2. How does this assessment relate to MISO s resource adequacy construct?

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1 DRAFT Applied Energy Group DR, EE, DG Assessment FAQs 1. What is the Applied Energy Group Assessment of Demand Response, Energy Efficiency and Distributed Generation for Midcontinent ISO, and how will it be used? This assessment estimates the likely future savings that will be achieved through demand response (DR), energy efficiency (EE) and distributed generation (DG) utility programs over the next 20 years. The study is based on a voluntary survey of load serving entities and information submitted by state regulatory agencies. The study develops a reference case that reflects modest increases to existing utility programs. It does not contemplate either additional programs for utilities that already have programs or new programs of any kind for utilities that are not running programs in Several scenarios, also called futures, explore alternative cases that would result in higher savings estimates. The purpose of this study is to allow MISO to analyze the impacts related to customer side DR, EE and DG utility programs for transmission planning purposes. This forecast will inform Clean Power Plan (CPP) transmission planning analysis. Additionally, the savings programs from this forecast that are selected as economic through EGEAS 1 will be incorporated into MISO s Independent Load Forecast models and MTEP Futures development for transmission planning purposes. 2. How does this assessment relate to MISO s resource adequacy construct? Broadly, this study allows MISO to more fully analyze the impacts of customer sited DR, EE and DG programs on future energy use and peak demand. However, the study results are not used in the annual Loss of Load Expectation study or the Planning Resource Auction process. 3. How does this assessment differ from the previous 2010 Global Energy Partners report? In general, the studies are similar in that they both begin with a survey of utilities in the MISO footprint and develop several futures for savings from DR and EE. However, this study builds upon and updates the 2010 Demand Response and Energy Efficiency study 2 completed by Global Energy Partners in several ways: 1 Electric Power Research Institute (EPRI) Electric Generation Expansion Analysis System (EGEAS) model performs integrated resource planning, and is one model MISO uses in its transmission expansion planning process. 2 Volume 1: https://www.misoenergy.org/library/repository/meeting%20material/stakeholder/drwg/2011/ / %20DRWG%20Item%2003%20Midwest%20ISO%20DR%20and%20EE%20Potential%20Assessment%20Volum e%201_w%20scenarios%20%20final.pdf; Volume 2: https://www.misoenergy.org/library/repository/meeting%20material/stakeholder/drwg/2011/ / %20DRWG%20Item%2003%20Midwest%20ISO%20DR%20and%20EE%20Potential%20Assessment%20Volum e%202%20w_scenarios.pdf

2 It provides estimates for each LRZ rather than the three regions considered in the 2010 study It includes customer sited distributed generation, which includes combined heat and power (CHP), solar and wind, as well as energy storage and behavioral programs. It reflects the current MISO footprint, which includes utilities in the South. The modeling is enhanced. AEG used its LoadMAP 3 model which is an end use model that explicitly accounts for stock turnover and appliance standards.. The reference case in this study is Existing Programs Plus, a case that only considers utility programs as they exist in In the previous study, the reference case, called Achievable Potential, assumed additional growth of existing programs, as well as the introduction of new programs during the study period. The current study considers the following futures: o A High Demand case that captures the effects of increased economic growth resulting in higher energy costs and medium high gas prices. The magnitude of the demand and energy growth are determined by using the upper bound of the Load Forecast Uncertainty metric and also includes forecasted load increases in the South region. o A Low Demand case that captures the effects of decreased economic growth resulting in lower energy costs and medium low gas prices. The magnitude of the demand and energy growth are determined by using the lower bound of the Load Forecast Uncertainty metric. o A Clean Power Plan (CPP 111(d)) case in this study analyzed conditions in which each MISO LRZ met the weighted average of the state target outlined in the EPA Clean Power Plan proposed rule in June For each LRZ, the amount of savings required as part of the proposed rule by 2029 was calculated by reverse engineering the LoadMAP model to reach that level of energy savings. AEG accomplished this by first maximizing participation in existing EE programs, then adding additional EE programs, starting in 2018, in the LRZs where no programs existed in the base year. o An increased Demand side DG case was developed since this is expected to be a high growth area in the coming years with the decrease in costs for solar technology and batter storage. This case uses forecasts by state from the Sunshot Vision study for solar technology, growth forecasts for wind, CHP and thermal storage from EIA s Annual Energy Outlook 2015, and growth forecasts for battery storage from the US Energy Storage Monitor. Since there is such uncertainty surrounding DG we created two cases: Demand side DG and High Penetration DG. The High Penetration DG is not to be considered realistic, but to 3 LoadMAP is an end use forecasting framework that allows the development of forecasts that address energy efficiency programs, appliance standards, building codes, naturally occurring efficiency, emerging technologies, customer sited renewable energy, distributed energy and electric vehicles specifically. (http://www.appliedenergygroup.com/load and revenue forecasting)

3 give some boundaries on what we think is possible in a future with an increased focus on distributed generation. 4. How are programs in this assessment different from what market participants offer in the market, or projects in the interconnection queue? This assessment focused on customer sited DR, EE and DG as a result of participation in utility programs. DG facilities eligible for these programs are often small enough that MISO interconnection is not required. Load Serving Entities (LSEs) may include customer energy efficiency in their load forecasts submitted to MISO for the Planning Resource Auction. LSEs may also register DR or DG as capacity and energy efficiency as an energy efficiency resource as described under MISO s Resource Adequacy in Module E of the Tariff. AEG surveyed utilities about current and planned customer programs and then analyzed and synthesized this data to develop a common set of programs across the MISO footprint. It also added programs to include emerging technologies such as battery storage. The Existing Programs Plus case in the AEG study uses program data from the utility survey and assumes a small increase in participation in existing programs over 20 years to represent increased participation rates over time. Mature programs, such as residential direct load control, that have been running for over 10 years are assumed to reach maximum participation and are held steady for the remainder of the forecast. The 111(d) case assumes that additional programs will be added to help meet regulatory goals. If a program is not currently offered in an LRZ, the 111(d) case of the AEG study assumes that it starts in 2018 at a low participation rate consistent with a new program offering, allowing for enough ramp up time to meet the 2029 compliance date. 5. How do the DR, EE and DG programs in this assessment affect energy and demand growth? The baseline projection for peak demand, which assumes no future utility programs beyond 2015, increases 15% between 2015 and 2035, from 118,235 MW to 136,441 MW, or growth of 18,176 MW. For energy, the AEG baseline increases 18% between 2015 and 2035 from 678,651 GWh to 801,747 GWh, or growth of 123,096 GWh. In the Existing Programs Plus case, 4 cumulative DR, EE, and DG peak demand savings reach 20,263 MW in 2035, or 14.9% of the baseline projection. These savings more than offset the growth in the baseline. Cumulative annual energy savings from DR, EE, and DG reach 53,225 GWh in 2035, or 6.6% of the baseline. These savings offset 43% of the expected growth in the baseline energy forecast. 4 Uses program data from the utility survey and assumes a small increase in participation in existing programs over 20 years to represent increased participation rates over time. Mature programs that have been running for over 10 years (such as residential direct load control) are assumed to reach maximum participation and are held steady for the remainder of the forecast.

4 6. How did this assessment take into account qualifying facilities in the South region? MISO requested qualifying facility information from both the Louisiana Energy Users Group and Texas Industrial Energy Consumers groups, which they discussed with their respective members. Given a variety of factors, their members elected to not respond. MISO will assess and evaluate how to best meet our mutual needs for a future period and we hope to have as many qualifying facilities as possible participate in a future study. Independent Load Forecast FAQs 1. What is the Independent Load Forecast? The Independent Load Forecast is a 10 year load forecast developed by the State Utility Forecasting Group (SUFG) for MISO. The forecast projects annual MISO regional energy demand for the ten MISO local resource zones (LRZs), regional winter and summer seasonal peak loads and MISO system wide annual energy and peak demands. This forecast does not attempt to replicate the forecasts that are produced by MISO s load serving entities (LSEs). It would not be appropriate to infer a load forecast for an individual LSE from this forecast. 2. Who will develop the independent long term load forecast? SUFG will develop the independent long term load forecast. SUFG was established through Indiana state legislation, is an independent research and analysis group at Purdue University, and is not an advocacy group. They have developed over 14 load forecasts of various loads within Indiana for use by the Indiana PSC and others. They have worked with a number of other entities in the state of Indiana, Federal agencies, other states, utilities, and national labs as well as the Eastern Interconnection State Planning Committee (EISPC). 3. Why is MISO having an independent consultant develop an independent long term load forecast? First, the intent is to gather an independent view of future demand in MISO; second, this will provide transparency into the process and assumptions for potentially developing a longer term MISO demand forecast; third, this will allow MISO to be able to assess risk from changes in demand by varying the input assumptions that could inform MISO about potential reliability issues in the future. Finally, and most importantly, this will provide an additional data point for future stakeholder discussions on long term load forecasts, which are a critical input into all MISO processes that use long term load forecast data.

5 4. How will the Independent Load Forecast be used? The intent is to use the State Utility Forecasting Group Independent Load Forecast as an additional sensitivity to the aggregated LSE forecasts in economic planning, seasonal assessments, and Long Term Resource Assessments. Each of these processes rely on the forecasts provided by the LSEs which, in companion with the Independent Load Forecast, will provide bottom up and top down perspectives. Economic planning would include using it in the MISO MTEP futures process. Seasonal assessments refer to the assessments developed per NERC standard for the upcoming season. The Long term Resource Assessment is the annual assessment required per NERC standard for each Planning Authority. 5. Does the Independent Load Forecast replace the forecasts submitted by LSEs and MISO Transmission Owners? No, MISO has explicitly communicated since the March 2014 PAC meeting that the SUFG independent load forecast will not replace a LSE s forecast where defined by the MISO Tariff. Any changes to the MISO tariff would go through the appropriate stakeholder process and require a tariff filing: https://www.misoenergy.org/library/repository/meeting%20material/stakeholder/pac/2014/ / %20PAC%20Item%2006%20Independent%20Load%20Forecast.pdf MISO s independent load forecast is a top down approach whereas the LSE and TO forecasts are a bottom up approach. The granularity of the independent load forecast is primarily at the state level, and ultimately allocated to each Local Resource Zone. LSEs and TOs have access to specific information that is necessary to build the transmission planning models and perform assessments. The intent is not to replicate each of the individual LSE or TO forecasts but rather develop a forecast that represents MISO from a regional perspective. This independent load forecast will provide MISO and its stakeholders an additional outlook on future demand. 6. How was the Independent Load Forecast developed? Econometric models were developed for each state to project annual retail sales of electricity. Forecasts of metered load at the LRZ level were developed by allocating the portion of each state s sales to the appropriate LRZ and adjusting for estimated distribution system losses. LRZ seasonal peak demand projections were developed using conversion factors, which translated annual energy into peak demand based on historical observations assuming normal weather conditions. The LRZ peak demand forecasts are on a non coincident basis. MISO system level projections were developed from the LRZ forecasts. For the seasonal MISO peak demands, coincidence factors were used. Energy efficiency, demand response, and distributed generation (EE, DR, DG) adjustments were made at the LRZ level based on a study of those factors performed by Applied Energy Group for MISO.

6 7. What data was used for the Independent Load Forecast? The state econometric models were developed using publicly available information for electricity sales, prices for electricity and natural gas, personal income, population, employment, gross state product, and cooling and heating degree days. Economic and population projections acquired from IHS Global Insight (IHS) and price projections developed by SUFG were used to produce projections of future retail sales. Weather variables were held constant at their 30 year normal values. 8. Why is there no net forecast available at the state level? Due to stakeholder request, SUFG changed the methodology for adjusting for EE, DR and DG. In the first year the adjustments were made at the state level. Thus, net forecasts were produced at the state level. The adjustments are now made at the LRZ level based on information obtained from the AEG assessment. Since that information was not available at the state level, no net state forecasts were produced. 9. Are the 2014 values in the report actual values or SUFG forecast values? The 2014 values are the actual values. 10. Does MISO currently develop a long term forecast? No, MISO does not create its own long term load forecast. MISO relies on each of its Transmission Owners to submit load forecast information to develop its reliability planning models and load serving entities to submit load forecast information for the next planning year for the Planning Resource Auction and the next nine years for economic planning. Each forecast has its own requirements driven by the process that uses it. The ILF is developed by the State Utility Forecasting Group to provide additional long term (ten year) load forecast data. Applied Energy Group DR, EE, DG Assessment and Independent Load Forecast FAQs

7 1. How are AEG s DR, EE, DG Assessment and the Independent Load Forecast (ILF) related? AEG s DR, EE, DG assessment is incorporated into the Independent Load Forecast in order to account for the effect of customer sited DR, EE and DG programs in the ILF. AEG s DR, EE, DG assessment develops estimates of peak and energy savings from customer participation in utility DR, EE, and DG programs. Those savings are then run through EGEAS, and programs are picked in EGEAS based on cost effectiveness. Those programs are then incorporated into the ILF to develop a net forecast, which accounts for the effect of customer sited DR, EE and DG. Because of the EGEAS results, not all of the programs used in AEG s assessment are incorporated into the ILF net forecast. The ILF reports both the gross and net forecasts. 2. What are the similarities in purpose and application for the AEG assessment and ILF at MISO? One of the purposes of AEG s DR, EE, DG assessment was to be incorporated into a net forecast in the ILF that accounts for the effect of customer sited DR, EE and DG programs in the ILF. Therefore, applications of the ILF net forecast data have taken the AEG assessment results into account. In addition, both the AEG assessment and ILF are intended to be a source of additional data for MISO. 3. How are building efficiency codes and standards incorporated into both the ILF and AEG assessment? Future building codes and standards are incorporated in the AEG study explicitly by using the LoadMAP model. Since it is a stock accounting model, it keeps track of when appliances are turning over. The model measures savings against the baseline technology available in each year. When there is a standard change the savings are less due to the more efficient baseline technology. Building codes are incorporated by modeling new construction separately from existing construction. The econometric approach used in the ILF captures the impact of changes in building codes and standards in the historical data. These changes affect the coefficients of the econometric models and thus, impact the forecast going forward. An implicit assumption is that future changes in codes and standards will be similar to those in the past. If future changes end up being more aggressive than past changes, the forecast will only capture a portion of the changes and end up being high (assuming all other factors are equal). Conversely, if future changes are less aggressive, the models will tend to come in low.

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