March 26, 2019 | Holyoke, MA

1. March 26, 2019 | Holyoke, MA Henry Yoshimura and Doug Smith ISO New England Demand Resources Working Group Assessing Energy Efficiency Measure Performance During Off-Peak Hours

2. Agenda • Background • Markets Committee Referral • Current Measurement and Verification (“M&V”) Approach (Generalized) • Options for Determining Demand Reduction Values (“DRVs”) During All Hours • Discussion of Other Potential Approaches • Next Steps

3. Background and Markets Committee Referral

4. Background • During the Nov. 2018 – Mar. 2019 timeframe, the Markets Committee was presented with different proposals to address settlement imbalances associated with the calculation of Capacity Performance Payments for energy efficiency resources (“EERs”) during Capacity Scarcity Conditions (“CSCs”) in off-peak hours • EERs refer to the portion of On-Peak Demand Resources and Seasonal Peak Demand Resources consisting of Energy Efficiency measures • “Off-peak hours” are those hours other than Demand Resource On-Peak Hours and Demand Resource Seasonal Peak Hours • The current FERC-accepted Tariff: • Excludes EERs from Capacity Performance Payments for CSCs occurring in off-peak hours • Assigns an Actual Capacity Provided (“ACP”) of zero to an EER if a CSC occurs in an off-peak hour • Charges the “underperformance” associated with the zero ACP to all resources with Capacity Supply Obligations (“CSOs”) on a CSO pro-rata basis

5. Background (cont.) • One potential solution offered was to assess the ACP of EERs for CSCs that occur in off-peak hours, and to use the resulting values to calculate Capacity Performance Payments for EERs • This approach requires a method that estimates EER performance in all hours • At this time, there is no consensus on a method by which to estimate EER performance in all hours for either existing or new measures

6. Markets Committee Referral • On March 5, 2019, the NEPOOL Markets Committee instructed the Demand Resources Working Group (“DRWG”) to: • Consider how EER performance in all hours for existing and new measures could be established and what, if any, additional methodological standards and reporting mechanisms are required to accommodate such a change • Prioritize options that require the least time and expense to develop and implement • The problem statement and referral is posted at: https://www.iso-ne.com/static-assets/documents/2019/02/a5_ee_problem_statement_and_referral.docx • The DRWG is to report potential options back to the Markets Committee, which may include time and cost estimates associated with implementing each option • The Markets Committee requests periodic reports of the DRWG’s progress • The first report will be made at the May 7-8, 2019 Markets Committee meeting

7. Current M&V Approach

8. Current M&V Approach (Generalized) • Equation (1) generally summarizes the approach used by program sponsors to estimate the energy savings produced by a single Energy Efficiency measure: • kWh Savingse= (kWb– kWe) x OH x RR x PF x ISR (1) • Where: • kWh Savingse = energy savings produced by Energy Efficiency measure e • kWb= kilowatt usage of baseline technology b • kWe = kilowatt usage of Energy Efficiency measure e • OH = annual operating hours of the end-use application • RR = savings realization rate based on impact evaluation studies • PF = savings persistence factor over the life of the measure • ISR = in-service rate, or portion of efficient units actually installed

9. Current M&V Approach (Generalized) (cont.) • kWh energy savings are transformed to kW capacity savings using a “coincidence factor study” that estimates the percentage of energy savings produced during Demand Resource On-Peak or Seasonal Peak Hours (“on-peak hours”) • Coincidence factors are developed from hourly load profiles of the customer class or building type into which the Energy Efficiency measure is installed, or from 24-hour load logger profiles • The average hourly demand reduction is the basis for the “demand reduction value” (“DRV”) of the Energy Efficiency measure [see equation (2)]: • On-Peak kW Savingse= kWh Savingsex CF / ON (2) • Where: • On-Peak kW Savingse = average hourly demand reduction of Energy Efficiency technology e during on-peak hours for the relevant season • CF = Coincidence factor for the relevant season • ON = Total Demand Resource On-Peak or Seasonal Peak Hours (as applicable) for the relevant season

10. Options for Determining DRVs DURING ALL HOURS

11. Options for Determining DRVsDuring All Hours • Average hourly demand reduction for all off-peak hours(single value approach) • Shaping currently known savings parameters • Modelling option • Bottom-up option

12. Average Hourly Load Reduction for Off-Peak Hours • Since On-Peak kW Savingse= kWh Savingsex CF / ON, and: • Off-Peak kWh Savingse = kWh Savingse x (1 - CF) (3) • The average hourly demand reduction of Energy Efficiency measure e during off-peak hours is: Off-Peak kW Savingse = kWh Savingse x (1 – CF) / OFF (4) • Where: • Off-Peak kW Savingse = average hourly demand reduction of Energy Efficiency measure e during off-peak hours for the relevant season • CF = Coincidence factor for the relevant season • ON = Total Demand Resource On-Peak or Seasonal Peak Hours (as applicable) for the relevant season • OFF = Total off-peak hours (hours other than Demand Resource On-Peak or Seasonal Peak Hours as applicable) for the relevant season

13. Shaping currently known savings parameters • The cost and time to estimate equation (4) are low, but the result will likely underestimate savings for off-peak hours near the peak period, and overestimate savings for off-peak hours far from the peak period • Intuitively, savings produced by a portfolio of Energy Efficiency measures should be greater during high-load periods, and lower during low-load periods • Individual Energy Efficiency measures produce savings during the operating hours of the affected end-use application, but a large portfolio of Energy Efficiency measures affecting a cross-section of end-use applications likely produce savings that follow the end-use load shape • “Energy efficiency resources are not similarly situated to other capacity resources because they do not actively perform in real-time—they represent a pre-determined level of load reduction that is constant as a percentage of that resource’s load….” (May 30, 2014 Order at P 89 emphasis added) • Building on this concept, off-peak energy savings could be allocated among off-peak hours based on load levels

14. Shaping currently known savings parameters (cont.) Shaping optionA: • ACPee, off-peak = ACPee, on-peak x ASL/PSL x 1.08 • Where: • ACPee, on-peak = The EER’s ACP had the CSC occurred in an on-peak interval that is closest in time to the CSC that occurred • ASL = actual system load during CSC interval • PSL = projected seasonal peak load (the same peak load forecast used by the ISO to determine Demand Resource Seasonal Peak Hours) • 1.08 = gross-up for avoided T&D losses • This approach can be implemented immediately at low cost • But ACPee, off-peak is not calibrated to total off-peak energy savings estimated through M&V studies [where Off-Peak kWh Savings = kWh Savings x (1 - CF)], so summing ACPee, off-peak for every off-peak hour will probably not equal total off-peak energy savings

15. Shaping currently known savings parameters (cont.) Shaping optionB: • Distribute total seasonal off-peak energy savings using an average load shape for the season • Similar to the allocation of wholesale energy to Profiled Load Assets, which uses class-average load shapes developed from distribution company load research • Σ(Off-Peak kWh Savingse)h= Σ[kWh Savingse x (1 - CF)] x LSPh (5) • Where: • Σ(Off-Peak kWh Savingse)h is the sum of kWh savings for all measures e in hour h • LSPh = load shape percentage for hour h, which is the amount of consumption in hour h as a percentage of total consumption based on an average load shape • This approach allocates off-peak energy savings developed from M&V studies to each off-peak hour • The time and cost of implementing this approach depends on the details: • How should dynamic load shape data be used to develop hourly off-peak allocators? • Which load shape should be used (class average, distribution company, system)? • Should a single 24x7 load shape or load shapes for different day types (e.g., business day, Saturday, Sunday/holiday) be developed and used?

16. Modelling Approaches • The National Renewable Energy Laboratory (NREL) and Lawrence Berkeley National Laboratory (LBNL) have kick-offed a three-year project to estimate the “Time-Sensitive Valuation of Energy Efficiency” • See End-use_Load_Profiles_TAG_ 112718_compressed.pdf • Validated end-use load profiles for U.S. building stock will be used to develop calibrated, open-source building stock end-use models with the ability to estimate EE/DR savings profiles for existing and emerging technologies • The resulting savings profiles could be used to establish hourly/sub-hourly EE performance • Once the models are established and calibrated, the cost of using them should be relatively modest • But the results will not be available until the 2021-2022 timeframe Source: Navigant Massachusetts RES 1 Baseline Load Shape Study

17. Bottom-Up Approaches • As discussed earlier, kWh energy savings are transformed to kW capacity savings using a “coincidence factor study” • Coincidence factors are developed from hourly load profiles of the customer class and/or building type into which the Energy Efficiency measure is planned to be installed, or from 24-hour load logger profiles • So another approach would be to review the hourly load profiles and/or load logger profiles to determine 24x7 savings profiles • As under the shaping approaches, these profiles could consist of a single 24x7 load shape or load shapes for different day types • While this will produce accurate results, reviewing profiles to determine 24x7 savings estimates for existing measures would likely be time-consuming and costly • For new measures, the incremental cost of producing 24x7 savings estimates may prove to be relatively modest compared to the cost of estimating on-peak savings only, but the approach is likely to be more expensive than shaping or modelling approaches

18. Are there other potential approaches that should be considered? Discussion of other potential Approaches M&V

19. Next steps

20. Next Steps • Action items and assignments • Meeting dates • Next scheduled DRWG meeting is April 29, 2019 • Draft report format and review • Presentation of report to the Markets Committee • The Markets Committee requests periodic reports of the DRWG’s progress – the first report will be made at the May 7-8, 2019 Markets Committee meeting