332 8333 Non Res Incremental Market Potential 595 628 678 724 759 747 743 720 695 561 3388 _. C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Redding Ten Year Cumulative Goals-Net(2018-2027) • Net Cumulative Market Potential by Sector „ All Sectors anergy Potential(MWh)and 76 of Sales uurin nso L 20.000 .00!: t 5 I'.0n) 2.5044 .4 la.., I SO% Y 0 U al 0.00.4 2016 201.1 .U.tl 2021 202: 1023 2024 2025 .21.126 10.7 4_11.,r„m„14*v6 M1,16:k,x.,1144, IllNnn Res i 6.66W6r Market vnten641 MEW.5,0”664,1) —0—In64,,6,66146,61,44n641434,6.6-44,4Vv 10 Year Energy Goals(Cumulative Net MWh) ALL Senors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 3,336 6,802 10,468 14,235 17,776 20,999 24,208 27,320 30,298 32,661 --_ 3888 Res Cumulative Market Potential 587. 1,194 1,833 2,421 3,053. 3,585 4,118 4,643 5,152 5,614 -__ ._r... .__ _._ 8333. Non-Res Cumulative Market Potential 2,749 5,607 8,635 11,814 14,722 17,413 20,090 22,678 25,146 27,047 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 3333 3333.. _. Total Cumulative Potential as a%of Total Sales 0.44% 0.89% 1.36% 1.87% 2.34% 2.77% 3.18% 3.59% 3.97% 4.50% 3888_ 8333 8833 .. Res Cumulative Potential as a%of Res Sales 0.17% 0.35% 0.54% 0.71% 0.90% 1.07% 1.22% 1.38% 1.53% 1.66% 8833_ 3338_ _._. _.. _. Non-Res Cumulative Potential as a%of Non-Res Sales 0.66% 1.34% 2.06% 2.82% 3.51% 4.15% 4.78% 5.38% 5.96% 6.39% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 836 1,714 2,658 3,665 4,726 5,678 6,627 7,550 8,440 9,180 8333 8333_. 3888.._ _ 3383 Res Cumulative Market Potential 240 491 757 1,040 1,342 1,546 1,752 1,956 2,155 2,342 _.. _.8833 Non-Res Cumulative Market Potential 595 1,224 1,901 2,625 3,384 4,132 4,875 5,594 6,286 6,838 3883._ C&5(It Claimed) 0 0 0 0 0 0 0 0 0 0 3333 3333 _ _.. _. NAVIGANT Riverside Ten Year Incremental Goals-Net(2018-2027) Net Incromeastal Market Potential by Sector All Sectors Energy Potential(MWh)and 96 ot Sales :.,,000 i.ces , •,,, loom, . 7..0>0 0 2C0s. 0 01, /0114 /OM. /WO to, 00.1 XII. 1014 -100. 101 1 10 Year Energy Goals(Net MW11) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 20594 20,815 20,309 19,451 18,492 17,505 16,426 15,403 14,310 12,968 Res Incremental Market Potential 5,043 4,697 4,459 4,526 4,866 5,093 5,206 5,084 4,773 4,500 Non-Res Incremental Market Potential 15,550 16,118 15,850 14,925 13,626 12,412 11,220 10,319 9,538 8,468 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.90% 0.90% 0.88% 0.84% 0.80% 0.75% 0.70% 0.66% 0.61% 0.55% Res Incremental Potential as a%of Res Sales 0.67% 0.62% 0.59% 0.60% 0.64% 0.66% 0.68% 0.66% 0.62% 0.58% Non-Res Incremental Potential as a%of Non-Res Sales 0.99% 1.03% 1.01% 0.94% 0.86% 0.78% 0.70% 0.65% 0.60% 0.53% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 7,463 7,107 6,915 6,981 7,050 6,979 6,908 6,283 5,595 4,608 Res Incremental Market Potential 3,941 3,436 3,291 3,527 3,849 4,190 4,396 3,986 3,482 2,671 Non-Res Incremental Market Potential 3,522 3,671 3,624 3,454 3,201 2,788 2,512 2,298 2,113 1,936 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Riverside Ten Year Cumulative Goals-Net(2018-2027) Nel Lornolatrve Markel Pol.-NOLA trySector AAll Sectors t runny Potential WWII)and 96 oil Sate, . i n.oce too.o:ro 7.00.4 140.000 I 1,,,.!.... 1(10.011C 'g )4,011•1 ..•". .7 00a, ,.. ! Z0.000 1,00, 0 0.00, , 401K JO, t0.(4,1 /01 I 40)1 101 i '10.to 11.11, 10,1, /011 IMMO Rea CU,,,t4,elve Moll,.Outer.tta, MOM 400-ite s Cllt.1,20Y,Meek.Pote.,,,, MIMS CLS PI C40.0ed) .1111...70te.COP1IVI•llYV P.......t..41 45....r a Tutal Sawa 10 Year Energy Goals(Cumulative Net NiWh) ALL Sectors(Cumulative MINA) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 20,594 41,409 61,719 81,170 99,662 116,581 131,430 145,170 157,742 168,729 Res Cumulative Market Potential 5,043 9,741 14,200 18,726 23,593 28,394 32,678 36,727 40,348 43,588 Non-Res Cumulative Market Potential 15,550 31,669 47,518 62,443 76,069 88,187 98,752 108,443 117,394 125,140 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.90% 1.80% 2.68% 3.51% 4.29% 5.00% 5.62% 6.19% 6.72% 7.12% Res Cumulative Potential as a%of Res Sales 0.67% 1.29% 1.87% 2.46% 3.08% 3.70% 4.25% 4.76% 5.22% 5.64% Non-Res Cumulative Potential as a%of Non-Res Sales 0.99% 2.02% 3.03% 3.95% 4.80% 5.55% 6.20% 6.80% 7.36% 7.84% 10 Year Demand Goals(Consolation kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 7,463 14,571 21,487 28,466 35,514 42,415 49,024 54,995 60,261 64,516 Res Cumulative Market Potential 3,941 7,378 10,669 14,195 18,042 22,194 26,344 30,065 33,262 35,640 Non-Ret Cumulative Market Potential 3,522 7,194 10,817 14,271 17,472 20,221 22,681 24,931 26,999 28,876 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 • NAVIGANT Roseville Ten Year Incremental Goals -Gross(2018-2027) Incremental Gross Market Potential by Sector 12,000 All Sectors Energy Potential(MWh)and%of Sales 1.00% 10,000 0.80% w 8,000 liall"1"Mil- 0.60% 3 2 6,000 ;‘'4,0000.40%2,0000.20% ° 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Mil Res Incremental Market Potentia I MI Non-Res Incremental Market Potential IIIIIINC&S(If Claimed) —Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 8,413 8,549 8,995 9,578 10,063 10,000 9,275 8,556 7,977 7,895 Res Incremental Market Potential 6,338 6,448 6,560 6,661. 6,760 6,847 6,873 6,880 6,871 6,838 Non Res Incremental Market Potential 2,074 2,101 2,435 2,917 3,303 3,152 2,402 1,677 1,106 1,058 —.. ...._ _._ C&5(If Claimed) 0 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.71% 0.72% 0.76% 0.81% 0.85% 0.85% 0.80% 0.74% 0.70% 0.70% Res Incremental Potential as a%of Res Sales 1.47% 1.50% 1.53% 1.56% 1.58% 1.61% 1.63% 1.65% 1.67% 1.68% Non Res Incremental Potential as a%of Non Res Sales 0 27% 0 28% 0.32% 0.38% 0.44% 0.42% 0.32% 0.23% 0.15% 0.15% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 965 1,132 1,426 1,681 1,786 1,565 1,458 1,350 1,260 1,239 Res Incremental Market Potential 187 212 247 286 322 346 361 367 369 367 Non-Res Incremental Market Potential 777 920 1,179 1,395 1,464 1,219 1,097 983 891 871 C&5(If Claimed) 0 0 0 0 0 0 0 0 0 0 Roseville Ten Year Cumulative Goals-Gross(2018-2027) Cumulative Market Potential by Sector 40,003 All Sectors Energy Potential(MWh)and%of Sales 3.50% 3.00 30,000 2.50Ei 3 20,000 2.002 10,000 S.DO% 0 0.50% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Cumulative Market Potential IMO Non-Res Cumulative Market Potential MIIMC&S(If Claimed) —Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 8,413 11,400 14,852 18,707 23,019 26,436 29,652 32,105 33,930 35,566 Res Cumulative Market Potential 6,338 7,622 9,037 10,373 11,780 12,583 13,956 15,334 16,698 17,966 Non-Res Cumulative Market Potential 2,074 3,777 5,814 8,334 11,239 13,852 15,696 16,771 17,233 17,601 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.71% 0.96% 1.25% 1.58% 1.95% 2.25% 2.55% 2.78% 2.98% 3.14% Res Cumulative Potential as a%of Res Sales 1.47% 1.77% 2.11% 2.43% 2.76% 2.95% 3.31% 3.68% 4.05% 4.41% Non-Res Cumulative Potential as a%of Non-Res Sales 0.27% 0.50% 0.76% 1.10% 1.48% 1.85% 2.11% 2.29% 2.38% 2.46% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 965 2,097 3,522 5,203 6,989 7,820 8,456 8,776 8,688 8,318 Res Cumulative Market Potential 187 399 646 931 1,253 1,467 1,733 1,994 2,238 2,454 Non-Res Cumulative Market Potential 777 1,698 2,876 4,272 5,736 6,353 6,723 6,781 6,450 5,864 C&5(If Claimed) -... _._ 0..._ 0_...._ 0 0 0 _.0.. 0 0 0 0 NAVIGANT San Francisco Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector "'an All Sectors lnorgy Potential(MWble )and%of Sas Ir urv._ g t1 )t)tR 3Cri'1 )i Vtl <cttl )�li> 2c>)i 1a)a 1<v. >Dir; tl»> tt1... 11.110aNes ln.reme Mar.,ikxentwi t♦Nnn tte a I nct..mamnr Market Pc,,,,rnf �C$}Of iCI.rnwali k%tirtutfl nut avatfatilr 4801 211'4) y-rotal in,Per11011.l 11 ,04(9%%a% 101.0 SAIY% 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 2,736 2,853 2,764 2,657 2,596 2,524 2,435 2,324 2,255 2,209 Res Incremental Market Potential 1 2 2 3 3 4 4 5 5 5 Non-Res Incremental Market Potential 2,735 2,851 2,762 2,654 2,593 2,520 2,431 2,320 2,250 2,204 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.27% 0.28% 0.27% 0.25% 0.25% 0.24% 0.23% 0.22% 0.21% 0.20% Res Incremental Potential as a%of Res Sales 0.01% 0.01% 0.01% 0.02% 0.02%. 0.02% 0.03% 0.03% 0.03% 0.03% Non-Res Incremental Potential as a%of Non-Res Sales 0.26% 0.27% 0.26% 0.25% 0.24% 0.23% 0.22% 0.21% 0.21% 0.20% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 335 371 377 373 383 399 402 400 402 409 Res Incremental Market Potential 0 0 .1 1 1 1 1 1 1 1 Non-Res Incremental Market Potential 335 371 377 372 382 398 401 398 401 ...407 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 San Francisco Ten Year Cumulative Goals-Net(2018-2027) • Net Cumulative Market Potential by Sector li 25.000 All Sectors Energy Potential(MWh)and 96 of Sales soman 15030 1-t.0.. 4 10.000 2018 2019 2020 2021 2027 2023 2024 2025 2026 2027 t♦Rrs 0l1,a0.000 Markrt Pornr,4I 11111111119v0 nes Comu4 t:vr Marirt Petenefll ♦G:&S III Cla1Ptra.Ertirt,ataa r(0 avaNatAr altar 2023) - -Tu1altuI 6rfivr P0trilial as a%0r Tutal Sales 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 2,736 5,588 8,352 11,009 13,518 15,616 17,618 19,495 21,294 23,002 Res Cumulative Market Potential 1 3 5 8 11 15 19 23 28 32 Non-Res Cumulative Market Potential 2,735 5,586 8,347 11,001 13,506. 15,601 17,599 19,471 21,266 22,970 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.27% 0.54% 0.80% 1.05% 1.28% 1.47% 1.65% 1.82% 1.98% 2.08% Res Cumulative Potential as a%of Res Sales 0.01% 0.02% 0.03% 0.05% 0.07% 0.10% 0.12% 0.15% 0.17% 0.20% Non-Res Cumulative Potential as a%of Non-Res Sales 0.26% 0.53% D79% 1.03% 1.26% 1.45% 1.63% 1.79% 1.95% 2.10% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 .2022 2023 2024 2025 2026 2027. Total Cumulative Market Potential 335 706 1,083 1,456 1,833 2,237 2,645 3,054 3,484 3,935 Res Cumulative Market Potential 0 1 1 2 3 4 5 6 8 9 Non Res Cumulative Market Potential 335 705 1,082 1,454 1,830 2,233 2,640 3,047 3,477 3,926 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Shasta Lake Ten Year Incremental Goals-Net(2018-2027) Not Incremental Market Polonti.rl by tone All Sectors Energy Potential(MWh)and%of Sales ..w.+a 600 o.as,,, ,an e+.al^� Y aryl .; G.25'� �1u .,n1r �S u l:. «rx le, 0.05 J[j litili ;ciLh 10)?.nes.u,t uva,wbM all.Y 20.40 -.l-renal lin .b-a 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 487 519 550 579 600 635 635 601 551 482 Res Incremental Market Potential 74 90 107 128 154 185 186 156 125 100 Non-Res Incremental Market Potential 413 428 443 451 447 450 449 445 425 382 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.27% 0.27% 0.29% 0.30% 0.33% 0.33% 0.33% 0.32% 0.31% 0.28% Res Incremental Potential as a%of Res Sales 0.20% 0.23% 0.27% 0.32% 0.41% 0.47% 0.47% 0.39% 0.33% 0.28% Non-Res Incremental Potential as a%of Non-Res Sales 0.27% 0.28% 0.29% 0.32% 0.30% 0.30% 0.30% 0.31% 0.31% 0.30% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,763 76 78 79 79 79 80 81 82 81 Res Incremental Market Potential 24 26 26 28 29 30 31 33 35 39 Non-Res Incremental Market Potential 1,739 51 52 52 50 49 48 48 46 42 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Shasta Lake Ten Year Cumulative Goals-Net(2018-2027) Not t: Wive Market Pcslenlial by Sermon 6.000All Sectors Energy Potential(MVN11)and%of Sale. x sls^n '..,i 5.000 Lilt,. 4,000 �4 5 .xxt �,e. ai 1 vat. :.nxl 1 lu,a 7. 1.000 0.`�'.3"v o 0.0.+e t016 L036 t4tLU «V/1 LUL« 101,1 ZUZ4 .0 10 10.6 LOZt NUM Has reowsiatwn 161.0.tbtentia. 11111460 Neva 1 umuiat.vv.Mnrknt Hoteransi Cbl It I Clai .,1:I Meal,001 available-alleI 2020 ainiF tut,CuniulalivaiP..Mal as a?b NA tonal 341. 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MW8) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 487 1,006 1,556 2,130 2,714 3,315 3,897 4,430. 4,899 5,276 Res Cumulative Market Potential 74 165 272 395 541 703 852 958 1,017 1,032 Non-Res Cumulative Market Potential 413 841 1,284 1,735 2,173. 2,612 3,044 3,473 3,881 4,245 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.27% 0.53% 0.82% 1.12% 1.51% 1.75% 2.05% 2.34% 2.73% 3.09% Res Cumulative Potential as a%of Res Sales 0.20% 0.41% 0.68% 0.99% 1.44%. 1.77% 2.15% 2.41% 2.70% 2.89% Non-Res Cumulative Potential as a%of Non-Res Sales 0.27% 0.56% 0.85% 1.21% 1.44% 1.73% 2.02% 2.43% 2.87% 3.31% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 74 150 228 307 385 458 527 597 668 737 Res Cumulative Market Potential 24 49 76 103 132 157 180 205 233 263 Non-Res Cumulative Market Potential 50 100 152 203 253 301 347 392 436 474 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Silicon Valley Power Ten Year Incremental Goals-Net(2018-2027) incr ernennial Cross Markel Potential by Sector All Sectors.Energy Potential(MWh)and Sales %of Sas i, t_r. 1r.nixt v no,iR It.tou 5. Z 1 u a.orX, 0.:0'a A.tx Hl I I I I I I I 451.Y:. , t,txX fi ll t♦ilr-rinrlrm,-ntn,M,e,krt/Min••ii.t, MIMI Noe lir.inetr..,rnt.ri M.j,44.1 nnl+nt»i t•S St,let(tvettnd) f1.Vniinr„•enant,al l.+rpteti:t+ev n 4„n11Mn1•.,In♦ 10Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 12,851 13,032 14,015 14,928 15,129 14,565 13,333 12,192 11,528 10,590 Res Incremental Market Potential 205 238 277 328 371 383 388 392 395 397 Non-Res Incremental Market Potential 12,646 12,794 13,738 14,600 14,758 14,182 12,945 11,800 11,132 10,193 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.42% 0.43% 0.46% 0.48% 0.48% 0.46% 0.42% 0.38% 0.36% 0,33% Res Incremental Potential as a%of Res Sales 0.09% 0.10% 0.12% 0.14% 0.15% 0.16% 0.16% 0.16% 0.16% 0.16% Non-Res Incremental Potential as a%of Non-Res Sales 0.45% 0.45% 0.48% 0.51% 0.51% 0.49% 0.44% 0.40% 0.38% 0.34%. 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 572,845 523,147 524,930 541,304 546,184 447,497 355,679 49,371 24,884 8,915 Res Incremental Market Potential 25 29 32 34 35 36 37 38 38 38 Non-Res Incremental Market Potential 572,820 523,118 524,898 541,270 546,149 447,461 355,642 49,334 24,846 8,876 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Silicon Valley Power Ten Year Cumulative Goals-Net(2018-2027) C. Int iw•Markel e-1 Potenti.tl lay Soul or Iu,ax l All Sectors r mirky Potential(MWh)and%01 Sales x i, '.i wee, x, n:,tr,e a.C10, III 3 5t5Il,040 2.ZX1'V. , 1 1.00.1s l01 i+ Jill's ,'l,Jl1 ttiJ 1 ',It, AM f Al., eql,,, JI1J1r. ..,,J Res Cweu,etne Market Patera, Non-Pe4 Cwnulet:v<Merkel Potent., r111111111Cr.s lel Cteo,ed) –i–tote,Cumulstefe PotenGel es e,of'rot,Sok, 10 Year Energy Goals(Cumulative Net MW h) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 .2026. 2027 Total Cumulative Market Potential 12,851 25,883 39,898 54,826 69,955 84,511 97,718 109,759 121,093 131,343 Res Cumulative Market Potential 205 443 721 1,049 1,419 1,795 2,089 2,373 2,651 2,922. Non-Res Cumulative Market Potential 12,646 25,440 39,177 53,777 68,536 82,716 95,629 107,386 118,443___._128,421 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.42% 0.84% 1.30% 1.77% 2.24% 2.69%. 3.10% 3.46% 3.81% 4.11% Res Cumulative Potential as a%of Res Sales 0.09% 0.19% 0.30% 0.43% 0.58% 0.73% 0.85% 0.96% 1.07% 1.17% Non-Res Cumulative Potential as a%of Non-Res Sales 0.45% 0.89% 1.37% 1.87% 2.36% 2.84% 3.27% 3.66% 4.02% 4.34% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 572,845 1,096,065 1,621,069 2,16.2,435 2,708,671 3,156,342 3,512,373 3,563,952 3,591,497 3,603,233 Res Cumulative Market Potential 25 54 86 120 156 190 209 225 239 253 _—. Non Res Cumulative Market Potential 572,820 1,096,010 1,620,983 2,162,315 2,708,515 3,156,151 3,512,165 3,563,728 3,591,258 3,602,981 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 NAVIGANT SMUD Ten Year Incremental Goals -Gross(2018-2027) Incremental Gross Market Potential by Sector 200,000 AllSectorsEner Potential Il a )and%of Sales 2.00% 1so,00o ... __,.__.. v so% X100,000 1.00%- a 50,000 0.50%o 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 NM Res Incremental Market Potentia I Non-Res Incremental Market Potential C&5(If Claimed.Estimates not available after 2024) tTotal Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 149,626 154,902 164,286 175,198 183,687 187,401 181,428 168,982 157,634 145,870 Res Incremental Market Potential 65,706 65,164 63,158 71,826 82,175 86,050 82,037 70,380 59,946 50,519 Non-Res Incremental Market Potential 46,921 47,739 48,128 48,373 48,512 47,351 47,391 47,602 47,688 46,351 C&S(If Claimed.Estimates not available after 2024) 37,000 42,000 53,000 55,000 53,000 54,000 52,000 51,000 50,000 49,000 Total Incremental Potential as a%of Total Sales 1.34% 1.37% 1.43% 1.51% 1.55% 1.56% 1.48% 1.36% 1.25% 1.14% Res Incremental Potential as a%of Res Sales 1.33% 1.30% 1.24% 1.38% 1.55% 1.58% 1.48% 1.24% 1.04% 0.86% Non-Res Incremental Potential as a%of Non Res Sales 0.75% 0.75% 0.75% 0.74% 0.74% 0.71% 0.70% 0.70% 0.69% 0.66% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 131,543 135,519 140,972 145,982 149,594 131,393. 132,947 133,068 134,734 136,139 Res Incremental Market Potential 10,445 10,691 10,843 11,713 12,746 12,893 12,880 11,019 10,723 10,276 Non-Res Incremental Market Potential 111,488 113,726 116,011 118,340 120,699 100,538 102,370 104,291 106,199 108,004. C&5(If Claimed.Estimates not available after 2024) 9,610 11,102 14,118 15,929 16,149 17,963 17,697 17,758 17,812 17,859 SMUD Ten Year Cumulative Goals-Gross(2018-2027) Cumulative Market Potential by Sector 1,500,000 AI I Sectors Energy Potential(MWh)and%of Sales 12.00% 10.00% N 1,000,000 8.00% _. 0 6.00% - 500,000 4.00% a `o 2.00% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 11=Res Cumulative Market Potentia I nil Non-Res Cumulative Market Potential IMINIC&5(If Claimed.Estimates not available after 2024) �STotal Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross MWh) ALL Sectors(Cumulative 114W6) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 149,626 288,718 437,060 592,921 756,514 907,832 1,049,981 1,178,333 1,293,458 1,392,735. Res Cumulative Market Potential 65,706 119,277 170,704 227,404 293,695 356,014 412,154 456,420 488,529 507,295 Non-Res Cumulative Market Potential 46,921 90,441 134,355 178,516 222,819 257,819 291,827 324,913 357,929 389,440 C&S(If Claimed.Estimates not available after 2024) 37,000 79,000 132,000 187,000 240,000 294,000 346,000 397,000 447,000 496,000. Total Cumulative Potential as a%of Total Sales 1.34% 2.56% 3.81% 5.09% 6.39% 7.54% 8.58% 9.48% 10.24% 10.85% Res Cumulative Potential as a%of Res Sales 1.33% 2.38% 3.34% 4.36% 5.52% 6.56% 7.43% 8.06% 8.45% 8.59% Non-Res Cumulative Potential as a%of Non-Res Sales 0.75% 1.43% 2.09% 2.75% 3.38% 3.86% 4.32% 4.75% 5.16% 5.55% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 131,543 257,452 387,322 519,186 652,852 611,309 565,499 516,368 465,460 412,408 Res Cumulative Market Potential 10,445 21,136 31,979 43,693 56,439 68,238 79,130 88,138 96,719 104,675 Non-Res Cumulative Market Potential 111,488 225,214 341,225 459,564 580,263 525,109 468,672 410,472 350,928 289,874 C&S(If Claimed.Estimates not available after 2024) 9,610 11,102 14,118 15,929 16,149 17,963 17,697 17,758 17,812 17,859 NAVIGANT Trinity Ten Year Incremental Goals-Net(2018-2027) Net Incremental Misr lel P01 tnil ii II by Sector All Sectors Energy Potential(MWh)and%ot Sates 7 07'o°Li ts' •, 6 , 0.01, IL' t• , MEW it.,inr,,,,,,,fal Mara,Praer,i n I IMMO W.,lira,,rrearnara ai IN.a-altat P.,,i.,,,a, C.Ed.S,A1 Clamped_Estirrusta,9tat....AAA,Altai 202a a....-IL,I al loatarra..ial iNataillisi as a,-.4 IA 1,21,Saf., . 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 7 6 6 6 6 6 6 6 6 6 Res Incremental Market Potential 7 6 6 6 6 6 6 6 6 6 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.01% 0.01% 0.01% 0.01% 0,01% 0.01% 0.01% 0.01% 0.01% 0.01% Res Incremental Potential as a%of Res Sales 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% Non-Res Incremental Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1 1 1 1 1 1 1 1 1 - 1 Res Incremental Market Potential 1 1 1 1 1 1 1 1 1 1 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Esti mates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Trinity Ten Year Cumulative Goals-Net(2018-2027) • • Net Cumulative Market Potential by Sector All Sectors Energy Potential(MWh)and%of Sakes 50 ti a0 I I i I I II I 1: 94u, .2‘ OW,, S.M., .10 29 le.5 1111111011tas,tirnistaiva Knarinat Paster-a,. VOIN•!Inn...,I-lanolai.w.a FOAM.,fanfaraus, MIR CAS It 0 tutot.t.l.k,limalas klcA u‘e.iituttte uttot 507.41 ...I...Total CotouLattvul 00tottlial as A%on 101,Sado, 10 Year Energy Goals(Cumulative Net NMI)) ALL Sectors(CurnulatNe MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 7 13 19 25 31 37 43 49 55 61 Res Cumulative Market Potential 7 13 19 25 31 37 43 49 55 61 Non-Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.01% 0.01% 0.02% 0.02% 0.03% 0.04% 0.04% 0.05% 0.05% 0.06% Res Cumulative Potential as a%of Res Sales 0.01% 0.01% 0.02% 0.02% 0.03% 0.04% 0.04% 0.05% 0.05% 0.06% Non-Res Cumulative Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1 2 3 4 5 6 7 8 9 10 Res Cumulative Market Potential 1 2 3 4 5 6 7 8 9 10 Non-Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Truckee Donner Ten Year Incremental Goals -Gross(2018-2027) Incremental Gross Market Potential by Sector 800 All Sectors Energy Potential(MWh)and%of Sales 0.50% IIIIIIIII11[111 a., 600 — 0.40% 3 400 0.30% Z 0.20% 200 0.10% * 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 NM Res Incremental Market Potential Non-Res Incremental Market Potential NMC&S(If Claimed.Estimates not available after 2024) —Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 730 639 654 672 689 693 693 686 685 679 Res Incremental Market Potential 585 496 511 537 567 578 583 580 579 576 Non-Res Incremental Market Potential 144 143 143 135 123 115 110 107 106 102 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.50% 0.43% 0.44% 0.45% 0.46% 0.46% 0.45% 0.45% 0.44% 0.43% Res Incremental Potential as a%of Res Sales 0.76% 0.64% 0.66% 0.68% 0.72% 0.73% 0.73% 0.72% 0.71% 0.70% Non-Res Incremental Potential as a%of Non-Res Sales 0.21% 0.20% 0.20% 0.19% 0.17% 0.16% 0.15% 0.14% 0.14% 0.14% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 236 237 248 233 247 238 245 235 236 225 Res Incremental Market Potential 207 209 220 208 226 218 225 215 215 204 Non-Res Incremental Market Potential 29 28 27 25 21 20 20 20 21 21 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Truckee Donner Ten Year Cumulative Goals-Gross(2018-2027) Cumulative Market Potential by Sector 8,000 All Sectors Energy Potential(MWh)and%of Sales 5.00% 6,000 4.00% lil 3 4,000 3.00% 3 2.00% F a 2,000 0 1.00% * 0 0.00 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 I Res Cumulative Market Potential O=Noo-Res Cumulative Market Potential 0111111C&S(If Claimed.Estimates not available after 2024) —Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Gross MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 730 1,368 2,022 2,694 3,384 4,063 4,581 5,085 5,581 6,062 Res Cumulative Market Potential 585 1,081 1,592 2,129 2,695 3,259 3,669 4,069 4,463 4,851 Non-Res Cumulative Market Potential 144 287 430 566 688 803 912 1,016 1,118 1,212 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.50% 0.93% 1.37% 1.80% 2.24% 2.67% 2.99% 3.30% 3.60% 3.88% Res Cumulative Potential as a%of Res Sales 0.76% 1.40% 2.05% 2.71% 3.40% 4.09% 4.57% 5.04% 5.49% 5.93% Non-Res Cumulative Potential as a%of Non-Res Sales 0.21% 0.41% 0.60% 0.79% 0.95% 1.10% 1.24% 1.38% 1.50% 1.62% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 236 472 720 953 1,201 1,436 1,635 1,823 2,010 2,189 Res Cumulative Market Potential 207 416 637 845 1,071 1,286 1,465 1,632 1,799 1,957 Non-Res Cumulative Market Potential 29 56 83 108 130 150 170 190 211 231 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Turlock Irrigation District Ten Year Incremental Goals-Net(2018-2027) Nei Ince errrental Market Potential by Sector a AU S e.ct1,.I riergy Polennal(MWI))and 94 or...aid, j )01n201n )ron 207120J> 7075 >n24n26207710 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021. 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 12,994 12,987 12,909 12,143 11,615 10,893 10,536 10,316 10,152 9,479 Res Incremental Market Potential 3,367 3,416 3,456 3,502 3,545 3,585 3,624 3,664 3,702 3,739 Non-Res Incremental Market Potential 3,990 4,127 4,368 4,615 4,715 4,714 4,593 4,523 4,463 3,872 C&S(If Claimed) 5,637 5,445 5,085 4,026 3,355 2,595 2,319 2,130 1,987 1,868 Total Incremental Potential as a%of Total Sales 0.59% 0.58% 0.57% 0.53% 0.50% 0.46% 0.44% 0.43% 0.42% 0.38% Res Incremental Potential as a%of Res Sales 0.45% 0.45% 0.45% 0.45% 0.46% 0.46% 0.46% 0.46% 0.46% 0.46% Non-Res Incremental Potential as a%of Non-Res Sales 0.27% 0.27% 0.29% 0.30% 0.30% 0.30% 0.29% 0.28% 0.27% 0.23% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 3,236 3,267 3,120 3,002 2,887 2,607 2,515 2,481 2,456 2,309 Res Incremental Market Potential 46 48 49 50 51 52 52 53 53 53 Non-Res Incremental Market Potential 1,507 1,549 1,584 1,607 1,596 1,421 1,392 1,396 1,403 1,286 C&S(If Claimed) 1,684 1,670 1,488 1,345 1,239 1,135 1,071 1,032 1,000 970 Turlock Irrigation District Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector All Sectors I nergy Potential(MWh)and 96 of Sales a,W„a 3.005, ... T. IIS 5.arta., ),err. 10.0110 : Jt)001.1 t r-u•a 10.000 0 000`, 2010 2019 2020 2021 2022 2023 2024 2025 2026 2027 MM.,.e.unxaatn.Market VMele,el rrrrr�NVn-ues,_u,,,,.tat,v.Mater Valent,. a c&.Irt Claimed) libl.,ta Cu,nulat,we Vote n t,al et a t.0 I otei S.e4s 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 12,994 22,856 32,604 41,550 49,933 57,554 64,703 71,591 78,257 84,162 Res Cumulative Market Potential 3,367 3,658 3,952 4,257 4,570 4,883 5,126 5,369 5,614 5,857 Non-Res Cumulative Market Potential 3,990 8,117 12,485 17,100 21,815 26,528 31,116 35,630 40,065 43,858 C&S(If Claimed) 5,637 11,082 16,166 20,193 23,548 26,142 28,462 30,592 32,579 34,447 Total Cumulative Potential as a%of Total Sales 0.59% 1.02% 1.44% 1.81% 2.15% 2.45% 2.72% 2.98% 3.22% 3.42% Res Cumulative Potential as a%of Res Sales 0.45% 0.49% 0.52% 0.55% 0.59% 0.62% 0,64% 0.67% 0.69% 0.71% Non Res Cumulative Potential as a%of Non-Res Sales 0.27% 0.54% 0.82% • 1.10% 1.39% 1.67% 1.94% 2.20% 2.44% 2.64% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 3,236 4,816 6,260 7,764 9,293 10,637 11,976 13,347 14,728 15,990 Res Cumulative Market Potential 46 91 134 177 219 259 281 302 323 343 Non-Res Cumulative Market Potential 1,507 3,055 4,638 6,242 7,834 9,243 10,625 12,013 13,405 14,676 C&S(If Claimed) - 1,684 1,670 1,488 1,345 1,239 1,135 1,071 1,032 1,000 970 NAVIGANT Ukiah Ten Year Incremental Goals-Net(2018-2027) Net Increonent l Markel Potential by Sector All Sa>r:tors t...ray l%,tentlal(MWtt)anal%nt Salim, 1:- P.040 01.204,3 : 00 ince o.to 0 O.:n•. 701A 2010 _Re.it...eo e.ttat Mmaet Oott-0041 11.=11400-Re5 t...lo/oe.taI Metk.t Outo00.i IMMIINc tet,..ciatol>a.e,t. .not a.,a Cat...ane,,u..tf ft-total Incr.-corn,at we....t.ai a,a 4.m 10.,,A1., 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 398 441 484 520 550 575 599 617 625 626 Res Incremental Market Potential 23 24 24 -23 25 26 26 26 26 26 Non-Res Incremental Market Potential 375 417 460 497 526 550 573 591 599 601 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.36% 0.40% 0.44% 0.46% 0.49% 0.51% 0.53% 0.54% 0.54% 0.54% Res Incremental Potential as a%of Res Sales 0.06% 0.07% 0.06% 0.06% 0.06% 0.07% 0.07% 0.07% 0.07% 0.06% Non-Res Incremental Potential as a%of Non-Res Sales 0.52% 0.57% 0.62% 0.67% 0.71% - 0.73% 0.76% 0.78% 0.78% 0.78% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 475 493 511 528 542 474 486 496 504 511 Res Incremental Market Potential 12 13 13 13 13 14 14 14 14 14 Non-Res Incremental Market Potential 463 480 498 515 529 460 472 482 490 497 C&5(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Ukiah Ten Year Cumulative Goals-Net(2018-2027) Net C (alive Mar lug Pot...diral by Sn nlee 1,t y w t All Sect ors t nergy Potential(MWh)and%of Sakes r . ,uN t 4'�^a 1 4.00 ro .ao^ 1.00,0 ttn.,4 a,ti /1/11-•/1/11-• r tt,.<. I,t EMS ',lie u.,t.10101a,M+marls Yoton,.at MINNru„n.t<.,t umtua,..,i.n4rl.t r.,r..,,.at M=BC&S III C.Iaitra..1!al Ottale.t lot avatlablo alt•t 10:.1j -1111...20:a1 Cottalwbw 1...W0tial u.A%a lutai Sala, 10 Year Energy Goals(Cumulative Net MINN ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 398 840 1,323 1,844 2,394 2,969 3,566 4,180 4,800 5,412 Res Cumulative Market Potential 23 48 71 94 119 145 169 193 216 239 Non-Res Cumulative Market Potential 375 792 1,252 1,749 2,275 2,824 3,397 3,987 4,584 5,173 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Cumulative Potential as a%of Total Sales 0.36% 0.76% 1.19% 1.65% 2.14% 2.63% 3.13% 3.67% 4.17% 4.67% Res Cumulative Potential as a%of Res Sales 0.06% 0.13% 0.19% 0.25% 0.31% 0.38% 0.44% 0.50% 0.55% 0.61% Non-Res Cumulative Potential as a%of Non-Res Sales 0.52% 1.08% 1.69% 2.37% 3.05% 3.76% 4.52% 5.26% 5.99% 6.70% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 475 968 1,480 2,007 2,549 3,023 3,509 4,004 4,508 5,018 Res Cumulative Market Potential 12 25 38 51 65 78 92 106 121 135 Non-Res Cumulative Market Potential 463 943 1,441 1,956 2,485 2,945 3,416 3,898 4,388 4,883 C&5(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 NAVIGANT Vernon Ten Year Incremental Goals-Net(2018-2027) Net Incremental Markn,t Potential by%edaar All Sectors Energy Potential(MWh)and 96 of Sates (,ixxt U.SO.<. •.''' 0.40. 4.000 .r 4 0.. 0.30^4 6 2nti 0 10". 4000 u MIN 1019 1010 /0,1 tall 1f111 1014 101, 1011, 10,/ 411111•944,nrrrmrnr It Mark rt nmonr,.al t♦Nnn 9r—.1h'(rrnn M41 Matter rrtrrt,.',1 (♦CGS In G14411441.E)t„l141r4 n..•1 Av4a4LM alta,:.f2,:A) yFl�ta1 11444014.4.44 4,4441141 4.4 b91 14441 Sake., 10 Year Energy Goals(Net MWh) Alt Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 5,268 5,218 5,523 5,618 5,544 5,145 4,536 4,147 3,900 3,557 Res Incremental Market Potential 0 0 0 0 0 0 0 0 Non-Res Incremental Market Potential 2,652 2,990 3,396 3,758 3,741 3,442 3,072 2,888 2,817 2,626 C&S(If Claimed.Estimates not available after 2024) 2,616 2,227 2,127 1,860 1,803 1,702 1,464 1,259 1,083 931 Total Incremental Potential as a%of Total Sales 0.44% 0.44% 0.46% 0.47% 0.46% 0.43% 0.37% 0.34% 0.32% 0.29% Res Incremental Potential as a%of Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Non-Res Incremental Potential as a%of Non-Res Sales 0.22% 0.25% 0.28% 0.31% 0.31% 0.28% 0.25% 0.24% 0.23% 0.22% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,961 3,200 3,556 3,767 4,295 4,355 4,341 4,288 4,234 4,148 Res Incremental Market Potential 0 0 0 0 0 Non Res Incremental Market Potential 1,258 2,589 3,115 3,372 3,907 3,981 4,014 4,001 3,983 3,928 C&S(If Claimed.Estimates not available after 2024) 704 611 441 395 388 375 328 287 251 220 Vernon Ten Year Cumulative Goals-Net(2018-2027) 1 Net Cumulative Markt Potential by Sector rr.,lrix> All Sectors r rterg y Potential(MWh)and%of Sales 4.w•a 4 SD,000 I .'}Ob .. r1 x, >gin.. 40000 runt � 10.0,91 0 Doti 2019 2019 2020 2021 2022 2023 2024 2025 2026 2027 aHry c,01,a41y4 M4.Mr 9044mi.lt aNnn Rer CI le/11.7,"M4rurt Pntenrlll t♦C&S 111 Cta,R 114.E114r14te.nut AvanALM,Aftr,20240 t Tutal Cvr,vtati.,Petor..41 a%AS yf Tuf.l 5414. 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 5,268 10,486 16,009 21,627 27,171 32,316 36,850 40,994 44,883 48,402 Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Cumulative Market Potential 2,652 5,643 9,039 12,797 16,538 19,981 23,051 25,936 28,742 31,330 C&S(If Claimed.Estimates not available after 2024) 2,616 4,843 6,970 8,830 10,633 12,335 13,799 15,058 16,141 17,072 Total Cumulative Potential as a%of Total Sales 0.44% 0.88% 1.34% 1.81% 2.26% 2.68% 3.04% 3.37% 3.69% 3.97% Res Cumulative Potential as a%of Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Non-Res Cumulative Potential as a%of Non-Res Sales 0.22% 0.47% 0.75% 1.06% 1.37% 1.65% 1.89% 2.13% 2.36% 2.57% 10 Year Demand Goals(Cumulative kW) t ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 1,961 4,457 7,402 10,728 14,629 18,599 22,570 26,535 30,484 34,379 Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Cumulative Market Potential 1,258 3,846 6,961 10,333 14,242 18,225 22,243 26,249 30,233 34,159 C&S(If Claimed.Estimates not available after 2024) 704 611 441 395 388 375 .328 287 251 220 NAVIGANT Victorville Ten Year Incremental Goals-Net(2018-2027) Net Incremental Market Potential by Sector 250 All Sectors Energy Potential(MWh)and%of Sales 0.30% 200. 0.25% 11, 150 0.20% v, 3 3 0.15%, 100 0.10% a so 0.05% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 NM Res Incremental Market Potentia I MO Non-Res Incremental Ma rket Potential #REF! ...Ill-Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 149 163 178 196 212 223 228 228 223 214 Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non Res Incremental Market Potential 149 163 178 196 212 223 228 228 223 214 Total Incremental Potential as a%of Total Sales 0.16% 0.17% 0.19% 0.21% 0.23% 0.24% 0.24% 0.24% 0.24% 0.23% Res Incremental Potential as a%of Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Non Res Incremental Potential as a%of Non Res Sales 0.16% 0.17% 0.19% 0.21% 0.23% 0.24% 0.24% 0.24% 0.24% 0.23% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 0.0154 0.0169 0.0184 0.0203 0.0219 0.0231 0.0237 0.0237 0.0231 0.0222 Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non Res Incremental Market Potential 0.0154 0.0169 0.0184 0.0203 0.0219 0.0231 0.0237 0.0237 0.0231 0.0222 Victorville Ten Year Cumulative Goals-Net(2018-2027) Net Cumulative Market Potential by Sector 2,500 All Sectors Energy Potential(MWh)a nd%of Sales 2.50% 2,000 2.00% a soo so%3 3 i 2 1,000 500 1.00% a' a` 0.50% ae 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Cumulative Market Potential Non-Res Cumulative Market Potential IIIIIII#REF! ..-Total Cumulative Potential as a%of Total Sales 10 Year Energy Goals(Cumulative Net MWh) ALL Sectors(Cumulative MW6) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 149 312 490 685 891 1,106 1,327 1,547 1,762 1,969 Res Cumulative Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Cumulative Market Potential 149. 312 490 685 891 1,106 1,327 1,547 1,762 1,969 Total Cumulative Potential as a%of Total Sales 0.16% 0.33% 0.52% 0.73% 0.95% 1.19% 1.42% 1.66% 1.89% 2.11% Res Cumulative Potential as a%of Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Non-Res Cumulative P tenti al as a%of Non-Res Sales 0.16% 0.33% 0.52% 0.73% 0.95% 1.19% 1.42% 1.66% 1.89% 2.11% 10 Year Demand Goals(Cumulative kW) ALL Sectors(Cumulative kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Cumulative Market Potential 0.015 0.032 0.051 0.071 0.092 0.115 0.138 0.161 0.183 0.204 Res Cumulative Market Potential 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Non-Res Cumulative Market Potential 0.015 0.032 0.051 0.071 0.092 0.115 0.138 0.161 0.183 0.204 NAVIGANT Appendix B. Utility Summary Memorandums Summary memorandums for the following utilities are provided: • Alameda Municipal Power • Anaheim, City of • Azusa, City of • Banning, City of • Biggs, City of • Burbank Water and Power • Colton Public Utilities • Corona, City of • Glendale Water and Power • Gridley Electric Utility • Healdsburg, City of • Imperial Irrigation District • Lassen Municipal Utility District • Lodi Electric Utility • Lompoc, City of • Los Angeles Department of Water& Power • Merced Irrigation District • Modesto Irrigation District • Moreno Valley Electric Utility • Needles, City of • Palo Alto, City of • Pasadena Water and Power • Pittsburg, City of • Plumas-Sierra Rural Electric Cooperative • Port of Oakland NAVIGANT • Rancho Cucamonga Municipal Utility • Redding Electric Utility • Riverside, City of • Roseville Electric • Sacramento Municipal Utility District • San Francisco Public Utilities Commission • Shasta Lake, City of • Silicon Valley Power • Trinity Public Utilities District • Truckee Donner Public Utilities District • Turlock Irrigation District • Ukiah, City of • Vernon, City of • Victorville, City of NAVIGANT To: Alameda Municipal Power From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Alameda Municipal Power with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Alameda service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 1. Base Case Run. This modeling run includes no changes or adjustments to Alameda's current portfolio of energy efficiency programs. 2. Final Run. This modeling run uses Alameda's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.18 Alameda's Final Run included the following adjustments to their Base Case Run: • Expanded measure list. Navigant modeled a number of measures—not currently offered in Alameda's portfolio—to provide a picture of potential savings should Alameda decide to expand their current programs. After review, Alameda added the following: - Residential clothes dryers - Residential clothes washer - Residential heat pump water heater - Residential LED fixtures and holiday lights - Expand the Energy Plus non-residential program Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 18 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT n r,a4a LUG0 1,400 0.40% 1.200 030% 1.000 iii ' 400 0.10% 100 0 0.00% 7018 2010 2020 2021 2077 2023 2074 7025 7076 7077 MI Res Incremental Market Potential MN Non Rea Incremental Market Potentia - -Total incremental Potential as a%ot total Sales Figure 3. Net Incremental Market Potential by Sector(MWh) and Percent of Sales-FINAL RUN Table 4-4. Inputs to Figure 1 10Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,459 1,614 832 823 818 858 818 818 756 740 Res Incremental Market Potential 305 296 170 168 169 209 175 185 131 135 Non Res Incremental Market Potential 1,154 1,317 661 655 649 649 643 633 626 605 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.43% 0.48% 0.25% 0.25% 0.25% 0.26% 0.24% 0.24% 0.22% 0,22% Res Incremental Potential as a%of Res Sales 0.25% 0.24% 0.14% 0.13% 0.14% 0.17% 0.14% 0.14% 0.10% 0.10% Non Res Incremental Potential as a%of Non-Res Sales 0.55% 0.63% 0.31% 0.31% 0.31% 0.31% 0.31% 0.30% 0.30% 0.29% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 242 367 158 151 147 149 147 149 146 143 Res Incremental Market Potential 26 24 15 9 8 10 8 10 6 8 Non Res Incremental Market Potential 216 343 143 142 139 139 139 139 139 136 C&S(If Claimed Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Alameda's results include: • A 2018-2027 average annual target of 0.28% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • Add new residential sector measures • Expand the non-residential Energy Plus Program NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Alameda begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.19 Rank Top Ten Measures•2018 2018-Energy 2018•Demand Energy%of Demand%of Savings(MWh) Savings(KW) Total Total 1 Com-Restaurant-LED downright screw-in lamp,1-3W,intrior Average 2 WalS200 53.6 117% 209, - ------- - 2 Street Lir hting-LED Streetll hls 172 0.0 1t8% 0 0% 3 Com-Retail-LED downright screw-in Ian's 1-3W,mtrior Avera_e 2 Watls 74 18.4 5.1% 7.2% 4 Corn-Office-Retro-comuissbning 70 0.0 4.8% 0.0% 5 Street Lighting_LED Streetlights with Advanced Controls 66 0.0 4.5% 0.0% 6 Res-Single Family-LED Indoor Screw-in Lamp Low Wattage_8 wattav_g_. 52 4.2 3.6% 1 6% 7 Corn-Ofice-LED fixture:33W,3500 lumens 47 19.3 3.2% 7.5% 8 Com-Ofice-Reduced Wattage T8 Lamp and Ballast Average Fixture Wattage 72.23 36 14.8 2.5% 5.8% 9 Res-Single Family-LED Indoor Screw-in Lag,-High Wattage-17 watavg. 36 , 2.9 2.5% 1.1% 10 Corn-Restaurant-LED downlight screw-in lane,4-20W,interior Average 11 Wats 35 9.5 2.4/ 3.7% Table 4-5. Top 10 Energy Saving Measures for 2017 Source:Navigant 2016 Table 4-6. Top 10 Energy Saving Measures for 2030 Rank Top Ten Measures•2027 2027•Energy 2027•Demand Energy%of Demand%of Savings(MWh) Savings(KW) Total Total 1 ComOfice-Retro-commissioning 68 0.0 9.1% 0.0% 2 Corn-Ofice-LED ixkire:33W,3500 lumens 66 26.8 8.9% 16.9% 3 Corn-Ofice WholeBlg-Com RET Level 2 40 16.9 5.4% 10.7% 4 Corn-Ofice-Occupancy Sensors 33 5.6 4.5% 3.6% 5 Res-Single Family_LED Indoor Screw-in Lamp-Low Wattage 8 watt avg. 24 1.9 3.2/ 1.2% 6 Com-Ofice WholeB -Com RET Level 1 24 9.4 12% 5.9% 7 Com-Retail-LED fixture:33W,3500lumens 22 5.6 3.0% 3.5% 8 Com-ALL Pump and Fan Variable Frequency Drive Controls1VFDs)_ 20 2.0 2.7% 1.2% 9 Res-Single Family-LED Indoor Specially Lamp_10 watt avg. 19 1.5 2.6% 1.0% 10 Res-Single Fairk:LED Indoor Refecbr Downlghl-12 wa8 avg. _ 18 1.4 2.5% 0.9% Source:Navigant 2016 Other Features Navigant worked with Alameda to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched 19 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Eipanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Alameda's current 10- year goals are about 114% of the goals established in the prior study. The primary reason for the higher goals is the addition of the new residential measures and the expansion of the non- residential Energy Plus Program. NAVIGANT To: Anaheim Public Utilities Department From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides the Anaheim Public Utilities Department with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Anaheim service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 3. Base Case Run. This modeling run includes no changes or adjustments to Anaheim's current portfolio of energy efficiency programs. 4. Final Run. This modeling run uses Anaheim's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.20 Anaheim chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 20 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the gross incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 4. Gross Incremental Market Potential by Sector(MWh) and Percent of Sales-FINAL RUN 30.000 1.40% 000 1.20% :1? 0.00X71.00% 2,+n0.80%5.5,000 t7 515 Oleo% c a 10.000 b 0.40% v: 5,000 0.20% 0 0,00% 2018 2019 2020 7021 2077 7029 2024 2025 2026 2027 lank Total Incremental Potential as a%of Total Sales =NNon'Pes lv rnnental Market Potential SINISC&S Of Claimed,Estimates not available after 2024) tTotal Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 28,098 28,104 26,801 26,140 25,830 25,071 23,855 23,053 21,812 20,458 Res Incremental Market Potential 6,232 6,368 5,098 5,218 5,223 5,303 4,775 5,028 4,904. 4,830 Non Res Incremental Market Potential 12,525 12,870 13,357 13,870 14,254 14,274 14,044 13,409 12,677 11,749 C&S(If Claimed.Estimates not available after 2024) 9,342 8,866 8,345 7,051 6,353 5,494 5,036 4,616 4,231 3,878. Total Incremental Potential as a%of Total Sales 1.15% 1.15% 1.09% 1.06% 1.04% 1.00% 0.95% 0.91% 0.86% 0.80% Res Incremental Potential as a%of Res Sales 0.99% 1.01% 0.81% 0.82% 0.82% 0.83% 0.74% 0.78% 0.75% 0.74% Non-Res Incremental Potential as a%of Non-Res Sales 0.68% 0.70% 0.72% 0.75% 0.76% 0.76% 0.75% 0.71% 0.67% 0.62% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 6,248 6,342 6,376 6,540. 6,757 6,491 6,514 6,405 6,207 5,951 Res Incremental Market Potential 1,143 1,181 1,213 1,233 1,250 1,256 1,293 1,285 1,310 1,327 Non Res Incremental Market Potential 2,610 2,751 2,997 3,327 3,640 3,491 3,577 3,571 3,438 3,247 C&S(If Claimed.Estimates not available after 2024) 2,494 2,411 2,166 1,980 1,866 1,744 1,644 1,549 1,460 1,376 Table 4-7. Inputs to Figure 1 Source:Navigant 2016 At a glance, Anaheim's results include: • A 2018-2027 average annual target of 1.0% of forecasted retail sales • Gross savings targets, as it did in 2012. • Only codes and standards (C&S)that are currently in place today, and not future C&S such as updates to Title 24 • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Anaheim begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.21 Table 4-8. Top 10 Energy Saving Measures for 2017 1 Com-Office-Retro-commissioning 1,360 0.0 8.4% 0.0% 2 Industrial Machinery-Efficient Lighting Equipment 645 73.2 4.0% 1.9% 3 Res-Single Family-LED Indoor Screw-in Lamp-Low Wattage-8 watt 603 52.4 3.7% 1.4% avg. 4 Electronics-Efficient Lighting Equipment 521 65.3 3.2% 1.7% 5 Com-Other-Thermostat Replacement 444 0.0 2.7% 0.0% 6 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 403 35.0 2.5% 0.9% 7 Com-Grocery-Retro-commissioning 398 0.0 2.4% 0.0% 8 Other Industrial-Efficient Lighting Equipment 389 37.8 2.4% 1.0% 9 Res-Multi Family-LED Indoor Screw-in Lamp-Low Wattage-8 watt avg. 381 33.1 2.3% 0.9% 10 Com-Other-Comprehensive Rooftop Unit Quality Maintenance(AC 380 184.0 2.3% 4.9% Tune-up) y Source:Navigant 2016 21 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-9. Top 10 Energy Saving Measures for 2030 1 Com-Office-Retro-commissioning 695 0.0 7.2% 0.0% 2 Res-Single Family-Refrigerator Recycling 551 110.8 5.7% 2.9% 3 Res-Single Family-Shade Tree 378 0.0 3.9% 0.0% 4 Industrial Machinery-Efficient Lighting Equipment 355 40.3 3.7% 1.1% 5 Electronics-Efficient Lighting Equipment 287 35.9 3.0% 0.9% 6 Corn-Other-Comprehensive Rooftop Unit Quality Maintenance(AC 259 125.6 2.7% ° Tune-up) 3.3/° 7 Com-Other-Demand Controlled Ventilation 246 14.7 2.5% 0.4% 8 Corn-Office-LED fixture:33W,3500 lumens 219 85.6 2.3% 2.2% 9 Other Industrial-Efficient Lighting Equipment 217 21.1 2.2% 0.6% 10 Corn-Office-Window Film 184 103.9 1.9% 2.7% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Anaheim to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. NAVIGANT The years 2018-2023 overlap between the two 10-year study periods. Anaheim's current 10- year goals are about 108% of the goals established in the prior study. The primary reason is the Codes & Standards claim. Anaheim claims gross savings, as it also did in 2012. NAVIGANT To: Azusa Light&Water From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Azusa Light &Water with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Azusa service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 5. Base Case Run. This modeling run includes no changes or adjustments to Azusa's current portfolio of energy efficiency programs. 6. Final Run. This modeling run uses Azusa's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.22 Azusa chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 22 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 5. Net Incremental Market Potential by Sector(MWh) and Percent of Sales—FINAL RUN 3,5!X1 1 40% 3.000 l.I090 2.500 100% kl 2.000 0.80% V 1,50C1 0.60% c 4 11, 1.000 04090 SW 0.20% 0 0.00% /0185 /019 1010 11)11 1011 1(!13 10)4 11)15 1011, 101 1111•112E9 Incremental Market Potential NM Non•Res Incremental Market Potential =MOSS(If Claimed.Estimates not available after 2024) --Total Incremental Potential as a 1,of Total Saks 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 2,813 3,089 2,943 2,824 2,769 2,682 2,565 2,512 2,410 2,257 Res Incremental Market Potential 358 373 397 424 449 470 485 495 496 470 Non-Res Incremental Market Potential 1,242 1,233 1,263 1,281 1,272 1,217 1,187 1,162 1,117 1,046 C&S(If Claimed.Estimates not available after 2024) 1,213 1,482 1,283 1,119 1,047 995 892 856 797 741 Total Incremental Potential as a%of Total Sales 1.07% 1.17% 1.11% 1.07% 1.04% 1.00% 0.96% 0.93% 0.90% 0.84% Res Incremental Potential as a%of Res Sales 3.06% 3.18% 3.38% 3.60% 3.80% 3.96% 4.07% 4.13% 4.15% 3.93% Non Res Incremental Potential as a%of Non-Res Sales 0.49% 0.49% 0.50% 0.50% 0.50% 0.48% 0.46% 0.45% 0.43% 0.41% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 2,034 2,144 2,157 2,203 2,238 1,917 1,937 1,959 1,974 1,979 Res Incremental Market Potential 7 8 8 9 9 10 10 10 10 10 Non Res Incremental Market Potential 1,794 1,831 1,877 1,927 1,977 1,680 1,716 1,744 1,766 1,783 C&S(If Claimed.Estimates not available after 2024) 232 306 272 267 251 228 212 206 197 187 Table 4-10. Inputs to Figure 1 Source:Navigant 2016 At a glance, Azusa's results include: • A 2018-2027 average annual target of 1.06% of forecasted retail sales • Net savings targets • Only codes and standards (C&S)that are currently in place today, and not future C&S such as updates to Title 24 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Azusa begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.23 Table 4-11. Top 10 Energy Saving Measures for 2017 1 Res-Multi Family-CEE Tier Ill Refrigerator(from 30$to 35%more efficient) 126 0.0 6.8% 0.0% 2 Corn-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 97 24.6 5.2% 1.2% Watts 3 Res-Single Family-CEE Tier Ill Refrigerator(from 30$to 35%more efficient) 93 0.0 5.0% 0.0% 4 Corn-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 75 18.6 4.1% 0.9% 5 Com-Grocery-LED downlight,screw-in lamp,1-3W,interior Average 2 Watts 57 10.1 3.1% 0.5% 6 Res-Multi Family-CEE Tier II Refrigerator 51 0.0 2.8% 0.0% 7 Corn-Retail-LED T8 Tube Replacement Average Fixture Wattage 59.65 40 9.7 2.1% 0.5% 8 Res-Multi Family-ENERGY STAR Refrigerator 38 0.0 2.1% 0.0% 9 Res-Single Family-CEE Tier II Refrigerator 38 0.0 2.0% 0.0% 10 Corn-Office-LED T8 Tube Replacement Average Fixture Wattage 59.65 37 15.0 2.0% 0.7% Source:Navigant 2016 23 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-12. Top 10 Energy Saving Measures for 2030 1 Res-Multi Family-CEE Tier II Refrigerator 48 0.0 6.1% 0.0% 2 Res-Single Family-Shade Tree 35 0.0 4.5% 0.0% 3 Res-Single Family-CEE Tier II Refrigerator 35 0.0 4.5% 0.0% 4 Res-Multi Family-ENERGY STAR Refrigerator 35 0.0 4.5% 0.0% 5 Corn-Education-LED fixture:33W,3500 lumens 30 4.0 3.9% 0.6% 6 Corn-Office-LED fixture: 33W,3500 lumens 30 12.0 3.9% 1.8% 7 Food-Efficient MachDr Equipment 27 1.8 3.5% 0.3% 8 Res-Single Family-ENERGY STAR Refrigerator 25 0.0 3.3% 0.0% 9 Com-Education-Commercial SEER-rated Packaged Air Conditioners,SEER= 24 17.7 3.10/o 2.70/o 15(EER=12.9) 10 Food-Efficient Lighting Equipment 22 2.2 2.8% 0.3% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Azusa to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. NAVIGANT The years 2018-2023 overlap between the two 10-year study periods. Azusa's current 10-year goals are about 133% of the goals established in the prior study. The reason for their targets to now be higher is their claim of savings from C&S. NAVIGANT To: The City of Banning From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides The City of Banning utility with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Banning service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 7. Base Case Run. This modeling run includes no changes or adjustments to Banning's current portfolio of energy efficiency programs. 8. Final Run. This modeling run uses Banning's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.24 Banning's Final Run included the following adjustments to their Base Case Run: • Expanded measure list. Navigant modeled a number of measures—not currently offered in Banning's portfolio—to provide a picture of potential savings should Banning decide to expand their current programs. Banning chose to include only a sub-set of this expanded measure list, detailed in the Output Viewer. The team used various sources and studies throughout California and the nation to inform this expanded measure list. • Not claiming Codes and Standards savings. Banning will not be claiming savings from codes and standards for this study. Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 24 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT 5(X) 0.40% 500 11_1. 035% - 0.30% 0.25% r 300 0.21796 0.t5% < 100 M 0.IQ% 100 0% 0115% 0 1111. 0.0 2018 2019 2020 2021 2022 2023 2024 2025 2025 2021 MIN Res Incremental Market Potential Me Non Res Inrreme ntai Market Potential ..Total Incremental Potential as a"at Total Sales Figure 6. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential328 367 399 445 490 502 492 463 428 404 ,__.. Res Incremental Market Potential 163 179 183 196 213 228 239 247 253 259 _.. _.___.. _.. _ 1111_... _.._._. _... _... Non-Res Incremental Market Potential 165 188 216 249 277 274 252 216 175 144 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.23% 0.26% 0.28% 0.31% 0.34% 0.34% 0.33% 0.31% 0.29% 0.26% Res Incremental Potential as a%of Res Sales 0.24% 0.27% 0.27% 0.29% 0.31% 0.33% 0.35% 0.36% 0.36% 0.37% __.._. __... 1111_. ___.._. 1_111 Non-Res Incremental Potential as a%of Non-Res Sales 0.21% 0.24% 0.28% 0.32% 0.35% 0.34% 0.31% 0.26% 0.21% 0.17% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 84 92 100 110 122 126 123 115 108 106 Res Incremental Market Potential 55 58 60 64 69 74 77 79 81 82 Non-Res Incremental Market Potential 29 34 40 47 53 52 46 36 28. 24 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 ___v__....._.. Table 4-13. Inputs to Figure 1 Source:Navigant 2016 • At a glance, Banning's results include: • A 2018-2027 average annual target of 0.3% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Banning begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.25 Table 4-14. Top 10 Energy Saving Measures for 2017 1 Other Industrial-Efficient Lighting Equipment 38 3.7 15.7% 4.4% 2 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 32 22.5 13.1% 26.9% 3 Res-Single Family-Residential Solar Screen 22 15.8 9.2% 18.9% 4 Res-Single Family-Refrigerator Recycling 15 2.9 6.1% 3.5% Com-Restaurant-LED downlight,screw-in lamp,1-3W,interior Average 2 5 Watts 12 3.0 5.1% 3.6% Corn-Grocery-LED downlight,screw-in lamp, 1-3W,interior Average 2 6 Watts 11 1.9 4.7% 2.3% 7 Com-Office-Bi-Level Lighting Fixture-Stairwells,Hallways,and Garages 6 0.1 2.5% 0.1% Res-Single Family-CEE Tier III Refrigerator(from 30$to 35%more 8 efficient) 5 0.0 2.1% 0.0% 9 Com-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 4 1.0 1.8% 1.2% 10 Com-Other-Bi-Level Lighting Fixture-Stairwells,Hallways,and Garages 4 0.0 1.6% 0.1% Source:Navigant 2016 • 25 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-15. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-Solar Attic Fan(1,000 CFM) 63 20.2 14.9% 16.6% 2 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 41 29.1 9.7% 23.9% 3 Other Industrial-Efficient Lighting Equipment 32 3.1 7.5% 2.5% 4 Res-Single Family-Shade Tree 31 0.0 7.4% 0.0% 5 Res-Single Family-Residential Solar Screen 29 20.5 6.8% 16.8% 6 Res-Single Family-Refrigerator Recycling 19 3.9 4.6% 3.2% 7 Res-Single Family-Low Income 19 4.5 4.5% 3.7% 8 Com-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 17 4.3 4.1% 3.5% 9 Res-Single Family-Wall Insulation(R-13) 17 0.0 4.1% 0.0% 10 Com-Grocery-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 17 2.9 4.1% 2.4% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Vernon to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include CSS Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Banning's current 10-year goals are about 85% of the goals established in the prior study even though it did add new measures to its portfolio. The primary reason is model calibration. In the earlier version, the calibration target was set above actual historical achievements. The calibration target for the current model reflects actual levels of program achievement. NAVIGANT To: The City of Biggs From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides the City of Biggs with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Biggs service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 9. Base Case Run. This modeling run includes no changes or adjustments to Biggs's current portfolio of energy efficiency programs. 10. Final Run. This modeling run uses Biggs's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.26 Biggs chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 26 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 7. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 9 0.014. a 0.06% 0.05°: 6 c S.' L 5 0.04% 3 c7 't 0.03% a -113 0.02% a 2 lir""fllIll"""ll"""tl 0.01% 0 0E709. 7018 2010 2020 2071 2072 2023 2674 7075 7026 2027 EMS Res Incremental Market Potential nil Non Res incremental Market Potential -e-Total Incremental Potential as a%ot Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 7 7 7 8 8 8 8 8 8 8 Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non Res Incremental Market Potential 6 7 7 7 8 8 8 8 8 8 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0. 0 0 0 a..�..�� 0 0 Total Incremental Potential as a%of Total Sales 0.05% 0.05% 0.05% 0.05% 0.05% 0.06% 0.06% 0.06% 0.06% 0.06% Res Incremental Potential as a%of Res Sales 0.01% 0.01% 0.01% 0.01% 0.01%.. 0.01% 0.01% 0.01% 0.01% 0.01% Non-Res Incremental Potential as a%of Non-Res Sales 0.07% 0.07% 0.07% 0.07% 0.08% 0.08% 0.08% 0.08% 0.08% 0.08% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1 1 1 1 1 1 1 1 1 1 Res Incremental Market Potential 0 0 0 0 0 0 0 0 1 1 Non-Res Incremental Market Potential 1 1 1 1 1 1 1 1 1 1 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-16. Inputs to Figure 1 Source:Navigant 2016 At a glance, Biggs's results include: • A 2018-2027 average annual target of 0.05% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Biggs begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.27 Table 4-17. Top 10 Energy Saving Measures for 2017 1 Other Industrial-Efficient Lighting Equipment 7.157 0.70 88.7% 4.8% 2 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 0.381 0.48 4.7% 3.4% 3 Res-Multi Family-Reflective Window Film(reduces SHGC to 0.39) 0.039 0.05 0.5% 0.3% 4 Corn-Other-Reduced Wattage T8 Lamp and Ballast Average Fixture 0.015 0.01 0.2% 0.1% Wattage 72.23 5 Corn-New-Reduced Wattage T8 Lamp and Ballast Average Fixture 0.004 0.00 0.0% 0.0% Wattage 72.23 6 Corn-Data Center-Server Equipment Upgrades 0.001 0.89 0.0% 6.2% 7 Com-Data Center-Server Monitoring&Controls 0.001 0.88 0.0% 6.2% 8 Corn-Data Center-Power Distribution Monitoring&Controls 0.001 0.88 0.0% 6.1% 9 Com-Data Center-Power Distribution Equipment Upgrades 0.001 0.88 0.0% 6.1% 10 Corn-Data Center-Lighting Monitoring&Controls 0.001 0.00 0.0% 0.0% Source:Navigant 2016 27 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-18. Top 10 Energy Saving Measures for 2030 1 Other Industrial-Efficient Lighting Equipment 9.353 0.91 90.0% 6.2% 2 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 0.493 0.62 4.7% 4.2% 3 Res-Multi Family-Reflective Window Film(reduces SHGC to 0.39) 0.051 0.06 0.5% 0.4% 4 Corn-Other-Reduced Wattage T8 Lamp and Ballast Average Fixture 0.020 0.01 0.2% 0.1% Wattage 72.23 5 Com-Other-De-Lamp Fluorescent Fixture Average Lamp Wattage 28W 0.001 0.00 0.0% 0.0% 6 Corn-Data Center-Server Equipment Upgrades 0.001 0.89 0.0% 6.0% 7 Corn-Data Center-Server Monitoring&Controls 0.001 0.88 0.0% 6.0% 8 Com-Data Center-Power Distribution Monitoring&Controls 0.001 0.88 0.0% 6.0% 9 Com-Data Center-Power Distribution Equipment Upgrades 0.001 0.88 0.0% 6.0% 10 Corn-Data Center-Lighting Monitoring&Controls 0.001 0.00 0.0% 0.0% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Biggs to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Biggs's current 10-year goals are about 17% of the goals established in the prior study. There are two primary reasons for the lower goals: • Biggs is a very small utility and since the 2012 study, the load forecast has dropped nearly 20%, reflecting the difficult economic conditions in Biggs. • The 2016 calibration targets are much lower than 2012, reflecting the difficult economic conditions. NAVIGANT To: Burbank Water and Power From: Navigant Consulting, Inc. Date: February 6, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Burbank Water and Power with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Burbank service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 11. Base Case Run. This modeling run includes no changes or adjustments to Burbank's current portfolio of energy efficiency programs. 12. Final Run. This modeling run uses Burbank's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.28 Burbank chose to call their Base Case Run as Final and made no adjustments to modeling scenarios, except to claim gross, rather than net savings. Figure 1 shows the gross incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 8. Gross Incremental Market Potential by Sector(MWh)and Percent of Sales—FINAL RUN Incremental Gross Market Potential by Sector 16.000 All Sectors Energy Potential(MWh)and%of Sales 1.20% 1u 1. 60. 30.r.�096a`0.40%60.20%0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res Incremental Market Potential MN Non-Res Incremental Market Potential MB C&S(If Claimed) —di—Total Incremental Potential as a 96 of Total Sales NAVIGANT Table 4-19. Inputs to Figure 1 ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 10,874 11,207 11,385 12,052 12,818 13,072 13,516 13,668 13,251 12,711 Res Incremental Market Potential 4,021 4,194 4,017 4,176 4,338 4,479 4,492 4,551 4,541 4,523 Non Res Incremental Market Potential 6,853 7,013 7,368 7,876 8,481 8,593 9,023 9,117 8,710 8,188 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.94% 0.96% 0.96% 1.01% 1.06% 1.07% 1.10% 1.10% 1.06% 0.99% Res Incremental Potential as a%of Res Sales 1.41% 1.46% 1.38% 1.42% 1.46% 1.49% 1.48% 1.49% 1.47% 1.45% Non Res Incremental Potential as a%of Non-Res Sales 0.77% 0.78% 0.81% 0.86% 0.91% 0.92% 0.95% 0.95% 0.90% 0.84% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 4,150 4,331 4,504 4,716 4,944 4,739 4,951 5,063 5,028 4,895 Res Incremental Market Potential 1107 1,175 1,222 1,300 1,380 1,452 1,506 1,547 1,569 1,546 Non-Res Incremental Market Potential 3,043 3,155 3,282 3,41.6 3,564 3,286 3,445 3,516 3,459 3,349 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Burbank's results include: • A 2018-2027 average annual target of 1.03% of forecasted retail sales • Gross savings targets • No claim of savings from codes and standards (C&S) Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Burbank begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.29 Table 4-20. Top 10 Energy Saving Measures for 2017 1 Com-Other-Commercial SEER-rated Packaged Air Conditioners,SEER=15 511 295.4 6.1% 7.2% (EER=12.9) 2 Street Lighting-LED Streetlights 353 0.0 4.2% 0.0% 3 Com-Office-Commercial SEER-rated Packaged Air Conditioners,SEER=15 326 193.6 3.9% 4.7% (EER=12.9) 4 Corn-Other-Commercial SEER-rated split Air Conditioners,SEER=15(EER=12.8) 239 153.2 2.9% 3.7% 29 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT 5 Com-Other-Commercial Package EER Rated dxAC-Average EER=11.41 220 77.0 2.6% 1.9% 6 Corn-Office-LED fixture:33W,3500 lumens 214 85.9 2.6% 2.1% 7 Com-Other-Thermostat Replacement 211 0.0 2.5% • 0.0% 8 Street Lighting-LED Streetlights with Advanced Controls 207 0.0 2.5% 0.0% 9 Corn-Other-Pkg HP SEER=15.0(<65 kbtuh),EER=12.0,HSPF=8.50,COP=3.74 163 99.5 2.0% 2.4% 10 Corn-Office-Commercial SEER-rated split Air Conditioners,SEER=15(EER=12.8) 159 111.2 1.9% 2.7% Source:Navigant 2016 Table 4-21. Top 10 Energy Saving Measures for 2030 1 Com-Other-Commercial SEER-rated Packaged Air Conditioners,SEER=15 504 291.6 5.90/0 6.40/0 (EER=12.9) . 2 Corn-Office-LED fixture:33W,3500 lumens 329 132.3 3.8% 2.9% 3 Com-Office-Commercial SEER-rated Packaged Air Conditioners,SEER=15 322 191.1 3.80/o 4.2% (EER=12.9) 4 Corn-Other-Commercial SEER-rated split Air Conditioners,SEER=15(EER=12.8) 236 151.3 2.7% 3.3% 5 Com-Other-Commercial Package EER Rated dxAC-Average EER=11.41 217 76.0 2.5% 1.7% 6 Com-New-LED fixture: 33W,3500 lumens 184 40.1 2.1% 0.9% 7 Corn-Restaurant-LED downlight,screw-in lamp,1-3W,interior Average 2 Watts 169 43.1 2.0% 0.9% 8 Corn-New-Electronically Commutated(EC)Motor w/Fan Cycling Controls for Cold 163 18.6 1.9% 0.4% Storage Evaporator Fans 9 Com-Office-Commercial SEER-rated split Air Conditioners,SEER=15(EER=12.8) 157 109.8 1.8% 2.4% 10 Com-Other-LED fixture:33W,3500 lumens 156 114.9 1.8% 2.5% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Burbank to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Burbank's current 10- year goals are about 114% of the goals established in the prior study. The average savings goal between the 2012 and 2016 study are very similar. However, the forecast of sales in 2016 is about 10% lower than the forecast of sales in 2012. Additionally, Burbank is claiming gross savings targets in 2016 while they claimed net in 2012. NAVIGANT To: Colton Electric Utility From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Colton Electric Utility with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Colton service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 13. Base Case Run. This modeling run includes no changes or adjustments to Colton's current portfolio of energy efficiency programs. 14. Final Run. This modeling run uses Colton's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.3o Colton's Final Run included the following adjustments to their Base Case Run: • Expanded measure list. Navigant modeled a number of measures—not currently offered in Colton's portfolio—to provide a picture of potential savings should Colton decide to expand their current programs. The modeling team used various sources and studies throughout California and the nation to inform this expanded measure list. • Increased promotional costs by 50%. Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 3°Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 9. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 4.500 1.40% 4.000 1.II 4.500 T 3000 150,'1 O.7Dnn o.150(1o 1.000 SW 7018 7019 2020 1071 2022 2023 7024 2025 7026 2027 fIIMM Total Incremental Potential as a%of Total Sales Non-Nes Incremental Market Potential IIIIIII/C&S(If Clainmd.Estimates not available after 2024) tTotal Inuernental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 4,252 4,137 4,163 4,108 4,201 4,121 3,852 3,462 3,133 2,852 Res Incremental Market Potential 149 166 153 170 194 225 264 291 293 292 Non-Res Incremental Market Potential 2,457 2,429 2,541 2,617 2,734 2,710 2,481 2,138 1,877 1,661 C&S(If Claimed.Estimates not available after 2024) 1,646 1,542 1,469 1,322 1,272 1,186 1,106 1,032 964 899 Total Incremental Potential as a%of Total Sales 1.16% 1.13% 1.13% 1.11% 1.13% 1.11% 1.03% 0.93% 0.84% 0.76% Res Incremental Potential as a%of Res Sales 1.07% 1.19% 1.10% 1.21% 1.38% 1.60% 1.87% 2.06% 2.07% 2.07% Non-Res Incremental Potential as a%of Non-Res Sales 0.69% 0.69% 0.71% 0.73% 0.76% 0.75% 0.69% 0.59% 0.52% 0.46% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,013 1,007 1,010 1,012 1,028 973 944 904 870 835 Res Incremental Market Potential 28 30 30 33 37 41 46 51 53 54 Non-Res Incremental Market Potential 597 612 643 666 686 639 621 591 568. 545 C&S(If Claimed.Estimates not available after 2024) 388 365 336 313 305 293 277 262 249 235 Table 4-22. Inputs to Figure 1 Source:Navigant 2016 At a glance, Colton's results include: • A 2018-2027 average annual target of 1.03% of forecasted retail sales • Net savings targets • Only codes and standards (C&S)that are currently in place today, and not future C&S such as updates to Title 24 • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Colton begins to allocate program dollars in new directions. Table 3 shows the top 10 energy saving measures for the first year of the forecast period and Table 4 shows the top 10 measures for year 2030 to use as a comparison.31 Table 4-23. Top 10 Energy Saving Measures for 2017 1 Com-ALL-Pump and Fan Variable Frequency Drive Controls 349 34.6 10.70/o 4.4% (VFDs) 2 Food-Efficient Lighting Equipment 234 24.1 7.2% 3.1% 3 Other Industrial-Efficient Lighting Equipment 127 12.3 3.9% 1.6% 4 Food-Efficient ProcRefrig O&M 114 9.6 3.5% 1.2% 5 Food-Efficient MachDr Equipment 111 7.3 3.4% 0.9% 6 Food-Efficient MachDr O&M 95 9.0 2.9% 1.2% 7 Food-Efficient HVAC O&M 91 6.2 2.8% 0.8% 8 Lumber&Furniture-Efficient Lighting Equipment 71 8.8 2.2% 1.1% 9 Com-Retail-LED fixture:33W,3500 lumens 65 16.0 2.0% 2.1% 10 Other Industrial-Efficient MachDr Equipment 57 8.7 1.7% 1.1% Source:Navigant 2016 31 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-24. Top 10 Energy Saving Measures for 2030 1 Food-Efficient MachDr O&M 95 9.0 5.2% 1.5% 2 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 75 6.0 4.1% 1.0% 3 Com-Retail-Electronically Commutated(EC)Motor w/Fan Cycling 57 6.5 3.1% 1.1% Controls for Cold Storage Evaporator Fans 4 Food-Efficient MachDr Equipment 54 3.5 2.9% 0.6% 5 Com-Health-WholeBlg-Com RET Level 2 53 12.0 2.9% 2.1% 6 Com-Health-Demand Controlled Ventilation 51 1.6 2.8% 0.3% 7 Res-Single Family-Shade Tree 44 0.0 2.4% 0.0% 8 Corn-Retail-WholeBlg-Com RET Level 2 44 13.3 2.4% 2.3% 9 Com-Other-WholeBlg-Com RET Level 2 43 17.8 2.3% 3.0% 10 Com-Grocery-Electronically Commutated(EC)Motor w/Fan Cycling 37 4.2 2.00/0 0.7% Controls for Cold Storage Evaporator Fans Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Colton to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018— 2023 overlap between the two 10-year study periods. Colton's current 10-year goals are about 177% of the goals established in the prior study. There are several reasons for these higher goals: • Claiming savings from Codes & Standards • Adding new residential, commercial and industrial sector measures to their programs • Increasing administrative/promotional activities by 50% beginning in 2016 • The current calibration target is higher than the 2012 calibration target. NAVIGANT To: Corona Department of Water and Power From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Corona Department of Water and Power with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Corona service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 15. Base Case Run. This modeling run includes no changes or adjustments to Corona's current portfolio of energy efficiency programs. 16. Final Run. This modeling run uses Corona's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.32 Corona chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 32 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 10. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 10 0.01% 9 0.01% R 0.01% 7 lg vR, 6 OAU% S J 55. m 4 a O 3 OM% } 7 0.00% 1 0 O.CD% 7019 7019 7070 7071 7027 7073 2074 7075 7076 7027 Res Incremental Market Potential MI Non Res Incremental Market Potential -Total incremental Potential as a%ol Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 9 9 7 6 5 5 4 4 3 3 Res Incremental Market Potential 9 9 7 6 5 5 4 4 3 3 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.01% 0.01% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%. 0.00% Res Incremental Potential as a%of Res Sales 0.22% 0.23% 0.18% 0.16% 0.13% 0.11% 0.10% 0.09% 0.08% 0.07% Non-Res Incremental Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1 1 1 1 1 1 1 1 1 0 Res Incremental Market Potential 1 1 1 1 1 1 1 1 1 0 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-25. Inputs to Figure 1 Source:Navigant 2016 At a glance, Corona's results include: • A 2018-2027 average annual target of 0.004% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Corona begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.33 Table 4-26. Top 10 Energy Saving Measures for 2017 1 Res-MF New-Heat Pump Water Heater(>2.0 EF-50 Gallon) 10 2.0 41.9% 12.7% 2 Res-MF New-CEE Tier III Clothes Washer,Elec DHW,Electric or Gas Dryer(2.4 3 0.0 12.50/0 0.0% MEF to 2.87 MEF) 3 Res-MF New-CEE Tier II Clothes Washer,Elec DHW,Electric or Gas Dryer(2.2 3 0.0 11.4% 0.0% MEF) 4 Res-MF New-ENERGY STAR Clothes Washer.Elec DHW,Electric or Gas Dryer 2 0.0 10.3% 0.00/0 (2.0 MEF) 5 Res-MF New-High Efficiency Electric Storage Water Heater(0.93 EF-50 gallon) 2 0.2 7.2% 1.0% 6 Res-Single Family-Low Flow Showerhead(Electric DHW) 1 0.2 3.5% 1.1% 7 Res-Single Family-Bathroom Faucet Aerators(0.5-1.0 GPM Electric DHW) 1 0.2 3.3% 1.0% 8 Res-SF New-Heat Pump Water Heater(>2.0 EF-50 Gallon) 0 0.1 1.2% 0.4% 9 Res-SF New-CEE Tier Ill Clothes Washer,Elec DHW,Electric or Gas Dryer(2.4 0 0.0 1.1% 0.0% MEF to 2.87 MEF) 10 Res-SF New-CEE Tier II Clothes Washer,Elec DHW,Electric or Gas Dryer(2.2 0 0.0 1.0% 0.0% MEF) Source:Navigant 2016 33 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-27. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-Low Flow Showerhead(Electric DHW) 1 0.1 20.1% 1.1% 2 Res-Single Family-Bathroom Faucet Aerators(0.5-1.0 GPM Electric DHW) 1 0.1 19.5% 1.1% 3 Res-MF New-Heat Pump Water Heater(>2.0 EF-50 Gallon) 1 0.1 18.9% 1.0% 4 Res-MF New-CEE Tier Ill Clothes Washer,Elec DHW,Electric or Gas Dryer(2.4 MEF 0 0.0 4.9% 0.0% to 2.87 MEF) 5 Res-MF New-CEE Tier II Clothes Washer,Elec DHW,Electric or Gas Dryer(2.2 MEF) 0 0.0 4.0% , 0.0% 6 Res-Multi Family-Low Flow Showerhead(Electric DHW) 0 0.0 3.8% 0.2% MEF)Res-MF New-ENERGY STAR Clothes Washer,Elec DHW,Electric or Gas Dryer(2.0 0 0.0 3.6% 0.0% 8 Res-MF New-High Efficiency Electric Storage Water Heater(0.93 EF-50 gallon) 0 0.0 3.2% 0.1% 9 Res-Multi Family-Bathroom Faucet Aerators(0.5-1.0 GPM Electric DHW) 0 0.0 3.0% 0.2% 10 Res-Single Family-Kitchen Faucet Aerators(1.5 GPM Electric DHW) 0 0.0 2.9% 0.2% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Corona to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Corona's current 10-year goals are only about 1% of the goals established in the prior study. There primary reason is much lower calibration targets reflecting the difficult economic conditions in Corona. NAVIGANT To: Glendale Water&Power From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Glendale Water& Power with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Glendale service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 17. Base Case Run. This modeling run includes no changes or adjustments to Glendale's current portfolio of energy efficiency programs. 18. Final Run. This modeling run uses Glendale's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.34 Glendale chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 34 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 11. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 16.000 1.60% 14.000 1.40% 12.0(X) 1.20% u 10,000 1.00% sn V 8.000 080% t. 2 6.000 0.60% o 4,000 0.40% 2.000 0.20% 0 0.00% 1018 2019 2020 2021 2022 2023 2014 2025 2026 2021 MEI Ret Incremental Market Potential NM Non Res Incremental Market Potential 11=I CRS(II Claimed) ....Total Incremental Potential as a%nt Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 14,801 14,723 14,634 14,160 13,998 13,528 12,447 11,534 10,682 9,966 Res Incremental Market Potential 3,778 3,809 3,841 3,878 3,928 3,957 3,967 3,986 3,990 3,993 Non-Res Incremental Market Potential 4,952 5,000 5,228 5,507 5,727 5,797 4,927 4,202 3,543 3,007 C&S(If Claimed) 6,070 5,914 5,565 4,774 4,343 3,774 3,553 3,346 3,150 2,966 Total Incremental Potential as a%of Total Sales 1.34% 1.33% 1.31% 1.26% 1.24% 1.19% 1.09% 1.01% 0.93% 0.87% Res Incremental Potential as a%of Res Sales 0.95% 0.96% 0.96% 0.96% 0.97% 0.97% 0.97% 0.97% 0.97% 0.97% Non-Res Incremental Potential as a%of Non-Res Sales 0.69% 0.70% 0.73% 0.76% 0.78% 0.79% 0.67% 0.57% 0.48% 0.41% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 5,392 5,640 6,125 6,831 7,549 6,891 6,832 1,108,974 1,065,294 1,023,445 Res Incremental Market Potential 156 162 167 170 170 170 169 168 167 166 Non-Res Incremental Market Potential 3,694 3,953 4,497 5,310 6,097 5,522 5,513 5,428 5,307 5,186 C&S(If Claimed) 1,542 1,526 1,461 1,351 1,282 1,200 1,149 1,103,378 1,059,820 1,018,093 Table 4-28. Inputs to Figure 1 Source:Navigant 2016 At a glance, Glendale's results include: • A 2018-2027 average annual target of 1.16% of forecasted retail sales • Net savings targets • Only codes and standards (C&S)that are currently in place today, and not future C&S such as updates to Title 24 NAVIGANT • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline"function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Glendale begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.35 Table 4-29. Top 10 Energy Saving Measures for 2017 1 Food-Efficient MachDr Equipment 356 23.3 6.9% 0.6% 2 Corn-Retail-LED fixture:33W,3500 lumens 340 83.7 6.6% 2.2% 3 Food-Efficient Lighting Equipment 257 26.5 5.0% 0.7% 4 Com-Education-LED fixture:33W,3500 lumens 198 26.0 3.8% 0.7% 5 Corn-Office-LED fixture:33W,3500 lumens 195 78.2 3.8% 2.0% 6 Com-Grocery-LED downlight,screw-in lamp, 1-3W,interior Average 2 171 30.2 3.3% 0.8% Watts 7 Other Industrial-Efficient MachDr Equipment 138 21.3 2.7% 0.5% 8 Com-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 128 32.5 2.5% 0.8% Watts 9 Corn-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 127 31.2 2.5% 0.8% 10 Com-Retail-LED downlight fixture,9-15W,interior Average 9 Watts 119 29.2 2.3% 0.8% Source:Navigant 2016 35 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-30. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-Shade Tree 83 0.0 6.7% 0.0% 2 Res-Single Family-Variable Speed Pool Pump 63 0.0 5.0% 0.0% 3 Res-Multi Family-CEE Tier Ill Refrigerator(from 30$to 35%more efficient) 46 0.0 3.7% 0.0% 4 Res-Single Family-Solar Attic Fan(1,000 CFM) 32 36.9 2.6% 0.8% 5 Res-Multi Family-Split System AC Tuneup/Recharge 32 42.9 2.6% 0.9% 6 Corn-Office-LED T8 Tube Replacement Average Fixture Wattage 59.65 32 12.8 2.6% 0.3% 7 Corn-Education-LED T8 Tube Replacement Average Fixture Wattage 32 4.2 2.5% 0.1% 59.65 8 Res-Single Family-Split System AC Tuneup/Recharge 29 27.8 2.3% 0.6% 9 Com-Office-Window Film 26 14.9 2.1% 0.3% 10 Com-Warehouse-Cool Roof 26 22.7 2.1% 0.5% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Glendale to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Glendale's current 10- year goals are about 132% of the goals established in the prior study. The primary reason for the higher goals is the claim of C&S savings. NAVIGANT To: Gridley Municipal Utilities From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Gridley Municipal Utilities with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Gridley service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 19. Base Case Run. This modeling run includes no changes or adjustments to Gridley's current portfolio of energy efficiency programs. 20. Final Run. This modeling run uses Gridley's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.36 Gridley chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 36 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 12. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 140 0.40% 0.35% 120 0.30% 1W 0.15% v', 80 .. .c i 0.20% v 60 E 0.15% a v a= 40 0.10% 20 0.05% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 IMITntal Incremental Potential as a%M Total Sales Non Res Incremental Market Potential -.0-Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 108 107 96 108 124 124 113 104 96 84 Res Incremental Market Potential 53 47 28 29 32 34 33 34 30 26 Non-Res Incremental Market Potential 55 61 69 79 92 90 80 70 65 59 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.30% 030% 0.27% 0.30% 0.33% 0.33% 0.31% 0.28% 0.26% 0.23% Res Incremental Potential asa%of Res Sales 0.34% 0.30% 0.18% 0.19% 0.20% 0.21% 0.21% 0.21% 0.19% 0.16% Non-Res Incremental Potential as a%of Non-Res Sales 0.27% 0.30% 0.33% 0.37% 0.44% 0.43% 0.38% 0.33% 0.31% 0.28% 30 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 25 26 27 30 33 32 31 29 28 27 Res Incremental Market Potential 11 10 9 10 10 11 11 11 11 10 Non-Res Incremental Market Potential 14 16 18 20 23 22 20 18 17 17 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 Table 4-31. Inputs to Figure 1 Source:Navigant 2016 At a glance, Gridley's results include: • A 2018-2027 average annual target of 0.29% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Gridley begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.37 Table 4-32. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-LED Indoor Screw-in Lamp-Low Wattage-8 watt avg. 30 2.4 16.6% 4.7% 2 Food-Efficient Lighting Equipment 18 1.9 10.0% 3.6% 3 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 12 1.0 6.6% 1.9% 4 Res-Single Family-LED Indoor Reflector Downlight-12 watt avg. 11 0.9 6.0% 1.7% Res-Single Family-LED Indoor Screw-in Lamp-High Wattage-17 watt 5 avg. 10 0.8 5.5% 1.5% 6 Com-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 5 1.4 3.0% 2.6% 7 Com-Lodging-LED fixture:33W,3500 lumens 5 0.3 2.8% 0.5% 8 Com-Lodging-Reduced Wattage T8 Lamp and Ballast Average Fixture 5 0.3 2.6% 0.5% Wattage 72.23 9 Res-Single Family-ENERGY STAR Ceiling Fan(w/ES rated CFL) 4 5.3 2.3% 10.2% 10 Com-Lodging-LED T8 Tube Replacement Average Fixture Wattage 59.65 4 0.2 2.0% 0.4% Source:Naviganf 2016 37 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-33. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 9 0.7 11.9% 1.6% 2 Res-Single Family-LED Indoor Reflector Downlight-12 watt avg. 7 0.6 9.9% 1.3% 3 Res-Single Family-ENERGY STAR Ceiling Fan(w/ES rated CFL) 5 6.4 6.8% 14.3% 4 Com-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 5 1.2 6.3% 2.6% 5 Corn-Retail-LED fixture:33W,3500 lumens 4 0.9 4.8% 2.0% 6 Corn-Office-LED fixture:33W,3500 lumens 3 1.2 4.0% 2.7% Com-Lodging-LED downlight,screw-in lamp, 1-3W,interior Average 27 2 0.1 2.9% 0.3% Watts 8 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 2 2.2 2.3% 4.9% 9 Com-Office-Bi-Level Lighting Fixture-Stairwells,Hallways,and Garages 2 0.0 2.1% 0.0% 10 Corn-Office-LED T8 Tube Replacement Average Fixture Wattage 59.65 2 0.6 2.1% 1.4% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Gridley to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Gridley's current 10-year goals are about 39% of the goals established in the prior study. The primary reason is calibration. In 2012, Gridley adopted targets that were calibrated significantly above historic achievements. In 2016, Gridley used the three year average of actual achievements between 2013 and 2015 for calibration. NAVIGANT To: Healdsburg Electric Department From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Healdsburg Electric Department with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Healdsburg service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 21. Base Case Run. This modeling run includes no changes or adjustments to Healdsburg's current portfolio of energy efficiency programs. 22. Final Run. This modeling run uses Healdsburg's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.38 Healdsburg's Final Run included the following adjustments to their Base Case Run: • Utilized a 3-year average calibration target. The three-year average of the years 2013 through 2015 is 32% higher than the 2015 program achievements. • Expanded measure list. Navigant modeled a number of measures—not currently offered in Healdsburg's portfolio—to provide a picture of potential savings should Healdsburg decide to expand their current programs. Healdsburg added several residential and commercial measures. • Increased promotional costs by 50%. • Increased incentive by 50%. 38 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 13. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN otYl 0-70% 0.60% SOO 0.50% ,� 400 0,40% 5300 03^ r 0.20 200 11X1 0.10 D ODD: 2078 2019 7020 2071 2072 2073 2074 2025 7076 2027 Total Incremental Potential as a%of Total Sales Mil Non Ret Incremental Market Potential f•Total Incremental Potential as a N of Total Sakes Table 4-34. Inputs to Figure 1 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 490 486 469 466 438 393 358 331 296 257 Res Incremental Market Potential 39 48 40 45 51 57 62 64 63 59 Non-Res Incremental Market Potential 451 438 429 421 387 336 296 268 233 198 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.65% 0.65% 0.62% 0.61% 0.57% 0.51% 0.46% 0.42% 0.38% 0.33% Res Incremental Potential as a%of Res Sales 0.08% 0.10% 0.08% 0.10% 0.11% 0.12% 0.13% 0.13% 0.13% 0.12% Non-Res Incremental Potential as a%of Non-Res Sales 1.54% 1.47% 1.44% 1.39% 1.28% 1.10% 0.97% 0.88% 0.76% 0.65% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 98 103 102 101 94 85 79 67 52 38 Res Incremental Market Potential 9 12 13 16 20 25 30 26 19 10 Non-Res Incremental Market Potential 89 91 89 84 74 60 49 41 34 28 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Healdsburg's results include: • A 2018-2027 average annual target of 0.52% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • Add new residential and commercial sector measures • Increase measure incentives by 50% • Increase program promotion budget by 50% NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Healdsburg begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.39 Table 4-35. Top 10 Energy Saving Measures for 2017 1 Com-Restaurant-LED downlight,screw-in lamp,1-3W,interior Average 2 Watts 45 11.9 7.7% 9.7% 2 Street Lighting-LED Streetlights 39 0.0 6.6% 0.0% 3 Street Lighting-LED Streetlights with Advanced Controls 28 0.0 4.8% 0.0% 4 Corn-Retail-LED fixture:33W,3500 lumens 23 5.8 3.9% 4.7% 5 Corn-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 20 5.1 3.4% 4.1% 6 Com-Lodging-LED fixture: 33W,3500 lumens 20 1.1 3.3% 0.9% 7 Com-Office-LED fixture:33W,3500 lumens 19 7.8 3.2% 6.3% 8 Fabricated Metals-Efficient Lighting Equipment 16 3.3 2.7% 2.6% 9 Com-Restaurant-LED downlight,screw-in lamp,4-20W,interior Average 11 14 3.6 2.3% 2.9% Watts 10 Corn-Grocery-Electronically Commutated(EC)Motor w/Fan Cycling Controls for 12 1.4 2.1% 1.1% Cold Storage Evaporator Fans Source:Navigant 2016 39 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-36. Top 10 Energy Saving Measures for 2030 Corn-Grocery-Electronically Commutated(EC)Motor w/Fan Cycling Controls for 21 2.4 9.5% 4.7% Cold Storage Evaporator Fans 2 Corn-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 15 1.5 6.6% 2.8% 3 Res-Single Family-LED Indoor Screw-in Lamp-Low Wattage-8 watt avg. 14 1.1 6.3% 2.2% 4 Com-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 13 3.5 6.0% 6.9% 5 Corn-Restaurant-Electronically Commutated(EC)Motor w/Fan Cycling Controls 11 1.3 5.2% 2.6% for Cold Storage Evaporator Fans 6 Corn-Retail-Electronically Commutated(EC)Motor w/Fan Cycling Controls for 11 1.2 4.9% 2.4% Cold Storage Evaporator Fans 7 Corn-Grocery-Electronically Commutated(EC)Walk-In Evaporator Fan Motor 11 1.2 4.9% 2.4% 8 Res-Single Family-Low Income 10 2.4 4.7% 4.7% 9 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 9 0.7 4.1% 1.4% 10 Other Industrial-Efficient Lighting Equipment 7 0.6 3.0% 1.2% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Healdsburg to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include CBIS Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Healdsburg's current 10- year goals are about 150% of the goals established in the prior study. There are several reasons for these higher goals: • Add new residential and commercial sector measures • Increase measure incentives by 50% • Increase program promotion budget by 50% NAVIGANT To: Imperial Irrigation District From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Imperial Irrigation District (IID) with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the IID service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 23. Base Case Run. This modeling run includes no changes or adjustments to HD's current portfolio of energy efficiency programs. 24. Final Run. This modeling run uses IID's chosen adjustments—if any—to various features within the model to illustrate alternative energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.40 IID chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 40 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 14. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 40.0(X7 1_W% 35,000 O.R09., I 0.70`k �, O.f,<No �� 3 2 L 0 5090 w 0.20Qe 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 IIIII8Res Incremental Market Potential 01111Non Rex Irxtementai Market Potential t✓•C&S it Claimed.Estimates not evadable atter 2024) --Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 33,475 33,760 33352 32,232 30,894 28,668 27,685 26,708 25,027 22,435 Res Incremental Market Potential 8,174 7,999 8,493 8,910 9,013 8,923 8,646 8,312 7,818 6,766 Non-Res Incremental Market Potential 7,500 8,076 8,716 9,141 9,212 8,994 8,786 8,618 7,885 6,777 C&S(If Claimed.Estimates not available after 2024) 17,801 17385 16,743 14,181 12,669 10,751 10,252 9,777 9,324 8,892 Total Incremental Potential as a%of Total Sales 0.95% 0.95% 0.94% 0.88% 0.82% 0.75% 0.71% 0.68% 0.63% 0.55% Res Incremental Potential as a%of Res Sales 0.52% 0.50% 0.52% 0.54% 0.53% 0.52% 0.50% 0.47% 0.43% 0.37% Non-Res Incremental Potential as a%of Non-Res Sales 0.38% 0.40% 0.43% 0.44% 0.44% 0.42% 0.40% 0.39% 0.35% 0.30% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 15,878 15,778 16,105 16,242 16,422 15,033 15,063 15,040 14,856 14,471 Res Incremental Market Potential 3350 3,086 3,290 3,477 3,537 3,515 3,357 3,151 3,006 2,788 Non-Res Incremental Market Potential 7,630 7,941 8,202 8,479 8,823 7,704 7,999 8,286 8,347 8,278 C&S(If Claimed.Estimates not available after 2024) 4,698 4,751 4,612 4,286 4,062 3,814 3,707 3,603 3,503 3,405 Table 4-37. Inputs to Figure 1 Source:Navigant 2016 At a glance, IID's results include: • A 2018-2027 average annual target of 0.79% of forecasted retail sales • Net savings targets • Only codes and standards (C&S)that are currently in place today, and not future C&S such as updates to Title 24 NAVIGANT • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as IID begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.41 Table 4-38. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-Duct Repaire to 13%Leakage 2,472 2,346.9 12.8% 14.7% 2 Res-Single Family-Variable Speed Pool Pump 1,272 0.0 6.6% 0.0% 3 Res-Single Family-Split System AC SEER 18 to 22, 13 EER 850 560.3 4.4% 3.5% 4 Corn-Office-Comprehensive Rooftop Unit Quality Maintenance(AC 802 354.0 4.2% 2.2% Tune-up) 5 Res-Single Family-Split System AC Tuneup/Recharge 743 422.6 3.9% 2.6% 6 Res-Single Family-Split System AC SEER 15, 12.5 EER 700 486.4 3.6% 3.0% 7 Other Industrial-Efficient Lighting Equipment 440 42.8 2.3% 0.3% 8 Res-Single Family-Solar Attic Fan(1,000 CFM) 407 131.1 2.1% 0.8% 9 Res-Single Family-Whole House Fan 379 0.0 2.0% 0.0% 10 Com-Other-Comprehensive Rooftop Unit Quality Maintenance(AC 368 144.6 1.9% 0.9% Tune-up) Source:Navigant 2016 41 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-39. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-Split System AC SEER 18 to 22, 13 EER 862 568.3 8.1% 4.9% 2 Res-Single Family-Split System AC Tuneup/Recharge 704 400.5 6.6% 3.4% 3 Res-Single Family-Solar Attic Fan(1,000 CFM) 668 215.1 6.3% 1.8% 4 Corn-New-LED downlight,screw-in lamp, 1-3W,interior Average 2 654 136.8 6.1% 1.2% Watts 5 Corn-ALL-Pump and Fan Variable Frequency Drive Controls 548 54.2 5.1% 0.5% (VFDs) 6 Corn-Retail-Electronically Commutated(EC)Motor w/Fan Cycling 272 31.0 2.6% 0.3% Controls for Cold Storage Evaporator Fans 7 Com-Grocery-Electronically Commutated(EC)Motor w/Fan Cycling 244 27.9 2.3% 0.2% Controls for Cold Storage Evaporator Fans 8 Res-Single Family-Refrigerator Recycling 217 43.7 2.0% 0.4% 9 Res-Single Family-Smart Thermostat(manual base) 196 0.0 1.8% 0.0% 10 Res-Single Family-Wall Insulation(R-13) 187 0.0 1.8% 0.0% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with IID to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. IID's current 10-year goals are about 176% of the goals established in the prior study. There are two primary reasons. The first is model calibration where the current calibration is higher than the 2012 model. The second is that IID now claims savings from Codes and Standards. NAVIGANT To: Lassen Municipal Utility District From: Navigant Consulting, Inc. Date: February 20, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Lassen Municipal Utility District with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2017 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Lassen service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 25. Base Case Run. This modeling run includes no changes or adjustments to Lassen's current portfolio of energy efficiency programs. 26. Final Run. This modeling run uses Lassen's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.42 Lassen modified program design to include early retirement starting in 2018. Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 15. Net Incremental Market Potential by Sector(MWh)and Percent of Sales—FINAL RUN Net Incremental Market Potential by Sector 101 All Sectors Energy Potential(MWh)and%of Sales 0.30s 350 :J:5% 300 6 250 096 'A^ 200 15% To 150 a 0.10%o 100 0.05% 50 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 MI Res Incremental Market Potential Non-Res Incremental Market Potential C&S(If Claimed) Total Incremental Potential as a 96of Total Sales NAVIGANT Table 4-40. Inputs to Figure 1 ALL Sectors(MW6) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 353 371 318 339 356 359 352 350 332 320 Res Incremental Market Potential 256 267 205 214 221 228 222 221 206 201 Non-Res Incremental Market Potential 97 104 114 125 134 131 130 129 126 120 C&S(If Claimed) 0 0 00 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.27% 0.28% 0.24% 0.25% 0.26% 0.26% 0.26% 0.25% 0.24% 0.23% Res Incremental Potential as a%of Res Sales 1.84% 1.92% 1.46% 1.51% 1.55% 1.59% 1.55% 1.53% 1.43% 1.39% Non-Res Incremental Potential as a%of Non-Res Sales 0.08% 0.09% 0.10% 0.10% 0.11% 0.11% 0.11% 0.11% 0.10% 0.10% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 79 86 87 96 104 104 103 102 98 92 Res Incremental Market Potential 35 39 35 39 41 44 44 44 42 41 Non-Res Incremental Market Potential 44 47 52 58 63 60 59 58 56 51 C&S(If Claimed) ._...._... 0 0 -__-0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Lassen's results include: • A 2018-2027 average annual target of 0.25% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • Modified program design to include early retirement NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Lassen begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.43 Table 4-41. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-LED Indoor Screw-in Lamp-Low Wattage-8 watt 78 6.3 26.2% 7.9% avg. 2 Res-Single Family-Low Flow Showerhead(Electric DHW) 29 6.2 9.6% 7.8% 3 Res-Single Family-Bathroom Faucet Aerators(0.5-1.0 GPM Electric 27 5.9 9.1% 7.4% DHW) 4 Res-Single Family-LED Indoor Screw-in Lamp-High Wattage-17 watt 27 2.2 8.9% 2.7% avg. 5 Corn-Other-LED fixture:33W,3500 lumens 14 10.1 4.6% 12.6% 6 Res-Single Family-ENERGY STAR Clothes Washer,Elec DHW,Electric 9 0.0 3.1% 0.0% or Gas Dryer(2.0 MEF) 7 Corn-Other-Bi-Level Lighting Fixture-Stairwells,Hallways,and 8 0.1 2.8% 0.1% Garages 8 Corn-Other-LED T8 Tube Replacement Average Fixture Wattage 59.65 7 5.2 2.4% 6.5% 9 Res-Single Family-Heat Pump Water Heater(>2.0 EF-50 Gallon) 6 1.2 2.0% 1.5% 10 Res-Single Family-LED Indoor Screw-in Lamp(CFL Base)-High 5 0.4 1.8% 0.6% Wattage-17 watt avg. Source:Navigant 2016 43 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-42. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-CEE Tier III Refrigerator(from 30$to 35%more 31 0.0 9.1% 0.0% efficient) 2 Res-Single Family-CEE Tier II Refrigerator 26 0.0 7.8% 0.0% 3 Res-Single Family-ENERGY STAR Refrigerator 21 0.0 6.2% 0.0% 4 Com-Other-LED fixture:33W,3500 lumens 20 14.9 6.0% 14.3% 5 Res-Single Family-Bathroom Faucet Aerators(0.5-1.0 GPM Electric 18 4.0 5.5% 3.9% DHW) 6 Res-Single Family-Low Flow Showerhead(Electric DHW) 16 3.5 4.9% 3.4% 7 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 13 1.0 3.8% 1.0% 8 Res-Single Family-LED Indoor Reflector Downlight-12 watt avg. 11 0.9 3.3% 0.9% 9 Com-Other-Bi-Level Lighting Fixture-Stairwells,Hallways,and 11 0.1 3.2% 0.1% Garages 10 Com-Other-Commercial SEER-rated Packaged Air Conditioners,SEER 11 5.8 3.2% 5.6% = 15(EER=12.9) Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Lassen to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10- year study periods. Lassen's current 10-year goals are about 118% of the goals established in the prior study. The primary reason is the change in program design to include early retirement NAVIGANT To: Lodi Electric Utility From: Navigant Consulting, Inc. Date: February 20, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Lodi Electric Utility with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Lodi service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 27. Base Case Run. This modeling run includes no changes or adjustments to Lodi's current portfolio of energy efficiency programs. 28. Final Run. This modeling run uses Lodi's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.44 Lodi chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. Figure 1 shows the gross incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 16. Gross Incremental Market Potential by Sector(MWh) and Percent of Sales-FINAL RUN Net Incremental Market Potential by Sector All Sectors Energy Potential(MWh)and%of Sales1,800 0.405i 1.i 0.35% 0.3096025% �^`30.20%o n% <``oa 10% xaas%am% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 SONO Res Incremental Market Potential IMO Non-Res Incremental Market Potential tTotal Incremental Potential as a%of Total Sales NAVIGANT Table 4-43. Inputs to Figure 1 ALL Sectors(MWS) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,227 1,313 1,399 1,496 1,575 1,604 1,612 1,618 1 587 1,534 Res Incremental Market Potential 361 380 387 408 427 443 453 458 458 454 Non-Res Incremental Market Potential 866 933 1,011 1,089 1,147 1,161 1,160 1,160 1,130 1,079 C&S(If Claimed.Estimates not available after 2024) 00 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.28% 0.30% 0.32% 0.34% 0.36% 0.36% 0.36% 0.36% 0.35% 0.34% Res Incremental Potential as a%of Res Sales 0.24% 0.25% 0.26% 0.27% 0.28% 0.29% 0.29% 0.30% 0.29% 0.29% Non-Res Incremental Potential as a%of Non-Res Sales 0.31% 0.33% 0.35% 0.38% 0.40% 0.40% 0.40% 0.40% 0.38% 0.36% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 372 394 418 440 457 465 472 480 470 452 Res Incremental Market Potential 171 183 194 205 213 218 221 220 218 214 Non-Res Incremental Market Potential 201 21.2 224 235 244 246 252 259 252 238 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Lodi's results include: • A 2018-2027 average annual target of 0.34% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Lodi begins to allocate program dollars in new directions. Table 3 shows the top 10 energy saving measures for the first year of the forecast period and Table 4 shows the top 10 measures for year 2030 to use as a comparison.45 Table 4-44. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-Low Income 208 48.0 12.3% 8.4% 2 Res-Single Family-Variable Speed Pool Pump 82 0.0 4.9% 0.0% 3 Com-Other-WholeBlg-Corn Retrofit Level 2 82 38.3 4.8% 6.7% 4 Res-Single Family-Solar Attic Fan(1,000 CFM) 65 73.3 3.9% 12.9% 5 Com-Other-Thermostat Replacement 59 0.0 3.5% 0.0% 6 Corn-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 57 5.6 3.4% 1.0% 45 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT 7 Com-Other-WholeBlg-Corn Retrofit Level 1 54 18.9 3.2% 3.3% 8 Res-Single Family-Wall Insulation(R-13) 49 0.0 2.9% 0.0% 9 Com-Office-Retro-commissioning 43 0.0 2:5% 0.0% 10 Res-Single Family-Split System AC Tuneup/Recharge 43 74.0 2.5% 13.0% Source:Navigant 2016 Table 4-45. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-Low Income 208 48.0 9.7% 6.8% 2 Res-Single Family-Variable Speed Pool Pump 137 0.0 6.4% 0.0% 3 Corn-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 124 12.3 5.8% 1.7% 4 Corn-Other-WholeBlg-Corn Retrofit Level 2 98 45.7 4.6% 6.5% 5 Res-Single Family-Solar Attic Fan(1,000 CFM) 90 100.6 4.2% 14.3% 6 Com-Other-WholeBlg-Corn Retrofit Level 1 64 22.6 3.0% 3.2% 7 Res-Single Family-Whole House Fan 60 0.0 2.8% 0.0% 8 Res-Single Family-Wall Insulation(R-13) 59 0.0 2.7% 0.0% 9 Com-Office-Retro-commissioning 55 0.0 2.6% 0.0%B 10 Com-Grocery-Electronically Commutated(EC)Motor w/Fan Cycling Controls for 50 5.7 2.3% 0.8% Cold Storage Evaporator Fans Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Lodi to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Lodi's current 10-year • goals are about 46% of the goals established in the prior study. The primary reason is model calibration. In the earlier version, the calibration target was set about 20% above actual historical achievements and the current calibration targets are over 40% lower. The calibration target for the current model reflects actual levels of average program achievement over the period 2013, 2014, and 2015. NAVIGANT To: City of Lompoc Utilities From: Navigant Consulting, Inc. Date: February 6, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides the City of Lompoc Utilities with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Lompoc service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 29. Base Case Run. This modeling run includes no changes or adjustments to Lompoc's current portfolio of energy efficiency programs. 30. Final Run. This modeling run uses Lompoc's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.46 For its final run, Lompoc: • Added new residential and commercial sector measures to their portfolio starting in 2018 • Is now claiming gross savings targets in 2016 while they claimed net in 2012. Figure 1 shows the gross incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 17. Gross Incremental Market Potential by Sector(MWh)and Percent of Sales—FINAL RUN Incremental Gross Markt Potential by Sector 3s0 All Sectors Energy Potential(MWh)and%of Sales azs% I o.zo% a 15%o.10% a`o.os%0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Res incremental Market Potential Min Non-Res Incremental Market Potential MMC&S(lf Claimed) —o—Total Incremental Potential as a%of Total Sales NAVIGANT Table 4-46. Inputs to Figure 1 ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 213 236 249 266 282 300 313 324 326 320 Res Incremental Market Potential 109 115 114 118 122 125 128 131 133 129 Non Res Incremental Market Potential 104 120 134 148 160 175 185 193 193 191 C&S(If Claimed) 0 0 0 00 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.16% 0.17% 0.18% 0.19% 0.20% 0.21% 0.22% 0.23% 0.23% 0.22% Res Incremental Potential as a%of Res Sales 0.20% 0.21% 0.21% 0.21% 0.22% 0.22% 0.23% 0.23% 0.23% 0.23% Non-Res Incremental Potential as a%of Non-Res Sales 0.13% 0.14% 0.16% 0.17% 0.19% 0.21% 0.22% 0.22% 0.22% 0.22% 10 Year Demand Goals(kW) ALL Sectors(MN) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 34 37 39 42 45 48 50 53 53 52 Res Incremental Market Potential 11 12 12 13 13 14 14 14 14 14 Non-Res Incremental Market Potential 23 2.4 26 29 31 34 36 38 38 38 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Lompoc's results include: • A 2018-2027 average annual target of.19% of forecasted retail sales • Gross savings targets • New residential and commercial sector measures • No claim of savings from codes and standards (C&S) Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Lompoc begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.47 Table 4-47. Top 10 Energy Saving Measures for 2017 1 Corn-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 19 1.9 14.5% 6.1% 2 Res-Single Family-CEE Tier III Refrigerator(from 30$to 35%more efficient) 16 0.0 12.4% 0.0% 3 Res-Single Family-CEE Tier II Refrigerator 15 0.0 11.2% 0.0% 4 Res-Low Income-Refrigerator Recycling 12 2.5 9.4% 8.1% 47 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT 5 Res-Single Family-Refrigerator Recycling 12 2.5 9.2% 7.9% 6 Com-Retail-Reduced Wattage T8 Lamp and Ballast Average Fixture Wattage 72.23 11 2.9 8.6% 9.2% 7 Res-Multi Family-CEE Tier Ill Refrigerator(from 30$to 35%more efficient) 11 0.0 8.3% 0.0% 8 Res-Multi Family-CEE Tier II Refrigerator 10 0.0 7.6% 0.0% 9 Corn-Office-Reduced Wattage T8 Lamp and Ballast Average Fixture Wattage 72.23 3 1.2 2.2% 3.8% 10 Com-Education-Reduced Wattage T8 Lamp and Ballast Average Fixture Wattage 3 1.3 2.1% 4.3% 72.23 Source:Navigant 2016 Table 4-48. Top 10 Energy Saving Measures for 2030 1 Com-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 21 2.1 6.9% 3.4% 2 Res-Single Family-CEE Tier Ill Refrigerator(from 30$to 35%more efficient) 21 0.0 6.8% 0.0% 3 Res-Single Family-CEE Tier Il Refrigerator 18 0.0 5.8% 0.0% 4 Res-Multi Family-CEE Tier Ill Refrigerator(from 30$to 35%more efficient) 14 0.0 4.6% 0.0% 5 Res-Single Family-Refrigerator Recycling 14 2.8 4.5% 4.4% 6 Res-Multi Family-CEE Tier II Refrigerator 12 0.0 3.9% 0.0% 7 Res-Low Income-Refrigerator Recycling 12 2.3 3.8% 3.7% 8 Corn-Retail-WholeBlg-Com RET Level 2 10 3.2 3.2% 5.0% 9 Com-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 8 2.0 2.5% 3.1% 10 Com-Office-Retro-commissioning 7 0.0 2.4% 0.0% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Lompoc to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Lompoc's current 10-year goals are about 112% of the goals established in the prior study. The primary reasons for the higher 2016 savings include adding new residential and commercial sector measures to their portfolio starting in 2018 and claiming gross savings targets in 2016 while they claimed net in 2012. NAVIGANT To: Los Angeles Department of Water&Power From: Navigant Consulting, Inc. Date: February 6, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Los Angeles Department of Water& Power(LADWP)with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the LADWP service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 31. Base Case Run. This modeling run includes no changes or adjustments to LADWP's current portfolio of energy efficiency programs. 32. Final Run. This modeling run uses LADWP's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.48 LADWP's Final Run included the following adjustments to their Base Case Run: • A/C Optimization Program added in 2016 • Efficient Product Marketplace Program added in 2016 • Commercial Direct Install Program added in 2016 • Residential Behavioral Program added in 2017 Figure 1 shows the gross incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 48 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 18. Gross Incremental Market Potential by Sector(MWh) and Percent of Sales-FINAL RUN 450.000 160.,. 400,000 1.40% 350,000 1.1P! 3(Y5,000 FY17 18 FY18 19 FY19 20 FY20 21 FY21 22 FY22 23 FY23 24 FY24 25 FY25•26 FY26 27 NM Res Incremental Market Potential Non-Res Incremental Market Potential IIMIC&S(If Claimed.Estimates not available after 2024) -Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Gross MWh) ALL Sectors(MWh) FY17-18 FY18-19 FY19-20 FY20-21 FY21-22 FY22-23 FY23-24 FY24-25 FY25-26 FY26-27 Total Incremental Market Potential 377,701 382,463 377,413 351,678 331,494 307,521 293,832 297,211 287,665 277,376 Res Incremental Market Potential 107,463 111,287 115,098 120,022 124,472 128,198 131,141 135,093 139,236 142,807 Non-Res Incremental Market Potential 112,823 116,466 116,058 107,696 96,009 83,369 72,112 62,932 53,821 44,297 C&S If Claimed 157,414 154,711 146,256 123,960 111,013 95,953 90,579 99,187 94,607 90,272 Total Incremental Potential as a%of Total Sales 1.51% 1.51% 1.47% 1.35% 1.26% 1.15% 1.09% 1.09% 1.04% 0.99% Res Incremental Potential as a%of Res Sales 1.25% 1.27% 1.29% 1.31% 1.33% 1.35% 1.35% 1.36% 1.38% 1.38% Non-Res Incremental Potential as a%of Non-Res Sales 0.68% 0.70% 0.69% 0.63% 0.56% 0.48% 0.42% 0.36% 0.31% 0.25% 10 Year Demand Goals(kW) ALL Sectors(kW) FY17-18 FY18-19 FY19-20 FY20-21 FY21-22 FY22-23 FY23-24 FY24-25 FY25-26 FY26-27 Total Incremental Market Potential 148,879 156,439 164,531 171,031 177,851 159,664 163,496 167,205 169,652 170,677 Res Incremental Market Potential 8,163 8,842 9,968 11,399 12,693 13,754 14,453 15,078 15,727 16,277 Non-Res Incremental Market Potential 98,985 105,729 113,536 121,391 128,799 111,666 115,872 119,670 122,362 123,700 C&S If Claimed 41,730 41,869 41,027 38,241 36,359 34,243 33,171 32,457 31,563 30,700 Table 4-49. Inputs to Figure 1 Source:Navigant 2016 At a glance, LADWP's results include: • A 2018-2027 average annual target of 1.25% of forecasted retail sales • Gross savings targets • Only codes and standards (C&S)that are currently in place today, and not future C&S such as updates to Title 24 • LADWP claims gross C&S savings • Four new programs added NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as LADWP begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.49 Table 4-50. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-Shade Tree 12,194 0.0 8.1% 0.0% 2 Res-Low Income-Refrigerator Recycling 6,677 1,344.0 4.4% 1.3% 3 Com-Grocery-LED downlight,screw-in lamp, 1-3W,interior Average 2 6,355 1,125.1 4.2% 1.1% Watts 4 Com-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 4,883 1,242.9 3.2% 1.2% Watts 5 Res-Single Family-Refrigerator Recycling 4,347 875.0 2.9% 0.8% 6 Petroleum-Efficient MachDr O&M 3,738 1,870.7 2.5% 1.8% 7 Com-Office-Bi-Level Lighting Fixture—Stairwells,Hallways,and Garages 3,593 41.7 2.4% 0.0% 8 Corn-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 2,818 693.0 1.9% 0.7% 9 Res-MF New-Zero Net Energy Home(40-50%less energy than 2013 T24 2,628 413.8 1.7% 0.4% home) 10 Com-ALL-Smart Power Strip—Commercial Use 2,434 590.9 1.6% 0.6% Source:Navigant 2016 49 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-51. Top 10 Energy Saving Measures for 2030 Res-MF New-Zero Net Energy Home(40-50%less energy than 2013124 ° 8�% 1 home): 19,318 3,042.0 21.1% 2 Res-Single Family-Refrigerator Recycling 12,864 2,589.6 14.0% 7.4% 3 Res-Low Income-Refrigerator Recycling 6,677 1,344.0 7.3% 3.8% 4 Res-Multi Family-Refrigerator Recycling 3,710 746.9 4.0% 2.1% 5 Res-Single Family-Shade Tree 3,603 0.0 3.9% 0.0% 6 Com-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 3,069 303.9 3.3% 0.9% 7 Com-Office-Retro-commissioning 2,292 0.0 2.5% 0.0% 8 Com-Office-Commercial SEER-rated Packaged Air Conditioners,SEER= 1,658 984.2 1.8% 2.8% 15(EER= 12.9) 9 Res-Single Family-Variable Speed Pool Pump 1,412 0.0 1.5% 0.0% 10 Res-Single Family-Freezer Recycling 1,154 231.6 1.3% 0.7% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with LADWP to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. LADWP's current 10-year goals are about 158% of the goals established in the prior study. There are several reasons for these higher goals: • A/C Optimization Program added in 2016 • Efficient Product Marketplace Program added in 2016 • Commercial Direct Install Program added in 2016 • Residential Behavioral Program added in 2017 • The C&S claim is expressed as gross savings NAVIGANT To: Merced Irrigation District From: Navigant Consulting, Inc. Date: February 5, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Merced Irrigation District with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Merced service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 33. Base Case Run. This modeling run includes no changes or adjustments to Merced's current portfolio of energy efficiency programs. 34. Final Run. This modeling run uses Merced's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.5o Merced chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 50 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 19. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 1,Z 0.35% .-,. U 1.400lir '�- 1,xa1 600 1,000 2 % 7018 2014 2070 2071 7071 7073 2074 2075 2076 7077 MIN Res Incremental Market Potential Non Res Incremental Market Potential --Total Incremental Potential as a%ot Total Sales Table 4-52. Inputs to Figure 1 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,258 1,346 1,452 1,551 1,597 1,586 1,525 1,455 1,392 1,350 Res Incremental Market Potential 14 15 16 19 23 24 25 26 26 26 Non-Res Incremental Market Potential 1,244 1,330 1,436 1,532 1,574 1,562 1,500 1,429 1,366 1,324 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.27% 0.28% 0.30% 0.32% 0.33% 0.32% 0.31% 0.29% 0.28% 0.27% Res Incremental Potential as a%of Res Sales 0.02% 0.03% 0.03% 0.03% 0.04% 0.04% 0.04% 0.04% 0.04% 0.04% Non-Res Incremental Potential as a%of Non-Res Sales 0.30% 0.32% 0.34% 0.36% 0.37% 0.36% 0.34% 0.32% 0.31% 0.29% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 219 236 255 273 281 279 265 248 234 229 Res Incremental Market Potential 1 1 1 1 1 1 1 1 1 1 Non-Res Incremental Market Potential 219 235 254 272 281 278 264 248 233 228 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Merced's results include: • A 2018-2027 average annual target of 0.30% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Merced begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.51 Table 4-53. Top 10 Energy Saving Measures for 2017 1 Food-Efficient Lighting Equipment 256 26.4 16.6% 9.5% 2 Printing&Publishing-Efficient Lighting Equipment 102 10.4 6.6% 3.8% 3 Com-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 80 7.9 5.2% 2.8% 4 Com-Retail-LED fixture:33W,3500 lumens 72 18.1 4.6% 6.5% 5 Corn-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 69' 17.6 4.5% 6.3% 6 Food-Efficient MachDr Equipment 66 4.3 4.3% 1.6% 7 Com-ALL-Smart Power Strip-Commercial Use 58 14.0 3.7% 5.0% 8 Corn-Education-LED fixture:33W,3500 lumens 49 5.8 3.2% 2.1% 9 Com-Restaurant LED downlight,screw-in lamp,1-3W interior Average 2 47 12.0 3.1% 4.3% Watts 10 Corn-Office-LED fixture:33W,3500 lumens 41 16.8 2.7% 6.1% Source:Navigant 2016 51 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-54. Top 10 Energy Saving Measures for 2030 1 Food-Efficient Lighting Equipment 153 15.8 9.9% 5,5% 2 Com-Retail-LED fixture: 33W,3500 lumens 110 27.8 7.1% 9.8% 3 Food-Efficient MachDr Equipment 102 6.7 6.6% 2.4% 4 Com-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 90 8.9 5.8% 3.1% 5 Com-Retail-LED downlight,screw-in lamp,1-3W,interior Average 2 Watts 75 18.9 4.8% 6.7% 6 Com-Education-LED fixture:33W,3500 lumens 74 8.9 4.8% 3.1% 7 Com-Office-LED fixture:33W,3500 lumens 63 25.6 4.1% 9.0% 8 Printing&Publishing-Efficient Lighting Equipment 61 6.2 4.0% 2.2% 9 Com-Retail-LED T8 Tube Replacement Average Fixture Wattage 59.65 56 14.3 3.7% 5.0% 10 Corn-Restaurant-LED downlight,screw-in lamp,1-3W,interior Average 2 49 12.7 3.2% 4.5% Watts Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Merced to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Merced's current 10-year goals are about 79% of the goals established in the prior study. The primary reason is model calibration. In the earlier version, the calibration target was set as a percent of sales, which was above actual historical achievements. The calibration target for the current model reflects actual levels of program achievement as an average of the years 2013, 2014, and 2015. NAVIGANT To: Modesto Irrigation District From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Modesto Irrigation District with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Modesto service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 35. Base Case Run. This modeling run includes no changes or adjustments to Modesto's current portfolio of energy efficiency programs. 36. Final Run. This modeling run uses Modesto's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.52 Modesto chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 52 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 20. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 16,000 0.4:0"%` 140(X) 050co 12.000 10, !000 3 8.0000.30% (q a n. 6.. 4,000 v.u0% 2,000 0 0.00% 2018 2019 2020 2071 2022 2071 2024 2025 2026 2027 NM Res Incremental Market Potential Inn Non-Res Incremental Market Potential tTotal Incremental Potential as a%ot Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 9,144 10,060 11,062 12,052 12,879 13,385 13,700 13,714 13,149 11,883 Res Incremental Market Potential 464 489 495 526 559 585 603 615 622 624 Non-Res Incremental Market Potential 8,680 9,570 10,567 11,526 12,320 12,800 13,096 13,098 12,527 11,259 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.34% 0.37% 0.41% 0.44% 0.46% 0.47% 0.48% 0.48% 0.45% 0.41% Res Incremental Potential as a%of Res Sales 0.05% 0.05% 0.05% 0.05% 0.06% 0.06% 0.06% 0.06% 0.06% 0.06% Non-Res Incremental Potential as a%of Non-Res Sales 0.49% 0.54% 0.59% 0.63% 0.67% 0.69% 0.70% 0.69% 0.65% 0.58% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 2,181 2,374 2,640 2,972 3,287 3,242 3,344 3,371 3,313 3,155 Res Incremental Market Potential 173 176 176 179 182 184 186 188 190 192 Non-Res Incremental Market Potential 2,008 2,197 2,464 2,793 3,105 3,058 3,158 3,182 3,122 2,963 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-55. Inputs to Figure 1 Source:Navigant 2016 At a glance, Modesto's results include: • A 2018-2027 average annual target of 0.43% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Modesto begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.53 Table 4-56. Top 10 Energy Saving Measures for 2017 1 Food-Efficient MachDr Equipment 789 51.7 7.6% 2.0% 2 Stone-Glass-Clay-Efficient MachDr Equipment 687 84.6 6.6% 3.2% 3 Food-Efficient Lighting Equipment 354 36.5 3.4% 1.4% 4 Daries-Efficient Process Mtr Equipment-Mid Cost 322 25.3 3.1% 1.0% Com-New-Electronically Commutated(EC)Motor w/Fan Cycling Controls 5 for Cold Storage Evaporator Fans 316 36.1 3.0% 1.4% 6 Com-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 315 80.7 3.0% ° Watts 3.1/° 7 Daries-Efficient Process Mtr Equipment-Low Cost 299 16.7 2.9% 0.6% 8 Stone-Glass-Clay-Efficient Lighting Equipment 281 34.4 2.7% 1.3% 9 Com-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts. 279 70.8 2.7% 2.7% 10 Corn-Office-Retro-commissioning 236 0.0 2.3% 0.0% Source:Navigant 2016 53 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-57. Top 10 Energy Saving Measures for 2030 Corn-New-Electronically Commutated(EC)Motor w/Fan Cycling Controls ° 1.6% 1 for Cold Storage Evaporator Fans 409 46:7 5.3/° 2 Food-Efficient MachDr Equipment 387 25.4 5.0% 0.9% 3 Stone-Glass-Clay-Efficient MachDr Equipment 384 47:3 5.0% 1.7% 4 Com-Retail-WholeBlg-Corn RET Level 2 262 85.4 3.4% 3.0% 5 Com-Office-Retro-commissioning 239 0.0 3.1% 0.0% 6 Food-Efficient Lighting Equipment 239 24.6 3.1% 0.9% 7 Com-Office-WholeBlg-Corn RET Level 2 233 97.3 3.0% 3.4% 8 Corn-New-Electronically Commutated(EC)Walk-In Evaporator Fan Motor 195 22.3 2.5% 0.8% 9 Corn-Retail-LED fixture:33W,3500 lumens 148 37.6 1.9% 1.3% 10 Res-Single Family-Refrigerator Recycling 145 29.2 1.9% 1.0% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Modesto to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Modesto's current 10- year goals are about 63% of the goals established in the prior study. The primary reason is calibration. The 2012 calibration targets were set at 1% of sales, though historical program achievements for the three years before the targets were about 40% lower. In 2016, Modesto used an average of the actual savings from 2013 through 2015 for calibration. NAVIGANT To: Moreno Valley Utility From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Moreno Valley Utility with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Moreno Valley service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 37. Base Case Run. This modeling run includes no changes or adjustments to Moreno Valley's current portfolio of energy efficiency programs. 38. Final Run. This modeling run uses Moreno Valley's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.54 Moreno Valley's Final Run included the following adjustments to their Base Case Run: • A 50% reduction to baseline densities to account for the relatively newer age of homes and buildings in their service territory • A 50% reduction to the impacts of the behavioral program • Increased administrative costs by 1.5 • Adjustments to the photovoltaic (PV)forecasts based on actual Moreno Valley data • Inclusion of a revised sales forecast Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 54 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT ' 2,000 1.029, 1,800 0.90% 1.II 0.80% iV 0.00% 2018 2019 2010 2021 2022 2023 2024 2015 2026 2027 11118•Res Incremental Market Potential imml Non-Res Incremental Market Potential 1111111111C&5(If Claimed.Estimates not available atter 2024) --Total Incremental Potential as a%of Total Sales Figure 21. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,734 1,748 1,752 1,630 1,427 1,227 1,106 1,007 909 833 Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Incremental Market Potential 752 753 761 761 617 501 417 354 290 245 C&S(If Claimed.Estimates not available after 2024) 982 994 991 869 809 726 689 653 620 588 Total Incremental Potential as a%of Total Sales 0.87% 0.87% 0.86% 0.79% 0.69% 0.59% 0.52% 0.47% 0.42% 0.38% Res Incremental Potential as a%of Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% Non-Res Incremental Potential as a%of Non-Res Sales 0.46% 0.46% 0.46% 0.45% 0.36% 0.29% 0.24% 0.20% 0.16% 0.14% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 413 419 416 400 359 321 296 275 255 239 Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Incremental Market Potential 164 163 164 164 132 104 85 72 58 48 C&S(If Claimed.Estimates not available after 2024) 249 256 252 236 228 218 210 204 197 191 Table 4-58. Inputs to Figure 1 Source:Navigant 2016 At a glance, Moreno Valley's results include: • A 2018-2027 average annual target of 0.65% of forecasted retail sales • Net savings targets • Only codes and standards (C&S) that are currently in place today, and not future C&S such as updates to Title 24 • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Moreno Valley begins to allocate program dollars in new directions. Table 3 shows the top 10 energy saving measures for the first year of the forecast period and Table 4 shows the top 10 measures for year 2030 to use as a comparison.55 Table 4-59. Top 10 Energy Saving Measures for 2017 1 Com-Retail-LED fixture:33W,3500 lumens 131 32.2 17.4% 18.2% 2 Com-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 82 20.3 11.0% 11.5% 3 Other Industrial-Efficient Lighting Equipment 79 7.6 10.5% 4.3% 4 Corn-Retail-LED T8 Tube Replacement Average Fixture Wattage 59.65 67 16.6 9.0% 9.4% 5 Food-Efficient Lighting Equipment 33 3.4 4.4% 1:9% 6 Com-Retail-Reduced Wattage T8 Lamp and Ballast Average Fixture 30 7.4 4.0% 4.2% Wattage 72.23 7 Corn-Retail-LED parking lot fixture (existing V12250) 25 5.6 3.4% 3.2% 8 Com-Retail-LED downlight fixture,9-15W,interior Average 9 Watts 25 6.1 3.3% 3.5% 9 Com-Office-LED fixture:33W,3500 lumens 24 r 9.5 3.2% 5.4% 10 Corn-Restaurant-LED downlight,screw-in lamp,1-3W,interior Average 2 18 4.5 2.4% 2.6% Watts Source:Navigant 2016 55 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-60. Top 10 Energy Saving Measures for 2030 1 Other Industrial-Efficient Lighting Equipment 22 2.1 19.1% 6.3% 2 Com-New-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 20 4.5 17.7% 13.2% 3 Com-New-LED fixture:33W,`3500 lumens 14 3.2 12.5% 9.4% 4 Corn-Retail-Refrigerated Display Case with Doors,EC Evaporative Fan 6 0.6 5.3% 1.8% Motors,T8 Lamps with Electronic Ballast 5 Com-ALL-Smart Power Strip-Commercial Use 4 1.1 3:8% 3.1% 6 Food-Efficient Lighting Equipment 4 0.4 3.3% 1.2% 7 Other Industrial-Efficient Lighting O&M 4 1.5 3.2% 4.3% 8 Com-New-LED downlight,screw-in lamp,4-20W,interior Average 11 Watts 3 0.7 2.7% 2.0% 9 Com-New-LED downlight fixture,9-15W,interior Average 9 Watts 3 0.7 2.6% 2.0% 10 Com-New-Reduced Wattage T8 Lamp and Ballast Average Fixture 3 0.6 2.6% 1.9% Wattage 72.23 Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Moreno Valley to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Moreno Valley's current 10-year goals are nearly 5-times greater than the goals established in the prior study. The primary reasons are model calibration and increased promotional activities. The current model is calibrated to 2015 actual program achievements and this calibration target is over 2.5 larger than the earlier model version. Additionally, the current model increases program promotional activities by 50% beginning in 2018. NAVIGANT To: City of Needles From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides the City of Needles with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Needles service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 39. Base Case Run. This modeling run includes no changes or adjustments to Needles's current portfolio of energy efficiency programs. 40. Final Run. This modeling run uses Needles's chosen adjustments—if any—to various features within the model to illustrate alternative energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.56 Needles chose to expand the list of measures modeled in ELRAM to include a number of ENERGY STAR®Appliances as they look to add these technologies to their program offerings. 56 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 22. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 35 0.05% 30 005% 25 0.04% u 20 Ti aoa% t 15 O.bJt% 9 4 10 $ g 5 o.o 0III 0.00% 2018 2019 2020 7021 2022 2023 2.0)4 7025 2076 7077 IMP Res Incremental Market Potential >♦Nan Res Incremental Market Potential -4-Total Incremental Potential as a%ot Total Sates Table 4-61. Inputs to Figure 1 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 19 20 22 25 27 29 27 21 15 10 Res Incremental Market Potential 19 20 22 25 27 29 27 21 15 9 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.04% 0.04% 0.04% 0.05% 0.05% 0.05% 0.05% 0.04% 0.03% 0.02% Res Incremental Potential as a%of Res Sales 0.30% 0.31% 0.33% 0.37% 0.40% 0.43% 0.39% 0.30% 0.21% 0.14% Non-Res Incremental Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 19 20 21 24 26 27 24 18 13 7 Res Incremental Market Potential 17 17 18 21 23 25 22 16 11 5 Non-Res Incremental Market Potential 2 2 3 3 3 2 2 2 2 2 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Needles's results include: • A 2018-2027 average annual target of 0.04% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Needles begins to allocate program dollars in new directions. Table 3 shows the top 10 energy saving measures for the first year of the forecast period and Table 4 shows the top 10 measures for year 2030 to use as a comparison.57 Table 4-62. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-Evaporative Cooler SEER 17.4, 15.1 EER 15 13.5 73.3% 44.3% 2 Res-Multi Family-Evaporative Cooler SEER 17.4, 15.1 EER 2 2.2 10.3% 7.2% 3 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 1 0.8 5.5% 2.5% 4 Res-Single Family-Residential Solar Screen 1 0.5 3.8% 1.8% 5 Res-Multi Family-Reflective Window Film(reduces SHGC to 0.39) 0 0.1 0.6% 0.3% 6 Res-Single Family-HP Clothes Dryer-Emerging 0 0.0 0.5% 0.1% 7 Res-Multi Family-Residential Solar Screen 0 0.1 0.4% 0.2% 8 Res-Single Family-CEE Tier Ill Refrigerator(from 30$to 35%more 0 0.0 0.3% 0.0% efficient) 9 Res-Single family-CEE Tier II Refrigerator 0 0.0 0.2% 0.0% 10 Res-Single Family-Split System AC SEER 18 to 22, 13 EER 0 0.0 0.2% 0.1% Source:Navigant 2016 57 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-63. Top 10 Energy Saving Measures for 2030 'I Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 3 2.4 37.2% 13.5% 2 Res-Single Family-Residential Solar Screen 2 1.7 26.2% 9.5% 3 Res-Multi Family-Reflective Window Film(reduces SHGC to 0.39) 0 0.3 4.3% 1.6% 4 Res-Single Family-CEE Tier II Refrigerator 0 0.0 4.0% 0.0% 5 Res-Single Family-HP Clothes Dryer-Emerging 0 0.1 3.9% 0.3% 6 Res-Multi Family-Residential Solar Screen 0 0.2 3.1% 1.1% 7 Res-Single Family-ENERGY STAR Dishwasher(1.0 to 1.19 EF, 0 0.0 2.4% 0.0% Compact,Elec DHW) 8 Res-Single Family-CEE Tier Ill Refrigerator(from 30$to 35%more 0 0.0 2.1% 0.0% efficient) 9 Res-Multi Family-ENERGY STAR Dishwasher(1.0 to 1.19 EF, 0 0.0 1.3% 0.00/0 Compact,Elec DHW) 10 Res-Multi Family-CEE Tier II Refrigerator 0 0.0 1.1% 0.0% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Needles to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Needles's current 10-year goals are about 20% of the goals established in the prior study. The primary reason is model calibration. In the earlier version, the calibration target was set above actual historical achievements. The calibration target for the current model reflects actual levels of program achievement. NAVIGANT To: City of Palo Alto From: Navigant Consulting, Inc. Date: February 22, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides the City of Palo Alto with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Palo Alto service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 41. Base Case Run. This modeling run includes no changes or adjustments to Palo Alto's current portfolio of energy efficiency programs. 42. Final Run. This modeling run uses Palo Alto's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.58 Palo Alto's Final goals were manually selected based on the following adjustments to their Base Case Run: • 3-5 year persistence of RCx savings (Palo Alto currently only claims 1 year) • Starting in 2018 10% of the Commercial floorspace reached each year by Building Operator Certification Behavioral Program • Early Retirement for Residential, Commercial, and Industrial starting in 2018 • All new cost-effective measures are deployed J • 33% more budget for Marketing and Admin J • 33% more budget for Customer Incentives 58 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT • Financing program available Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the manually selected final target selection. Figure 23. Net Incremental Market Potential by Sector(MWh) and Percent of Sales-FINAL Incremental Market Potential by Sector 10j 000 All Sectors Energy Potential(MWh)and%of Sales 1.00% 0.909E 0.80%. 0.7096TN0.60%0.50. ,040% ia 3azo%.a00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 IIIIII Res Incremental Market Potential MN Non-Res Incremental Market Potential MINI C&S(If Claimed Estimates not available after 2024) —0—Total Incremental Potential as a 96 of Total Sales Table 4-64. Inputs to Figure 1 ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 7,280 7,284 7,760 7,757 8,253 8,146 8,631 8,647 9,139 9,152 Res Incremental Market Potential 1,879 1,802 1,804 1,768 1,924 1,997 2,209 2,245 2,433 2,570 Non-Res Incremental Market Potential 5,401 5,482 5,956 5,989 6,330 6,149 6,421 6,402 6,706 6,581 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 _-_ 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.75% 0.75% 0.80% 0.80% 0.85% 0.85% 0.90% 090% 0.95% 0.95% Res Incremental Potential as a%of Res Sales 0.19% 0.19% 0.19% 0.18% 0.20% 0.21% 0.23% 0.23% 0.25% 0.27% Non-Res Incremental Potential as a%of Non-Res Sales 0.56% 0.56% 0.61% 0.62% 0.65% 0.64% 0.67% 0.67% 0.70% 0.68% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,697 1,698 1,783 1,785 1,925 1,865 1,865 1,684 1,587 1,580 Res Incremental Market Potential 113 109 99 103 125 126 147 149 162 170 Non-Res Incremental Market Potential 1,584 1,589 . 1,684 1,682 1,800 1,740 1,718 1,535 1,426 1,410 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Palo Alto's results include: • A 2018-2027 average annual target of 0.85% of forecasted retail sales • Net savings targets • C&S not claimed NAVIGANT • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life • New measures • Commercial Sector Behavioral Program • Higher incentives by 33% • Higher promotional expenditures by 33% • Financing program offered Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Palo Alto begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.59 Table 4-65. Top 10 Energy Saving Measures for 2017 1 Com-Office-Retro-commissioning 546 0.0 11.4% 0.0% 2 Com-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 247 24.4 5.2% 1.4% 3 Com-Office-Thermostat Replacement 146 0.0 3.1% 0.0% 4 Com-Office- -Comprehensive Rooftop Unit Quality Maintenance(AC Tune- 125 73.7 2.6% 4.3% up 5 Res-SF New-T24 15%Stretch Goal.Compliant Home 114 89.8 2.4% 5.2% 6 Electronics-Efficient Lighting Equipment 111 13.9 2.3% 0.8% 7 Corn-Retail-LED downlight,screw-in lamp,1-3W,interior Average 2 Watts 94 23.3 2.0% 1.4% 8 Corn-Retail-LED fixture:33W,3500 lumens 93 22.9 1.9% 1.3% 9 Com-Office-Demand Controlled Ventilation 89 5.3 1.9% 0.3% 10 Com-Office-Retro-commissioning 83 0.0 1.7% 0.0% Source:Navigant 2016 59 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-66. Top 10 Energy Saving Measures for 2030 1 Corn-Office-Retro-commissioning 483 0.0 18.9% 0.0% 2 Corn-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 192 19.0 7.5% 2.1% 3 Res-Single Family-Refrigerator Recycling 99 19.8 3.8% 2.1% 4 Corn-Office-Electronically Commutated(EC)Motor w/Fan Cycling Controls 85 9.8 3.3% 1.1% for Cold Storage Evaporator Fans 5 Com-Office-Retro-commissioning 81 0.0 3.1% 0.0% 6 Com-Office-Commercial SEER-rated Packaged Air Conditioners,SEER= 78 45.4 3.0% 4.9% 15(EER= 12.9) 7 Com-Retail-Electronically Commutated(EC)Motor w/Fan Cycling Controls 76 8.7 3.0% 0.9% for Cold Storage Evaporator Fans 8 Com-Health-Electronically Commutated(EC)Motor w/Fan Cycling Controls 55 6.3 2.2% 0.7% for Cold Storage Evaporator Fans 9 Res-Single Family-Shade Tree 49 0.0 1.9% 0.0% 10 Com-Office-Electronically Commutated(EC)Walk-In Evaporator Fan Motor 47 5.4 1.8% 0.6% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Palo Alto to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Palo Alto's current 10- year goals are about 144% of the goals established in the prior study. There are several reasons for these higher goals: • Increased incentives and promotional expenses • The 2012 goals did not include either Residential or Commercial Behavioral Programs, which are now included in the targets • Transition from Replace on Burnout to Early Retirement, where appropriate • New measures • Offers a financing program • Early Retirement measures • The forecast of sales in 2016 is about 5% lower than the forecast of sales in 2012 NAVIGANT To: Pasadena Water&Power From: Navigant Consulting, Inc. Date: February 5, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Pasadena Water& Power with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Pasadena service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 43. Base Case Run. This modeling run includes no changes or adjustments to Pasadena's current portfolio of energy efficiency programs. 44. Final Run. This modeling run uses Pasadena's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.6o Pasadena chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 60 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 24. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 15000 2110% II 20,000 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 IMO Res Incremental Market Potenttal III=Non Res Incremental Market Potential IMOC&S(If Claimed) -4-I otal Incremental Potential as a'k of total Sales Table 4-67. Inputs to Figure 1 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 20,087 20,028 19,570 19,546 19,735 19,640 19,373 18,636 17,118 15,275 Res Incremental Market Potential 7,060 7,187 6,824 6,968 7,101 7,236 7,316 7,426 7,448 7,474 Non-Res Incremental Market Potential 6,786 6,883 7,133 7,699 8,147 8,428 8,306 7,670 6,330 4,650 C&S(If Claimed) 6,241 5558 5,613 4,880 4,487 3,976 3,751 3539 3,340 3,151 Total Incremental Potential as a%of Total Sales 1.84% 1.86% 1.82% 1.82% 1.83% 1.82% 1.79% 1.72% 1.58% 1.41% Res Incremental Potential as a%of Res Sales 2.30% 2.38% 2.26% 2.30% 2.34% 2.39% 2.41% 2.44% 2.45% 2.46% Non-Res Incremental Potential as a%of Non-Res Sales 0.88% 0.89% 0.92% 0.99% 1.05% 1.09% 1.07% 0.99% 0.81% 0.60% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 5,101 5,123 5,101 5,125 5,200 5,251 5,271 1,084,491 1,039,493 996,294 Res Incremental Market Potential 201 221 197 210 223 236 246 257 261 264 Non-Res Incremental Market Potential 3,368 3,421 3,479 3,595 3,725 3,839 3,898 3,772 3,472 3,090 C&S(If Claimed) 1,532 1,482 1,426 1,319 1,252 1,177 1,127 1,080,462 1,035,761 992,940 Source:Navigant 2016 At a glance, Pasadena's results include: • A 2018-2027 average annual target of 1.75% of forecasted retail sales • Net savings targets • Only codes and standards (C&S)that are currently in place today, and not future C&S such as updates to Title 24 • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Pasadena begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.61 Table 4-68. Top 10 Energy Saving Measures for 2017 1 Corn-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 1,261 124.9 16.3% 8.6% 2 Corn-Office-LED fixture: 33W,3500 lumens 420 168.8 5.4% 11.6% 3 Com-Other-Thermostat Replacement 231 0.0 3.0% 0.0% 4 Com-Office-Thermostat Replacement 181 0.0 2.3% 0.0% 5 Com-Office-Bi-Level Lighting Fixture-Stairwells,Hallways,and Garages 179 2.1 2.3% 0.1% 6 Corn-ALL-Smart Power Strip-Commercial Use 177 42.9 2.3% 3.0% 7 Res-Single Family-LED Indoor Screw-in Lamp-Low Wattage-8 watt avg. 166 13.8 2.1% 1.0% 8 Com-Other-LED fixture:33W,3500 lumens 161 118.8 2.1% 8.2% 9 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 159 13.2 2.1% 0.9% 10 Com-Office-Window Film 152 86.0 2.0% 5.9% Source:Navigant 2016 61 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-69. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 252 21.0 7.2% 2.8% 2 Res-Single Family-LED Indoor Reflector Downlight-12 watt avg. 250 20.8 7.1% 2.8% 3 Com-Grocery-LED downlight,screw-in lamp, 1-3W,interior Average 2 240 42.5 6.9% 5.6% Watts 4 Corn-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 166 42.2 4.7% 5.6% Watts 5 Corn-Other-Demand Controlled Ventilation 151 21.5 4.3% 2.8% 6 Res-Low Income-Refrigerator Recycling 123 24.8 3.5% 3.3% 7 Com-Other-LED fixture:33W,3500 lumens 114 83.9 3.3% 11.1% 8 Corn-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 Watts 103 25.4 2.9% 3.4% 9 Res-Single Family-Refrigerator Recycling 94 18.8 2.7% 2.5% 10 Res-Single Family-CEE Tier III Refrigerator(from 30$to 35%more 85 0.0 2.4% 0.0/°° efficient) Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Pasadena to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Pasadena's current 10- year goals are about 195% of the goals established in the prior study. There are two reasons for these higher goals: • The 2016 calibration target includes a residential behavioral program that was not included in the 2012 study. • The forecast of sales in 2016 is about 15% lower than the forecast of sales in 2012. NAVIGANT To: Pittsburg Power From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Pittsburg Power with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Pittsburg service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 45. Base Case Run. This modeling run includes no changes or adjustments to Pittsburg's current portfolio of energy efficiency programs. 46. Final Run. This modeling run uses Pittsburg's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.62 Pittsburg's Final Run included the following adjustments to their Base Case Run: • Expanded measure list. Navigant modeled a number of measures—not currently offered in Pittsburg's portfolio—to provide a picture of potential savings should Pittsburg decide to expand their current programs. Pittsburg added some residential and non- residential measures to their programs. Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 62 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT Figure 25. Net Incremental Market Potential by Sector(MWh) and Percent of Sales-FINAL RUN 140 OW% 120 0.50?: 1W 0.40% E 80 c Lo 3 0.30% 60 El K J 40 0.10% 20 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 1♦Total Incremental Pntrntial ac a%of Total Sales Non Res I ncrerrerttal Market Potential -0-Total Incremental Potential an a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 119 105 94 86 79 72 68 62 58 55 Res Incremental Market Potential 44 4 4 5 5 5 5 5 6 Non-Res Incremental Market Potential 115 101 90 82 74 68 63 57 52 49 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.49% 0.43% 0.37% 0.34% 0.31% 0.28% 0.26% 0.23% 0.21% 0.20% Res Incremental Potential as a%of Res Sales 0.19% 0.21% 0.21% 0.22% 0.23% 0.24% 0.25% 0.25% 0.26% 0.26% Non-Res Incremental Potential as a%of Non-Res Sales 0.50% 0.43% 0.38% 0.34% 0.30% 0.27% 0.25% 0.22% 0.20% 0.19% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 23 19 17 15 14 13 12 11 11 10 Res Incremental Market Potential 1 1 1 1 1 1 1 1 1 1 Non-Res Incremental Market Potential 22 18 16 15 13 12 11 109 9 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-70. Inputs to Figure 1 Source:Navigant 2016 At a glance, Pittsburg's results include: • A 2018-2027 average annual target of 0.31% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • Add new residential and non-residential sector measures NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Pittsburg begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.63 Table 4-71. Top 10 Energy Saving Measures for 2017 1 Com-Education-LED fixture:33W,3500 lumens 23 2.7 15.3% 6.2% 2 Corn-Office-LED fixture: 33W,3500 lumens 12 4.8 7.9% 10.9% 3 Com-Education-LED T8 Tube Replacement Average Fixture Wattage 12 1.4 7.9% 3.2% 59.65 4 Com-Education-Bi-Level Lighting Fixture-Stairwells,Hallways,and 9 0.1 6.4% ° Garages 0.3/° 5 Corn-Office-Bi-Level Lighting Fixture-Stairwells,Hallways,and 7 0.1 4.9% 0.2% Garages 6 Fabricated Metals-Efficient Lighting Equipment 6 1.3 4.3% 3.0% 7 Com-Office-LED T8 Tube Replacement Average Fixture Wattage 59.65 6 2.5 4.1% 5.6% 8 Corn-Education-Reduced Wattage T8 Lamp and Ballast Average 6 0.7 3.7% 1.5% Fixture Wattage 72.23 9 Com-Education-LED wallpack(existing W<250) 5 0.3 3.6% 0.6% 10 Com-Education-LED downlight fixture,9-15W,interior Average 9 Watts 5 0.6 3.3% 1.3% Source:Navigant 2016 63 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Table 4-72. Top 10 Energy Saving Measures for 2030 1 Com-New-LED downlight,screw-in lamp, 1-3W,interior Average 2 7 1.5 12.1% 6.3% Watts 2 Corn-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 5 0.5 9.2% 2.1% 3 Com-Education-Retro-commissioning 4 0.0 7.9% 0.0% 4 Com-Office-Retro-commissioning 4 0.0 7.1% 0.0% 5 Com-Education-WholeBlg-Corn RET Level 2 3 0.6 5.5% 2.7% 6 Corn-Office-WholeBlg-Corn RET Level 2 2 0.9 4.0% 3.9% 7 Corn-Education-WholeBlg-Corn RET Level 1 2 0.3 3.0% 1.5% 8 Corn-Office-WholeBlg-Corn RET Level 1 1 0.5 2.3% 2.1% 9 Fabricated Metals-Efficient MachDr O&M 1 0.1 2.3% 0.6% 10 Res-Single Family-Whole House Fan 1 0.0 2.0% 0.0% Source:Navigant 2016 NAVIGANT Other Features Navigant worked with Pittsburg to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT Table 4-105. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-High Efficiency Electric Storage Water Heater(0.93 EF-50 4 0.3 38.2% 2.1% gallon) 2 Res-Multi Family-Heat Pump Water Heater(>2.0 EF-50 Gallon) 2 0.5 25.2% 3.3% 3 Res-Single Family-Heat Pump Water Heater(>2.0 EF-50 Gallon) 2 0.4 21.9% 2.7% 4 Res-Multi Family-High Efficiency Electric Storage Water Heater(0.93 EF-50 0 0.0 5.3% 0.3% gallon) 5 Res-MF New-Heat Pump Water Heater(>2.0 EF-50 Gallon) 0 0.0 2.4% 0.3% ' 6 Res-SF New-Heat Pump Water Heater(>2.0 EF-50 Gallon) 0 0.0 1.5% 0.2% 7 Res-SF New-High Efficiency Electric Storage Water Heater(0.93 EF-50 gallon) 0 0.0 0.2% 0.0% 8 Res-MF New-High Efficiency Electric Storage Water Heater(0.93 EF-50 gallon) 0 0.0 0.2% 0.0% 9 Com-Data Center-Server Equipment Upgrades 0 0.9 -0.0% 5.6% 10 Com-Data Center-Server Monitoring&Controls 0 0.9 0.0% 5.6% Source:Navigant 2016 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Trinity begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.84 Table 4-104. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-Heat Pump Water Heater(>2.0 EF-50 Gallon) 8 1.8 57.0% 10.6% 2 Res-Single Family-High Efficiency Electric Storage Water Heater(0.93 EF-50 3 0.3 21.2% 1.8% gallon) 3 Res-Multi Family-Heat Pump Water Heater(>2.0 EF-50 Gallon) 2 0.5 15.0% 2.9% 4 Res-Multi Family-High Efficiency Electric Storage Water Heater(0.93 EF-50 0 0.0 2.2% 0.2% gallon) 5 Res-SF New-Heat Pump Water Heater(>2.0 EF-50 Gallon) 0 0.0 0.6% 0.1% 6 Res-MF New-Heat Pump Water Heater(>2.0 EF-50 Gallon) 0 0.0 0.6% 0.1% 7 Res-SF New-High Efficiency Electric Storage Water Heater(0.93 EF-50 gallon) 0 0.0 0.1% 0.0% 8 Res-MF New-High Efficiency Electric Storage Water Heater(0.93 EF-50 gallon) 0 0.0 0.0% 0.0% 9 Com-Data Center-Server Equipment Upgrades 0 0.9 0.0% 5.2% 10 Com-Data Center-Server Monitoring&Controls 0 0.9 0.0% 5.2% Source:Navigant 2016 84 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Figure 36. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 7 0.01% 7 0.01% 0.01% 6 0.01% ji c 60IYJ% L 6 O.U64P � 6 %a U-U°r 6 0.0 5 0.CO% 2018 2019 2020 2021 2022 2023 2024 2021 2026 2027 t♦total incremental Potential as a%of total Sales Non-Res Incremental Market Potential ♦-Iotal lncrementdl Potential as a%of total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 7 6 6 6 6 6 6 6 6 6 Res Incremental Market Potential 7 6 6 6 6 6 6 6 6 6 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% Res Incremental Potential as a%of Res Sales 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% 0.01% Non-Res Incremental Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00%. 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1 1 1 1 1 1 1 1 1 1 Res Incremental Market Potential 1 1 1 1 1 1 1 1 1 1 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0. 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-103. Inputs to Figure 1 Source:Navigant 2016 At a glance, Trinity's results include: • A 2018-2027 average annual target of 0.01% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) NAVIGANT To: Trinity Public Utility District From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Trinity Public Utility District with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Trinity service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 67. Base Case Run. This modeling run includes no changes or adjustments to Trinity's current portfolio of energy efficiency programs. 68. Final Run. This modeling run uses Trinity's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.83 Trinity chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 83 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Silicon Valley Power's current 10-year goals are about 87% of the goals established in the prior study even though it did add new measures to its portfolio. The primary reason is model calibration. In the earlier version, the calibration target was set as a percent of sales, which was above actual historical achievements. The calibration target for the current model reflects actual levels of program achievement in 2015. NAVIGANT Other Features Navigant worked with Silicon Valley Power to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include CSS Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement).This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT Table 4-102. Top 10 Energy Saving Measures for 2030 1 Electronics-Efficient Lighting Equipment 1,385 173.3 22.8% 14.4% 2 Corn-Office-WholeBlg-Corn RET Level 2 260 108.6 4.3% 9.0% 3 Com-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 243 24.0 4.0% 2.0% 4 Corn-Office-Bi-Level Lighting Fixture-Stairwells,Hallways,and 185 2.1 3.0% 0.2% Garages 5 Com-Office-LED T8 Tube Replacement Average Fixture Wattage 59.65 183 74.8 3.0% 6.2% 6 Corn-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 181 47.2 3.0% 3.9% Watts 7 Corn-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 168 41.5 2.8% 3.4% Watts 8 Com-Office-WholeBlg-Corn RET Level 1 149 58.8 2.5% 4.9% 9 Res-Single Family-Refrigerator Recycling 139 28.0 2.3% 2.3% 10 Electronics-Efficient MachDr Equipment 136 16.5 2.2% 1.4% Source:Navigant 2016 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Silicon Valley Power begins to allocate program dollars in new directions. Table 3 shows the top 10 energy saving measures for the first year of the forecast period and Table 4 shows the top 10 measures for year 2030 to use as a comparison.82 Table 4-101. Top 10 Energy Saving Measures for 2017 1 Electronics-Efficient Lighting Equipment 1,796 224.8 12.3% 0.0% 2 Electronics-Efficient MachDr Equipment 1,595 194.0 10.9% 0.0% 3 Electronics-Efficient HVAC Equipment 1,492 165.5 10.2% 0.0% 4 Corn-Office-LED fixture:33W,3500 lumens 949 388.2 6.5% 0.0% 5 Chemicals-Efficient MachDr Equipment 535 33.3 3.7% 0.0% 6 Stone-Glass-Clay-Efficient MachDr Equipment 489 60.3 3.4% 0.0% 7 Com-Data Center-Server Monitoring&Controls 369 330,021.3 2.5% 41.4% 8 Com-Retail-LED fixture: 33W,3500 lumens 334 82.3 2.3% 0.0% 9 Stone-Glass-Clay-Efficient Lighting Equipment 317 38.7 2.2% 0.0% 10 Corn-Office-Bi-Level Lighting Fixture-Stairwells,Hallways,and 296 3.4 2.0% 0.0% Garages Source:Navigant 2016 82 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 35. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 16,000 0.5(1% 14.0510I r"..."111""fi • 0_d09� .51 12,000 10000 0.30'M t g 8.000 61100 0.20' a 0 47 4,000 0 10°v 7,000 0 0.00% 7018 7019 7070 7071 7072 7073 7024 7025 2076 7077 Min Res Incremental Market Potential IMP Non Ret Incremental Market Potential —0-Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 12,851 13,032 14,015 14,928 15,129 14,565 13,333 12,192 11,528 10,590 Res Incremental Market Potential 205 238 277 328 371 383 388 392 395 397 Non-Res Incremental Market Potential 12,646 12,794 13,738 14,600 14,758 14,182 12,945 11,800 11,132 10,193 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.42% 0.43% 0.46% 0.48% 0.48% 0.46% 0.42% 0.38% 0.36% 0.33% Res Incremental Potential as a%of Res Sales 0.09% 0.10% 0.12% 0.14% 0.15% 0.16% 0.16% 0.16% 0.16% 0.16% Non-Res Incremental Potential as a%of Non-Res Sales 0.45% 0.45% 0.48% 0.51% 0.51% 0.49% 0.44% 0.40% 0.38% 0.34% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 572,845 523,147 524,930 541,304 546,184 447,497 355,679 49,371 24,884 8,915 Res Incremental Market Potential 25 29 32 34 35 36 37 38 38 38 Non-Res Incremental Market Potential 572,820 523,118 524,898 541,270 546,149 447,461 355,642 49,334 24,846 8,876 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Table 4-100. Inputs to Figure 1 Source:Navigant 2016 At a glance, Silicon Valley Power's results include: • A 2018-2027 average annual target of 0.42% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • Add new commercial sector measures • Increase measure incentives by 10% NAVIGANT To: Silicon Valley Power From: Navigant Consulting, Inc. Date: January 26, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Silicon Valley Power with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Silicon Valley Power service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 65. Base Case Run. This modeling run includes no changes or adjustments to Silicon Valley Power's current portfolio of energy efficiency programs. 66. Final Run. This modeling run uses Silicon Valley Power's chosen adjustments—if any— to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.81 Silicon Valley Power's Final Run included the following adjustments to their Base Case Run: • Expanded measure list. Navigant modeled a number of measures—not currently offered in Silicon Valley Power's portfolio—to provide a picture of potential savings should Silicon Valley Power decide to expand their current programs. After review, Silicon Valley Power added the following commercial sector measures to their program portfolio: - Retro-commissioning - Pump and Fan Variable Frequency Drive Controls - Whole Building Retrofit - Comprehensive Rooftop Unit Quality Maintenance (AC Tune-up) • Increased incentives by 10%. 81 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Shasta Lake's current 10- year goals are about 250% of the goals established in the prior study. There are several reasons for these higher goals: • Shasta Lake has been achieving program savings above the 2012 targets, which increased the calibration targets for 2016 • Additional new measures in all sectors • For appropriate measures, early retirement modeling assumptions made NAVIGANT Other Features Navigant worked with Shasta Lake to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. F NAVIGANT Table 4-99. Top 10 Energy Saving Measures for 2030 1 Food-Efficient MachDr Equipment 39 2.6 14.0% 3.2% 2 Food-Efficient MachDr O&M 32 3.0 11.4% 3.7% 3 Res-Single Family-Shade Tree 13 0.0 4.5% 0.0% 4 Res-Single Family-Refrigerator Recycling 11 2.2 3.9% 2.7% 5 Res-Single Family-Whole House Fan 10 0.0 3.4% 0.0% 6 Res-Single Family-CEE Tier III Refrigerator(from 30$to 35% 9 0.0 3.4% 0.0% more efficient) 7 Res-Single Family-Solar Attic Fan(1,000 CFM) 9 7.4 3.1% 9.1% 8 Res-Single Family-Wall Insulation(R-13) 8 0.0 2.9% 0.0% 9 Res-Single Family-GEE Tier II Refrigerator 8 0.0 2.8% 0.0% 10 Food-Efficient ProcRefrig O&M 8 0.7 2.8% 0.8% Source:Navigant 2016 NAVIGANT • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Shasta Lake begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.80 Table 4-98. Top 10 Energy Saving Measures for 2017 1 Food-Efficient Lighting Equipment 306 31.5 65.2% 36.3% 2 Other Industrial-Efficient Lighting Equipment 67 6.5 14.3% 7.5% 3 Res-Single Family-Split System AC Tuneup/Recharge 7 6.6 1.5% 7.6% 4 Res-Single Family-Wall Insulation(R-13) 6 0.0 1.3% 0.0% 5 Com-Other-Thermostat Replacement 6 0.0 1.2% 0.0% 6 Res-Single Family-Variable Speed Pool Pump 5 0.0 1.1% 0.0% 7 Com-Other-LED fixture:33W,3500 lumens 4 2.8 0.8% 3.2% 8 Corn-Education-LED fixture:33W,3500 lumens 4 0.4 0.8% 0.5% 9 Com-Other-Bi-Level Lighting Fixture-Stairwells,Hallways,and 4 0.0 0.8% 0.0% Garages 10 Com-Other-LED downlight,screw-in lamp, 1-3W,interior Average 3 2.4 0.7% 2.8% 2 Watts Source:Navigant 2016 80 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT 7011 0.40% 600 0.i5% 0.10% 111[1 I IM 500 0.15% ,n 401) 0 20% v 300 c 0.15% ; `n e. 200 0.10% 100 0.05% 0 U.W9e 7018 1019 7070 1071 7022 1013 7014 2075 7026 7027 OM Total Inuemental Potential as a%of total Sales MN Non Res Uxrernental Market Potential -•-totel Inuemental Potential as a%of total Sales Figure 34. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 487 519 550 579 600 635 635 601 551 482 Res Incremental Market Potential 74 90 107 128 154 185 186 156 125 100 Non-Res Incremental Market Potential 413 428 443 451 447 450 449 445 425 382 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.27% 0.27% 0/9% 0.30% 0.33% 0.33% 0.33% 0.32% 0.31% 0.28% Res Incremental Potential as a%of Res Sales 0.20% 0.23% 0.27% 0.32% 0.41% 0.47% 0.47% 0.39% 0.33% 0.28% Non-Res Incremental Potential as a%of Non-Res Sales 0.27% 0.28% 0.29% 0.32% 0.30% 0.30% 0.30% 0.31% 0.31% 0.30% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 1,763 76 78 79 79 79 80 81 82 81 Res Incremental Market Potential 24 26 26 28 29 30 31 33 35 39 Non-Res Incremental Market Potential 1,739 51 52 52 50 49 48 48 46 42 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-97. Inputs to Figure 1 Source:Navigant 2016 At a glance, Shasta Lake's results include: • A 2018-2027 average annual target of 0.30% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • Additional new measures in all sectors NAVIGANT To: City of Shasta Lake From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides the City of Shasta Lake with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Shasta Lake service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 63. Base Case Run. This modeling run includes no changes or adjustments to Shasta Lake's current portfolio of energy efficiency programs. 64. Final Run. This modeling run uses Shasta Lake's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.79 Shasta Lake's Final Run included the following adjustments to their Base Case Run: • Expanded measure list. Navigant modeled a number of measures—not currently offered in Shasta Lake's portfolio—to provide a picture of potential savings should Shasta Lake decide to expand their current programs. The modeling team used various sources and studies throughout California and the nation to inform this expanded measure list. • For appropriate measures, early retirement modeling assumptions made. Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 79 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. San Francisco's current 10-year goals are about 87% of the goals established in the prior study even though it did add new measures to its portfolio. The primary reason is model calibration. In the earlier version, the calibration target was set as a percent of sales, which was above actual historical achievements by more than double. The calibration target for the current model reflects actual levels of average program achievement in 2013, 2014, and 2015. NAVIGANT Other Features Navigant worked with San Francisco to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT Table 4-96. Top 10 Energy Saving Measures for 2030 1 Corn-Other-WholeBlg-Corn RET Level 2 205 95.6 9.6% 22.3% 2 Street Lighting-LED Streetlights 192 0.0 9.0% 0.0% 3 Com-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 178 17.7 8.3% 4.1% 4 Corn-Other-WholeBlg-Corn RET Level 1 138 48.6 6.5% 11.3% 5 Street Lighting-LED Streetlights with Advanced Controls 94 0.0 4.4% 0.0% 6 Com-Health-WholeBlg-Corn RET Level 2 60 13.8 2.8% 3.2% Com-Other-Commercial SEER-rated Packaged Air Conditioners,SEER 0 0 7 =15(EER=12.9) 51 32.3 2.4/0 7.5/0 8 Corn-Education-WholeBlg-Corn RET Level 2 47 10.0 2.2% 2.3% 9 Transportation Equipment Efficient Lighting Equipment 45 5.7 2.1% 1.3% 10 Com-Education-Retro-commissioning 45 0.0 2.1% 0.0% Source:Navigant 2016 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as San Francisco begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.78 Table 4-95. Top 10 Energy Saving Measures for 2017 1 Transportation Equipment-Efficient MachDr O&M 451 24.4 20.5% 13.1% 2 Corn-Other-Demand Controlled Ventilation 210 20.4 9.5% 10.9% 3 Transportation Equipment-Efficient MachDr Equipment 200 11.9 9.1% 6.4% 4 Street Lighting LED Streetlights 182 0.0 8.3% 0.0% 5 Com-Health-Demand Controlled Ventilation 145 5.0 6.6% 2.7% 6 Com-ALL-Smart Power Strip-Commercial Use 133 32.3 6.0% 17.3% 7 Street Lighting-LED Streetlights with Advanced Controls 89 0.0 4.0% 0.0% 8 Other Industrial-Efficient MachDr Equipment 76 11.7 3.4% 6.3% 9 Other Industrial-Efficient MachDr O&M 61 4.9 2.8% 2.6% 10 Corn-ALL-Plug-Load Occupancy Sensor 59 14.4 2.7% 7.7% Source:Navigant 2016 78 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Figure 33. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 3,000 0.30% :.'" 0.25% . 0.20% L t 0.IS% m r a 1.0000,10% o 500 0.05% 0 0,00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 IIIIINIRes Incremental Market Potential =II Non-Res Incremental Market Potential .41-Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 2,736 2,853 2,764 2,657 2,596 2,524 2,435 2,324 2,255 2,209 Res Incremental Market Potential 1 2 2 3 3 4 4 5 5 5 Non-Res Incremental Market Potential 2,735 2,851 2,762 2,654 2,593 2,520 2,431 2,320 2,250 2,204 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.27% 0.28% 0.27% 0.25% 0.25% 0.24% 0.23% 0.22% 0.21% 0.20% Res Incremental Potential as a%of Res Sales 0.01% 0.01% 0.01% 0.02% 0.02% 0.02% 0.03% 0.03% 0,03% 0.03% Non-Res Incremental Potential as a%of Non-Res Sales 0.26% 0.27% 0.26% 0.25% 0.24% 0.23% 0.22% 0.21% 0.21% 0.20% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 335 371 377 373 383 399 402 400 402 409 Res Incremental Market Potential 0 0 1 1 1 1 1 1 1 1 Non-Res Ihcremental Market Potential 335 371 377 372 382 398 401 398 401 407 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-94. Inputs to Figure 1 Source:Navigant 2016 At a glance, San Francisco's results include: • A 2018-2027 average annual target of 0.24% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • Measures added to the portfolio of measures offered • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline"function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life NAVIGANT To: San Francisco Public Utilities Commission Power Enterprise From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides San Francisco Public Utilities Commission Power Enterprise with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the San Francisco service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 61. Base Case Run. This modeling run includes no changes or adjustments to San Francisco's current portfolio of energy efficiency programs. 62. Final Run. This modeling run uses San Francisco's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings." San Francisco's Final Run included the following adjustments to their Base Case Run: • Expanded measure list. Navigant modeled a number of measures—not currently offered in San Francisco's portfolio—to provide a picture of potential savings should San Francisco decide to expand their current programs. The modeling team used various sources and studies throughout California and the nation to inform this expanded measure list. • For appropriate measures, early retirement modeling assumptions made. Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. "Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. SMUD's current 10-year goals are about 113% of the goals established in the prior study. The reasons for the higher level of savings include: • The inclusion of behavioral programs in the new study that were not part of the 2012 study • Savings from C&S included in 2016 but not in 2012 • The calibration for non-behavioral programs is lower in 2016 reflecting the aggressive nature of the SMUD programs with the resulting saturation of some measure categories • The load forecast is about 5% lower in 2016 • SMUD is claiming gross rather than net savings NAVIGANT Other Features Navigant worked with SMUD to•provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT Table 4-93. Top 10 Energy Saving Measures for 2030 1 Res-Low Income-LED Indoor Specialty Lamp-10 watt avg. 5,074 422.0 6.8% 0.3% 2 Res-Low Income-LED Indoor Reflector Downlight-12 watt avg. 4,683 389.5 6.3% 0.3% 3 Res-Single Family-Refrigerator Recycling 4,012 807.5 5.4% 0.7% 4 Corn-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 3,603 356.7 4.8% 0.3% 5 Com-Office-Retro-commissioning 2,729 0.0 3.6% 0.0% 6 Corn-Office-WholeBlg-Corn RET Level 2 2,394 1,001.3 3.2% 0.8% 7 Res-Low Income-LED Indoor Screw-in Lamp-Low Wattage-8 watt 2,222 184.8 3.0% 0.1% avg. 8 Res-Single Family-Whole House Fan 2,080 0.0 2.8% 0.0% 9 Corn-New-WholeBlg-Corn NC Level 3 1,829 280.6 2.4% 0.2% 10 Com-New-WholeBlg-Com NC ZNE 1,799 334.1 2.4% 0.3% Source:Navigant 2016 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as SMUD begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.76 Table 4-92. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 8,910 741.1 9.0% 0.6% 2 Res-Single Family-LED Indoor Reflector Downlight-12 watt avg. 7,896 656.8 8.0% 0.5% 3 Com-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 7,647 757.1 7.8% 0.6% 4 Res-Single Family-Variable Speed Pool Pump 5,198 0.0 5.3% 0.0% 5 Res-Low Income-LED Indoor Screw-in Lamp-Low Wattage-8 watt 5,177 430.6 5.3% 0.3% avg. 6 Res-Low Income-LED Indoor Specialty Lamp-10 watt avg. 3,938 327.5 4.0% 0.3% 7 Res-Low Income-LED Indoor Reflector Downlight-12 watt avg. 3,676 305.8 3.7% 0.2% 8 Res-Low Income-LED Indoor Screw-in Lamp-High Wattage-17 watt 2,828 235.2 2.9% 0.2% avg. 9 Com-Office-Retro-commissioning 2,110 0.0 2.1% 0.0% 10 Corn-Office-WholeBlg-Corn RET Level 2 1,850 774.0 1.9% 0.6% Source:Navigant 2016 76 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Figure 32. Gross Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN Incremental Gross Market Potential by Sector zoo.000 All Sectors Energy Potential(MWh)and%of Sales Lso% 180,000 160% 160.000 L40% 140.000 ' 120% --1 120.000 t 1.0046 3100,000 2 080% 80,000 a` 12 60.000 0 ' 40.000 0.40% 20,000 0.20% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 MIN Res Incremental Market Potential MINI Non-Res Incremental Market Potential MI C&S)lf Claimed.Estimates not available after 2024) -0-Total Incremental Potential as a%of Total Sales Table 4-91. Inputs to Figure 1 ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 149,626 154,902 164,286 175,198 183,687 187,401 181,428 168,982 157,634 145,870 Res Incremental Market Potential 65,706 65,164 63,158 71,826. 82,175 86,050 82,037 70,380 59,946 50,519 Non-Res Incremental Market Potential 46,921 47,739 48,128 48,373 48,512 47,351 47,391 47,602 47,688 46,351 C&S(If Claimed.Estimates not available after 2024) 37,000 42,000 53,000 55,000 53,000 54,000 52,000 51,000 50,000 49,000 Total Incremental Potential as a%of Total Sales 1.34% 1.37% 1.43% 1.51% 1.55% 1.56% 1.48% 1.36% 1.25% 1.14% Res Incremental Potential as a%of Res Sales 1.33% 1.30% 1.24% 1.38% 1.55% 1.58% 1.48% 1.24% 1.04% 0.86% Non-Res Incremental Potential as a%of Non-Res Sales 0.75% 0.75% 0.75% 0.74% 0.74% 0.71% 0.70% 0.70% 0.69% 0.66% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potenti al 131,543 135,519 140,972 145,982. 149,594 131,393 132,947 133,068 134,734 136,139 Res Incremental Market Potential 10,445 10,691 10,843 11,713 12,746 12,893 12,880 11,019 10,723 10,276 Non-Res Incremental Market Potential 111,488 113,726 116,011 118,340 120,699 100,538 102,370 104,291 106,199 108,004 C&S(If Claimed.Estimates not available after 2024) 9,610 11,102 14,118 15,929 16,149 17,963 17,697 17,758 v17,812 17,859 Source:Navigant 2016 At a glance, SMUD's results include: • A 2018-2027 average annual target of 1.4% of forecasted retail sales • Gross savings targets • Only codes and standards (C&S)that are currently in place today, and not future C&S . such as updates to Title 24 • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life • Behavioral programs for all sectors NAVIGANT To: Sacramento Municipal Utility District From: Navigant Consulting, Inc. Date: February 6, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Sacramento Municipal Utility District (SMUD)with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the SMUD service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 59. Base Case Run. This modeling run includes no changes or adjustments to SMUD's current portfolio of energy efficiency programs. 60. Final Run. This modeling run uses SMUD's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.75 SMUD's Final Run included the following adjustments to their Base Case Run: • The expansion of behavioral programs beyond the residential sector to the commercial and industrial sectors • Claiming gross rather than net savings Figure 1 shows the gross incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 75 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Roseville's current 10- year goals are about 142% of the goals established in the prior study. There are several reasons for these higher goals: • Added Streetlighting Program. • Added Commercial Sector Behavioral Program. • Increased promotional costs by 10%. • Increased incentives by 10%. • Claims gross savings targets rather than the net savings targets it claimed in 2012 NAVIGANT Other Features Navigant worked with Roseville to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT Table 4-90. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-Whole House Fan 650 0.0 39.8% 0.0% 2 Com-Retail-LED fixture:33W,3500 lumens 87 22.0 5.3% 1.8% 3 Com-Office-LED fixture:33W,3500 lumens 70 28.5 4.3% 2.4% 4 Res-Single Family-Evaporative Cooler SEER 17.4, 15.1 EER 62 93.1 3.8% 7.&% 5 Res-Single Family-Split System AC SEER 18,13 EER 57 79.3 3.5% 6.6% 6 Res-Single Family-Low Income 55 12.8 3.4% 1.1% 7 Res-Single Family-Split System AC SEER 15,12.5 EER 48 72.6 2.9% 6.1% 8 Res-Single Family-Bathroom Faucet Aerators(0.5-1.0 GPM Electric 34 7.6 2.1% 0.6% 9 Corn-Retail-LED wallpack(existing W<250) 26 6.0 1.6% 0.5% 10 Com-Health-LED fixture:33W,3500 lumens 26 10.0 1.6% 0.8% Source:Navigant 2016 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Roseville begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.74 Table 4-89. Top 10 Energy Saving Measures for 2017 1 Electronics-Efficient Lighting Equipment 786 ' 98.3 18.8% 9.8% 2 Res-Single Family-Whole House Fan 502 0.0 12.0% 0.0% 3 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 492 40.9 11.8% 4.1% 4 Res-Single Family-LED Indoor Reflector Downlight-12 watt avg. 436 36.2 10.4% 3.6% 5 Res-Single Family-Variable Speed Pool Pump 326 0.0 7.8% 0.0% 6 Other Industrial-Efficient Lighting Equipment 175 17.0 4.2% 1.7% 7 Res-Single Family-LED Outdoor Reflector Downlight-14 watt avg. 70 0.0 1.7% 0.0% 8 Corn-Retail-LED parking lot fixture (existing W>_250) 63 14.3 1.5% 1.4% 9 Com-Retail-LED fixture:33W,3500 lumens 56 14.3 1.4% 1.4% 10 Res-Multi Family-LED Indoor Specialty Lamp-10 watt avg. 53 4.4 1.3% 0.4% Source:Navigant 2016 74 See the ELRAM Output Viewer workbook for the full list of top 50 measures. • NAVIGANT Figure 31. Gross Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 12.000 0.90% 0.80% 10,000 .. 0.70% $,000 0.60% C L 00 0.504p 6.0 0.4D9c 1I11III1II : 4,00000 0-30ae 0.24°ro 7.0 0.10% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2025 2021 Mil ken Incremental Market t'otential BM Nom Res Incremental Market Potential t total Incremental Potential as a%of total Sales Table 4-88. Inputs to Figure 1 ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 8,413 8,549 8,995 9,578 10,063 10,000 9,275 8,556 7,977 7,895 Res Incremental Market Potential 6,338 6,448 6,560 6,661 6,760 6,847 6,873 6,880 6,871 6,838 Non-Res Incremental Market Potential 2,074 2,101 2,435 2,917 3,303 3,152 2,402 1,677 1,106 1,0.58 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.71% 0.72% 0.76% 0.81% 0.85% 0.85% 0.80% 0.74% 0.70% 0.70% Res Incremental Potential as a%of Res Sales 1.47% 1.50% 1.53% 1.56% 1.58% 1.61% 1.63% 1.65% 1.67% 1.68% Non-Res Incremental Potential as a%of Non-Res Sales 0.27% 0.28% 0.32% 0.38% 0.44% 0.42% 0.32% 0.23% 0.15% 0.15% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 965 1,132 1,426 1,681 1,786 1,565 1,458 1,350 1,260 1,239. Res Incremental Market Potential 187 212 247 286 322 346 361 367 369 367 Non-Res Incremental Market Potential 777 920 1,179 1,395 1,464 1,219 1,097 983 891 871 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Source:Navigant 2016 At a glance, Roseville's results include: • A 2018-2027 average annual target of 0.76% of forecasted retail sales • Gross savings targets • No claim of savings from codes and standards (C&S) • Added Streetlighting Program. • Added Commercial Sector Behavioral Program. • Increased promotional costs by 10%. • Increased incentives by 10%. NAVIGANT To: Roseville Electric From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Roseville Electric with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Roseville service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 57. Base Case Run. This modeling run includes no changes or adjustments to Roseville's current portfolio of energy efficiency programs. 58. Final Run. This modeling run uses Roseville's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.73 Roseville's Final Run included the following adjustments to their Base Case Run: • Added Streetlighting Program. • Added Commercial Sector Behavioral Program. • Increased promotional costs by 10%. • Increased incentives by 10%. • Claim gross rather than net savings Figure 1 shows the gross incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 73 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Riverside's current 10- year goals are about 106% of the goals established in the prior study. The primary reasons are: • Using the three-year average for calibration rather than only 2015 • The addition of streetlighting NAVIGANT Other Features Navigant worked with Riverside to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.72 Table 4-86. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-Shade Tree 2,082 0.0 9.4% 0.0% 2 Corn-Office-LED fixture:33W,3500 lumens 1,261 499.4 5.7% 5.9% 3 Corn-Education-LED fixture:33W,3500 lumens 975 128.4 4.4% 1.5% 4 Corn-Office-Retro-commissioning 931 0.0 4.2% 0.0% 5 Corn-Retail-LED fixture:33W,3500 lumens 785 193.8 3.6% 2.3% 6 Corn-Office-LED T8 Tube Replacement Average Fixture Wattage 59.65 649 257.0 2.9% 3.0% 7 Corn-Grocery-LED downlight,screw-in lamp, 1-3W,interior Average 2 557 100.9 2.5% 1.2% Watts 8 Corn-Education-LED T8 Tube Replacement Average Fixture Wattage 502 66.1 2.3% 0.8% 59.65 9 Corn-Education-Retro-commissioning 473 0.0 2.1% 0.0% 10 Corn-Retail-WholeBlg-Corn RET Level 2 473 144.3 2.1% 1.7% Source:Navigant 2016 Table 4-87. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-Refrigerator Recycling 951 191.4 8.6% 6.3% 2 Res-Single Family-Shade Tree 829 0.0 7.5% 0.0% 3 Com-Office-Retro-commissioning 823 0.0 7.4% 0.0% 4 Corn-Retail-WholeBlg-Corn RET Level 2 611 186.7 5.5% 6.2% 5 Corn-Grocery-Retro-commissioning 439 . 0.0 4.0% 0.0% 6 Corn-Grocery-LED downlight,screw-in lamp, 1-3W,interior Average 2 425 76.9 3.8% 2.5% Watts 7 Res-Single Family-CEE Tier II Refrigerator 408 0.0 3.7% 0.0% 8 Com-Education-Retro-commissioning 358 0.0 3.2% 0.0% 9 Corn-Retail-Electronically Commutated(EC)Motor w/Fan Cycling 270 30.8 2.4% 1.0% Controls for Cold Storage Evaporator Fans 10 Corn-Grocery-Electronically Commutated(EC)Motor w/Fan Cycling 269 30.7 2.4% 1.0% Controls for Cold Storage Evaporator Fans Source:Navigant 2016 72 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Net Incremental Market Potential by Sector 2501 All Sectors Lnergy Potential(MWh)and%of Sales 1.00 0.90% 70,0000.80% 0.70% °i 15,000 0.60% 0.50$ 7 10000 0.40% a 0.30% A 5,000 0.20% 0.10% 0 0.00% 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 ti Total Incremental Potential as a%ot Total Sales II=Non Res Incremental Market Potential C&S(If Claimed) tTotal Incremental Potential as a%of Total Sales Figure 30. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potenti al 20,594 20,815 20,309 19,451 18,492 17,505 16,426 15,403 14,310 12,968 Res Incremental Market Potential 5,043 4,697 4,459 4,526 4,866 5,093 5,206 5,084 4,773 4,500 Non-Res Incremental Market Potential 15,550 16,118 15,850 14,925 13,626 12,412 11,220 10,319 9,538 8,468 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sa Iles 0.90% 0.90% 0.88% 0.84% 0.80% 0.75% 0.70% 0.66% 0.61% 0.55% Res Incremental Potential as a%of Res Sales 0.67% 0.62% 0.59% 0.60% 0.64% 0.66% 0.68% 0.66% 0.62% 0.58% Non-Res Incremental Potential as a%of Non-Res Sales 0.99% 1.03% 1.01% 0.94% 0.86% 0.78% 0.70% 0.65% 0.60% 0.53% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 7,463 7,107 6,915 6,981 7,050 6,979 6,908 6,283 5,595 4,608 Res Incremental Market Potenti al 3,941 3,436 3,291 3,527 3,849 4,190 4,396 3_9863,482 2,671 Non-Res Incremental Market Potential 3,522 3,671 3,624 3,454 3,201 2,788 2,512 2,298 2,113 1,936 C&S(If Claimed) 0 0 0 0 0 0 0 0 0 0 Table 4-85. Inputs to Figure 1 Source:Navigant 2016 At a glance, Riverside's results include: • A 2018-2027 average annual target of 0.76% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • The addition of streetlighting phase starting in 2018 Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Riverside begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures NAVIGANT To: Riverside Public Utilities From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction • This memo provides Riverside Public Utilities with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Riverside service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 55. Base Case Run. This modeling run includes no changes or adjustments to Riverside's current portfolio of energy efficiency programs. 56. Final Run. This modeling run uses Riverside's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings." Riverside's Final Run included the following adjustments to their Base Case Run: • Expanded measure list. Included streetlighting phase in starting in 2018. • Utilized a three-year average calibration target rather than 2015 alone. Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 71 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Redding's current 10- year goals are about 115% of the goals established in the prior study. There are two reasons for these higher goals: • Redding added streetlighting to their programs. • The forecast of sales in 2016 is about 10% lower than the forecast of sales in 2012. NAVIGANT Other Features Navigant worked with Redding to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT Table 4-84. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-Variable Speed Pool Pump 198 0.0 10.2% 0.0% 2 Com-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 192 50.0 9.9% 7.1% Watts 3 Com-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 156 39.3 8.0% 5.6% Watts 4 Res-Single Family-CEE Tier III Refrigerator(from 30$to 35%more 96 0.0 4.9% 0.0% efficient) 5 Res-Single Family-Whole House Fan 92 0.0 4.8% 0.0% 6 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 91 114.6 4.7% 16.3% 7 Res-Single Family-CEE Tier II Refrigerator 75 0.0 3.8% 0.0% 8 Res-Single Family-Split System AC SEER 18 to 22, 13 EER 72 77.9 3.7% 11.1% 9 Res-Single Family-Split System AC SEER 15,12.5 EER 65 76.1 3.3% 10.8% 10 Res-Single Family-Ceiling Insulation(No insulation to R-30 or R-38) 62 0.0 3.2% 0.0% Source:Navigant 2016 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Redding begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.70 Table 4-83. Top 10 Energy Saving Measures for 2017 1 Street Lighting-LED Streetlights 410 0.0 10.8% 0.0% 2 Res-Single Family-Variable Speed Pool Pump 248 0.0 6.5% 0.0% 3 Res-Single Family-Ceiling Insulation(No insulation to R-30 or R-38) 188 0.0 4,9% 0.0% 4 Corn-Retail-LED fixture: 33W,3500 lumens 167 42.2 4.4% 4.1% 5 Street Lighting-LED Streetlights with Advanced Controls 162 0.0 4.3% 0.0% 6 Com-Restaurant-LED downlight,screw-in lamp, 1-3W,interior Average 2 158 41.1 4.1% 4.0% Watts 7 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 140 177.6 3.7% 17.2% 8 Com-Retail-LED downlight,screw-in lamp, 1-3W,interior Average 2 125 31.6 3.3% 3.0% Watts 9 Other Industrial-Efficient Lighting Equipment 115 11.2 3:0% 1.1% 10 Corn-Office-LED fixture:33W,3500 lumens 107 43.7 2.8% 4.2% Source:Navigant 2016 70 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 29. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 4.500 0.60% 4.000 0.SO% 1.I 3 0.40% c L 7,il o0.30% 7V20% _o0 0-10 0.00% 7018 7014 . 2070 7021 7077 70I5 7074 7075 7076 2077 ale Res Incremental Market Potentiai MI Non Res Incremental Market Potential —0—Total Incremental Potential as a%of Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 3,336 3,466 3,666 3,858 3,629 3,439 3,438 3,352 3,234 2,695 Res Incremental Market Potential 587 608 639 678 721 748 760 760 751 736 Non-Res Incremental Market Potential 2,749 2,858. 3,027 3,179 2,908 2,691 2,678 2,593 2,483 1,958 C&S(If Claimed) 0 0 0 Total Incremental Potential as a%of Total Sales 0.44% 0.45% 0.48% 0.51% 0.48% 0.45% 0.45% 0.44% 0.42% 0.37% Res Incremental Potential as a%of Res Sales 0.17% 0.18% 0.19% 0.20% 0.21% 0.22% 0.23% 0.23% 0.22% 0.22% Non-Res Incremental Potential as a%of Non-Res Sales 0.66% 0.68% 0.72% 0.76% 0.69% 0.64% 0.64% 0.62% 0.59% 0.46% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 836 879 944 1,012 1,065 1,066 1,071 1,053 1,028 893 Res Incremental Market Potential 240 250 266 288 305 319 328 332 333 332 Non-Res Incremental Market Potential 595 628 678 724 759 747 743 720 695 561 C&S(If Claimed) 0 0... 0 0 _. .0 0 0 _. 0 0 0 Table 4-82. Inputs to Figure 1 Source:Navigant 2016 At a glance, Redding's results include: • A 2018-2027 average annual target of 0.45% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • Streetlights added to their programs NAVIGANT To: Redding Electric Utility From: Navigant Consulting, Inc. Date: February 6, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Redding Electric Utility with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Redding service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 53. Base Case Run. This modeling run includes no changes or adjustments to Redding's current portfolio of energy efficiency programs. 54. Final Run. This modeling run uses Redding's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.69 Redding added streetlights to its program offerings starting in 2016. 69 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Rancho Cucamonga's current 10-year goals are about 86% of the goals established in the prior study even though it did add new measures to its portfolio. The primary reason is model calibration. In the earlier version, the calibration target was set above actual historical achievements. The calibration target for the current model reflects actual levels of program achievement. Rancho Cucamonga claims gross savings, as it also did in 2012. NAVIGANT Other Features Navigant worked with Rancho Cucamonga to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area ip California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT Table 4-81. Top 10 Energy Saving Measures for 2030 Com-Retail-Electronically Commutated(EC)Motor w/Fan Cycling Controls for Cold 1 Storage Evaporator Fans 42 4.8 11.7% 5.5% 2 Corn-Restaurant-Electronically Commutated(EC)Motor w/Fan Cycling Controls for 33 3.7 9.1% 4.3% Cold Storage Evaporator Fans 3 Com-Retail-Electronically Commutated(EC)Walk-In Evaporator Fan Motor 20 2.3 5.6% 2.6% 4 Com-Retail-WholeBlg-Com RET Level 2 19 5.9 5.4% 6.8% 5 Com-Retail-LED fixture:33W,3500 lumens 18 4.4 5.0% 5.1% 6 Com-Restaurant-Electronically Commutated(EC)Walk-In Evaporator Fan Motor 16 1.8 4.4% 2.1% 7 Com-ALL-Pump and Fan Variable Frequency Drive Controls(VFDs) 14 1.4 3.9% 1.6% 8 Corn-Restaurant-WholeBlg-Corn RET Level 2 9 2.4 2.6% 2.7% 9 Com-Retail-WholeBlg-Corn RET Level 1 8 2.5 2.3% 2.9% 10 Com-Restaurant-Energy Star Commercial Freezer 8 0.9 2.2% 1.0% Source:Navigant 2016 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Rancho Cucamonga begins to allocate program dollars in new directions. Table 3 shows the top 10 energy saving measures for the first year of the forecast period and Table 4 shows the top 10 measures for year 2030 to use as a comparison.68 Table 4-80. Top 10 Energy Saving Measures for 2017 1 Com-Retail-Reduced Wattage T8 Lamp and Ballast Average Fixture Wattage 72.23 46 11,3 18.8% 20.8% 2 Food-Efficient Lighting Equipment 24 2.4 9.7% 4.5% Com-Retail-Electronically Commutated(EC)Motor w/Fan Cycling Controls for Cold o ° /° 3.7/° Storage Evaporator Fans 4 Corn-Restaurant-Electronically Commutated(EC)Motor w/Fan Cycling Controls for 14 1.6 5.6% 2.9% Cold Storage Evaporator Fans 5 Com-Retail-LED fixture:33W,3500 lumens 12 2.9 4.8% 5.3% 6 Com-Retail-Bi-Level Lighting Fixture—Stairwells, Hallways,and Garages 9 0.1 3.7% 0.2% 7 Com-Retail-Electronically Commutated(EC)Walk-In Evaporator Fan Motor 8 1.0 3.5% 1.8% 8 Corn-Office-Bi-Level Lighting Fixture—Stairwells,Hallways,and Garages 8 0.1 3.4% 0.2% 9 Com-Retail-LED Exit Sign 4 Watt Fixture(2 lamp) 7 0.9 2:8% 1.7% 10 Com-Restaurant-Electronically Commutated(EC)Walk-In Evaporator Fan Motor 7 0.8 2.7% 1.4% Source:Navigant 2016 68 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Figure 28. Gross Incremental Market Potential by Sector(MWh) and Percent of Sales-FINAL RUN 4S0 060% 400 350 3U0 0.40% 71111 7.c 250 3 0309> a zoo 150 0.20% 100 0.10% 50 7018 7019 2070 702) 7077 2023 7024 7075 2026 2027 Res incremental Market Potential OM Non-Res incremental Market Potential .011..Total Incremental Potential as a%ot Total Sates 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 288 293 313 347 388 411 416 409 393 375 Res Incremental Market Potential 2 3 5 7 10 13 15 17 19 19 Non-Res Incremental Market Potential 286 290 309 340 378 398 401 392 374 356 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.37% 0.38% 0.40% 0.45% 0.49% 0.52% 0.53% 0.51% 0.49% 0.47% Res Incremental Potential as a%of Res Sales 1.10% 2.00% 2.90% 4.27% 6.00% 7.77% 9.03% 9.95% 10.77% 11.26% Non-Res Incremental Potential as a%of Non-Res Sales 0.37% 0.37% 0.40% 0.43% 0.48% 0.50% 0.50% 0.49% 0.47%. 0.44% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 53 53 55 60 66 71 74 76 76 75 Res Incremental Market Potential 1 2 2 3 4 6 7 8 8 9 Non-Res Incremental Market Potential 52 51 53 57 62 66 68 68 68 66 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-79. Inputs to Figure 1 Source:Navigant 2016 At a glance, Rancho Cucamonga's results include: • A 2018-2027 average annual target of 0.46% of forecasted retail sales • Gross savings targets, as it did in 2012 • No claim of savings from codes and standards (C&S) • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life NAVIGANT To: Rancho Cucamonga Municipal Utility From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Rancho Cucamonga Municipal Utility with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Rancho Cucamonga service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 51. Base Case Run. This modeling run includes no changes or adjustments to Rancho Cucamonga's current portfolio of energy efficiency programs. 52. Final Run. This modeling run uses Rancho Cucamonga's chosen adjustments—if any— to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.67 Rancho Cucamonga's Final Run included the following adjustments to their Base Case Run: • Expanded measure list. Navigant modeled a number of measures—not currently offered in Rancho Cucamonga's portfolio—to provide a picture of potential savings should Rancho decide to expand their current programs. The team used various sources and studies throughout California and the nation to inform this expanded measure list. • Not claiming Codes and Standards savings. Rancho Cucamonga will not be claiming savings from codes and standards for this study. Figure 1 shows the gross incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. 67 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Port of Oakland's current 10-year goals are about 556% of the goals established in the prior study. The primary reason is that the Port has hired an implementation contractor and they have identified near term potential implementation opportunities. Historically, despite having goals in 2012, the Port has not achieved energy savings. NAVIGANT Other Features Navigant worked with Port of Oakland to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects —the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT Table 4-78. Top 10 Energy Saving Measures for 2030 1 Industrial Machinery-Efficient Lighting Equipment 89.1 10.1 16.6% 7.8% 2 Corn-Other-WholeBlg-Corn RET Level 2 65.6 30.7 12.2% 23.7% 3 Industrial Machinery-Efficient MachDr O&M 58.3 6.5 10.9% 5.0% 4 Com-Other-WholeBlg-Corn RET Level 1 44.0 15.5 8.2% 11.9% 5 Industrial Machinery-Efficient MachDr Equipment 43.6 4.9 8.1% 3.8% 6 Corn-Retail-WholeBlg-Corn RET Level 2 31.4 10.2 5.9% 7.9% 7 Industrial Machinery-Efficient HVAC O&M 19.9 1.0 3.7% 0.8% 8 Corn-Warehouse-WholeBlg-Corn RET Level 2 19.1 4.3 3.6% 3.3% 9 Industrial Machinery-Efficient HVAC Equipment 18.1 2.3 3.4% 1.8% 10 Corn-Retail-WholeBlg-Corn RET Level 1 15.1 5.1 2.8% 4.0% Source:Navigant 2016 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Port of Oakland begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.66 Table 4-77. Top 10 Energy Saving Measures for 2017 1 Industrial Machinery-Efficient Lighting Equipment 79.460 9.0 16.0% 7.4% 2 Corn-Other-WholeBlg-Corn RET Level 2 50.723 23.7 10.2% 19.4% 3 Industrial Machinery-Efficient MachDr O&M 50;161 5:6 10.1% 4.6% 4 Industrial Machinery-Efficient MachDr Equipment 38.901 4.3 7.8% 3.6% 5 Com-Other-WholeBlg-Corn RET Level 1 34.049 12.0 6.8% 9.8% 6 Corn-Retail-WholeBlg-Corn RET Level 2 24.305 7.9 4.9% 6.5% Corn-Other-Comprehensive Rooftop Unit Quality Maintenance(AC Tune-up) 17,488 11.5 3.5% 9.4% 8 Industrial Machinery-Efficient HVAC O&M 17.162 0.9 3.4% 0.7% 9 Com-Other-Demand Controlled Ventilation 16.410 1.6 3.3% 1.3% 10 Industrial Machinery-Efficient HVAC Equipment 16.135 2.1 3.2% 1.7% Source:Navigant 2016 66 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Figure 27. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 400 0.91% 0.90e 500 0.89aa 4W V 3(1.) o.a o.r�6% ;.- 0.85% 0.1344a 300 RIO 0 0.83% 2018 2019 2020 2071 2022 2073 2024 2025 2026 2027 IINM Res Incremental Market Potential 1111111111Non-Res Incremental Market Potential Total Incremental Potential as a%01 Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MW6) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 512 517 521 526 528 530 532 533 534 535. Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Incremental Market Potential 512 517 521 526 528 530 532 533 534 535 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.90% 0.90% 0.90% 0.90% 0.89% 0.88% 0.88% 0.87% 0.86% 0.86% Res Incremental Potential as a%of Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%. 0.00% Non-Res Incremental Potential asa%of Non-Res Sales 0.89% 0.89% 0.89% 0.89% 0.88% 0.87% 0.87% 0.86% 0.85% 0.85% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 110 112 112 112 114 114 114 114 113 113 Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 Non-Res Incremental Market Potential 110 112 112 112 114. 114 114 114 113 113 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-76. Inputs to Figure 1 Source:Navigant 2016 At a glance, Port of Oakland's results include: • A 2018-2027 average annual target of 0.88% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) • A mix of existing condition and code baselines for modeled measures, as well as a "dual baseline" function that can use the existing condition for a portion of the remaining useful life, and the code baseline for the remaining useful life NAVIGANT To: Port of Oakland From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Port of Oakland with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Port of Oakland service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM) to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 49. Base Case Run. Generally, the Base Case modeling run includes no changes or adjustments to Port of Oakland's current portfolio of energy efficiency programs. However, the Port of Oakland has no current portfolio 50. Final Run. This modeling run uses Port of Oakland's chosen adjustments. Port of Oakland's Final Run included the following additions: • Added measures. The Port staff reviewed the list of available measures within the measure database and selected a set of commercial and industrial sector measures. • Where appropriate, the added measures were modeled as early retirement. Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Plumas-Sierra's current 10-year goals are about 143% of the goals established in the prior study. The primary reason is calibration. The calibration target in 2012 was based on 0.5% of sales. The current calibration is based on actual 2015 program achievements. The 2016 calibration target is about 58% larger than the 2012 calibration target. NAVIGANT Other Features Navigant worked with Plumas-Sierra to provide a number of other ELRAM modeling features described in more detail in the Output Viewer workbook. Among others these include: • Cumulative Savings. Savings shown cumulating over the forecast period. • Electric Vehicles (EVs) and Photovoltaics (PV). Forecast of EV and PV usage and generation over the 10 year study period. The modeling team based these projections on the EV/PV assumptions defined in the 2016 California Energy Commission (CEC) Integrated Energy Policy Report for each planning area in California. The team matched each POU to the nearest planning area and prorated the forecasts based on the POU's electric sales by sector. • Interactive Charts. The tabs titled Potential by Sector, Potential by Program, and Potential by End-Use include interactive charts where users can filter the potential savings results in a number of informative ways. Comparison to 2014-2023 10-Year EE Potential Study The model currently used to develop the 10-year EE potential goals is similar to the one used to develop the 2014-2023 potential goals, with the following key differences: • Improved Calibration —for calibration purposes, the model now spreads historical program savings across end-use categories at the program level, using actual savings per end-use category/program as identified in E3. The prior model did not calibrate to the program level. • Updated Measure Impact/Cost Information —the modeling team has significantly improved the measure level inputs using the Technical Reference Manual (TRM) recently developed by the POUs, as well as the most recent CPUC database of available measures with impacts and costs at the climate zone level. • Measure Impacts Include C&S Effects—the new ELRAM includes the most recent (C&S) impacts to measure savings, but does not include future or planned C&S impacts not currently adopted. • Increased Decision Type Flexibility and Existing Baseline Changes —the model structure now allows for dual baseline measures (early retirement). This function uses the existing condition baseline for a specified portion of the useful life of a measure, and the code baseline for the remaining portion of the useful life. • Expanded Building Types — ELRAM provides model results at the building type level for both the residential and commercial segments. The prior model only provided a rolled up commercial sector result. • Behavioral Programs Included — ELRAM now includes optional Behavioral Programs for the residential, commercial, and industrial sectors. The earlier model did not. NAVIGANT Table 4-75. Top 10 Energy Saving Measures for 2030 1 Res-Single Family-Solar Attic Fan(1,000 CFM) 19 44.1 . 19.2% 45.1% 2 Res-Single Family-CEE Tier III Refrigerator(from 30$to 35%more 18 0.0 18.9% 0.0% efficient) 3 Res-Single Family-CEE Tier II Refrigerator 14 0.0 14.7% 0.0% 4 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 11 21.8 10.9% 22.3% 5 Res-Single Family-LED Indoor Reflector Downlight-12 watt avg. 8 0.7 8.2% 0.7% 6 Res-Single Family-Residential Solar Screen 7 15.3 7.6% 15.6% 7 Res-Single Family-Wall Insulation(R-13) 7 0.0 7.0% 0.0% 8 Res-Single Family-LED Indoor Specialty Lamp-10 watt avg. 2 0.2 2.0% 0.2% 9 Res-Single Family-Ceiling Insulation(No insulation to R-30 or R-38) 1 0.0 1.5% 0.0% 10 Res-Multi Family-CEE Tier III Refrigerator(from 30$to 35%more 1 0.0 1.4% 0.0% efficient) Source:Navigant 2016 NAVIGANT Top Energy Saving Measures Navigant's model displays a list of the top 50 measures generating savings for the forecast period. These measures can help inform future program design efforts as Plumas-Sierra begins to allocate program dollars in new directions. Table 2 shows the top 10 energy saving measures for the first year of the forecast period and Table 3 shows the top 10 measures for year 2030 to use as a comparison.65 Table 4-74. Top 10 Energy Saving Measures for 2017 1 Res-Single Family-Wall Insulation(R-13) 94 0.0 30.1% 0.0% 2 DHW) 49 Family-Bathroom Faucet Aerators(0.5-1.0 GPM Electric 49 10.7 15.6% 6.3% 3 Res-Single Family-Ceiling Insulation(No insulation to R-30 or R-38) 48 0.0 15.4% 0.0% 4 Res-Single Family-Solar Attic Fan(1,000 CFM) 32 76.1 10.4% 44.9% 5 Res-Single Family-Reflective Window Film(reduces SHGC to 0.39) 18 37.5 5.8%° 22.2% 6 Res-Single Family-Residential Solar Screen 13 26.4 4.1% 15.6% 7 Res-Single Family-Ceiling Insulation(R-30 addition) 9 0.0 2.9% 0.0% 8 Res-Single Family-CEE Tier III Refrigerator(from 30$to 35%more 8 0.0 2.5% 0.0% efficient) 9 Res-Single Family-Kitchen Faucet Aerators(1.5 GPM Electric DHW) 8 1.6 2.4% 0.9% 10 Res-Single Family-Ceiling Insulation(R-19 addition) 7 0.0 2.3% 0.0% Source:Navigant 2016 65 See the ELRAM Output Viewer workbook for the full list of top 50 measures. NAVIGANT Figure 1 shows the net incremental market potential achievable for each sector across the forecast period, as well as the percent of forecasted sales for each year for the Final Run. Figure 26. Net Incremental Market Potential by Sector(MWh)and Percent of Sales-FINAL RUN 180 0.12% 160 U.lO`b 140 120 0.08% i 1W $ 5 0.06% E- .- 60 0.04% o 40 0.02:% 70 2018 2019 2020 2021 2012 2023 2024 2025 2026 1021 MI Total Incremental Market Potential Non Re;Incremental Market Potential ....Total Incremental Potential as a%ot Total Sales 10 Year Energy Goals(Net MWh) ALL Sectors(MWh) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 146 149 146 153 162 146 120 93 74 70 Res Incremental Market Potential 146 149 146 153 162 146 120 93 74 70 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Total Incremental Potential as a%of Total Sales 0.10% 0.10% 0.10% 0.10% 0.11% 0.09% 0.08% 0.06% 0.05% 0.04% Res Incremental Potential as a%of Res Sales 0.27% 0.27% 0.27% 0.28% 0.29% 0.26% 0.21% 0.17% 0.13% 0.12% Non-Res Incremental Potential as a%of Non-Res Sales 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%. 0.00% 0.00% 10 Year Demand Goals(kW) ALL Sectors(kW) 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 Total Incremental Market Potential 72 77 84 90 94 88 79 73 69 72 Res Incremental Market Potential 72 77 84. 90 94 88 79 73 69. 72 Non-Res Incremental Market Potential 0 0 0 0 0 0 0 0 0 0 C&S(If Claimed.Estimates not available after 2024) 0 0 0 0 0 0 0 0 0 0 Table 4-73. Inputs to Figure 1 Source:Navigant 2016 At a glance, Plumas-Sierra's results include: • A 2018-2027 average annual target of 0.08% of forecasted retail sales • Net savings targets • No claim of savings from codes and standards (C&S) NAVIGANT To: Plumas-Sierra Rural Electric Cooperative From: Navigant Consulting, Inc. Date: January 30, 2017 Re: 2016 CMUA Energy Efficiency Potential Forecasting Study Introduction This memo provides Plumas-Sierra Rural Electric Cooperative with the results of the California Municipal Utilities Association (CMUA) Energy Efficiency Potential Forecasting Study conducted in 2016 by Navigant Consulting, Inc. (Navigant). The results described here are specific to the Plumas-Sierra service territory. Summary of Potential Navigant used their Electric Resource Assessment Model (ELRAM)to estimate achievable energy and demand savings over a 10 year forecast period. The modeling team forecasted these savings using two modeling steps: 47. Base Case Run. This modeling run includes no changes or adjustments to Plumas- Sierra's current portfolio of energy efficiency programs. 48. Final Run. This modeling run uses Plumas-Sierra's chosen adjustments—if any—to various features within the model to illustrate increased energy savings goals. This run may be the same as the Base Case Run if the utility chose not to make adjustments to current portfolio offerings.64 Plumas-Sierra chose to call their Base Case Run as Final and made no adjustments to modeling scenarios. 64 Utilities are often already doing everything they can within their energy efficiency budgets and have no plans to increase current program offerings. NAVIGANT These changes have the opportunity to either increase or decrease the utility's 10-year goal as compared to the previous study. Measure selection, program additions, and most importantly, the calibration targets determine the change. The years 2018-2023 overlap between the two 10-year study periods. Pittsburg's current 10- year goals are about 66% of the goals established in the prior study, despite adding new measures to their program offerings. The primary reason is calibration. The 2012 calibration targets were aggressive; 1% of sales. Historic program achievement at that time was about 45% less. Current calibration uses the average of 2013 through 2015 actual program achievements.