1. Continued: DHP for New Construction Current Practice Baseline Regional Technical Forum Adam Hadley February 17, 2016

2. Background This is a follow-up to the question from last meeting about how to set the baseline for a new proposed measure: DHP for new construction – Q: Should the baseline include all eligible end users (all new houses in the region, which includes a high fraction of gas heated houses) or should the baseline consist only of the subset of houses likely to install a DHP Why no subcommittee? – We discussed having a subcommittee, but there was room on today’s agenda, so we’re continuing with the discussion from last meeting with the full RTF – We also anticipate any resolution on the remaining outstanding “current practice” baseline issues (see extra slides) will not have an impact on this decision, and vice versa 2

3. Guidelines Language (from Roadmap) 3

4. 3.2.1 Current Practice A current practice baseline is used if the measure affects systems, equipment or practices that are at the end of their useful life or for measures delivering new systems, equipment or practices, e.g., ENERGY STAR® specifications for new homes. There are a number of possible indicators that current practice is the appropriate baseline: – Measure is delivered as part of a new construction project or is subject to the requirements of current state and local building codes or federal standards, including major renovations that are covered by codes and standards. – Relevant equipment is no longer operable and must be replaced – Equipment is old and due to increasing frequency and difficulty of repairs and maintenance the end user has firm plans to replace the equipment – Equipment must be replaced due to regulatory requirements, such as those promulgated by the US EPA (Environmental Protection Agency) – Existing equipment cannot serve the end user’s likely near-term loads For these measures, the baseline is defined by the typical choices of eligible end users in purchasing new equipment and services at the time of RTF approval. The RTF estimates this baseline based on recent choices of eligible end users in purchasing new equipment and services. These choices may be inferred from data on shipments, purchases (equipment or services) or selected design / construction features. For example, the baseline for more efficient televisions is the average efficiency of recent television shipments. The period between RTF approval and the sunset date should be shortened as needed to reliably estimate savings for a measure whose baseline is rapidly changing The RTF may determine that current state and local building codes or federal standards provide a reliable definition of the baseline for these measures. As a general rule the RTF will use a baseline that is characterized by current market practice or the minimum requirements of applicable codes or standards, whichever is more efficient. The RTF may decide to use an alternative current practice based on other factors. 4

5. Why have we used “typical choices of eligible end users”? It’s objective It’s a compromise – It avoids the subjective and very difficult issues associated with attribution, but it doesn’t get us program-caused savings – It keeps the RTF out of program design – It sends a signal of the potential savings available under today’s market conditions, similar to the Plan (without attribution) Note: The RTF and Council has always considered this appropriate for current practice measures

6. Back to the DHP Example Q: How to establish the baseline? Options Identified so Far 1.Look strictly at the typical choices of “Eligible End Users”, per the Guidelines 2.Consider a subset of eligible end users – the typical choices of “Likely Program Participants”

7. Option 1: Eligible End Users If we go strictly by “eligible end users”, all the recent new construction in the Region would be included in the baseline and electric savings would be negative – As discussed at the last meeting, there would be options to split the measure by objective eligibility criteria (measure identifiers) and find a pocket of positive savings, for example: Measure identifier groups: Gas availability, House Size, Both – Pros Objective answers from straightforward research Sends signals to programs regarding savings availability under today’s market conditions – Cons Can leave savings on the table (not UES-able) Does not get at savings caused by the program Baseline Heating SystemPrevalenceDHP Electric Savings DHP1%0 kWh/yr Zonal Electric3%2,900 kWh/yr Electric FAF2%4,600 kWh/yr ASHP8%0 kWh/yr Gas FAF81%–5,000 kWh/yr Wood/Other4%–5,000 kWh/yr All100%–4,100 kWh/yr

8. Option 2: Likely Program Participants A subset of eligible end users – the likely participants – may have a significantly different baseline than the whole population of eligible end users – Is there a way for the RTF to reliably estimate the baseline for likely participants? Important: If so, this would get us the savings caused by the program – The electric savings could be significant For example, assuming the program effectively targets only new houses that would have installed DHP, zonal electric, and electric FAF, savings could be about (positive) 3,000 kWh/yr Baseline Heating SystemPrevalenceDHP Electric Savings DHP1%0 kWh/yr Zonal Electric3%2,900 kWh/yr Electric FAF2%4,600 kWh/yr ASHP8%0 kWh/yr Gas FAF81%–5,000 kWh/yr Wood/Other4%–5,000 kWh/yr All5%3,000 kWh/yr

9. Option 2 in-depth How to reliably estimate the baseline for “likely participants”? Possible Approaches: A.Ask builders/homeowners of recent new houses with DHP’s what they would have installed without the program – Pros This would get at the savings caused by the program (if we get it right) – Cons Responses depend on program design (would RTF specify program design?) This is very difficult, if impossible, to do reliably – it’s subjective This is an attribution question, which the guidelines (and Tom Eckman) currently advises against (indirectly, in the case of the guidelines) 1.3.2. Savings Savings is defined as the difference in annual energy use between the baseline and post (after measure delivery) periods, which is caused by the delivery of a measure. The terms “net” or “gross” are intentionally not used to modify the term “savings,” as they may conflict with the definition of “baseline,” provided in section 3.2. The current practice baseline defines typical choices of eligible end users, as dictated by codes and standards and the current practices of the market. The most important conflict would arise if savings were estimated against a current practice baseline and then those savings were further adjusted by a net-to-gross ratio, where the net-to-gross ratio was the probability that the measure would have been delivered in the absence of program influence.

10. Option 2 in-depth (Continued) How to reliably estimate the baseline for “likely participants”? Possible Approaches: B.Define builders/homeowners who are likely to install a DHP, then see what those builders/homeowners install – Pros This would get at the savings caused by the program (if we get it right) – Cons It would be very difficult to reliably pre-define builders/homeowners who are likely to install a DHP – Very subjective C.Use the collective judgment of the RTF to estimate the baseline heating system mix for “likely program participants” – Pros This would save time and money over approaches A and B – It could be argued to have similar reliability, too This would get at the savings caused by the program (if we get it right) – Cons Ultra Subjective May come down to a thumb wrestling contest D.Your idea here ________

11. CAT Perspective: We can try Option 2, but… Options 1.Look strictly at the typical choices of “Eligible End Users”, per the Guidelines – This is an intentional compromise Savings don’t exactly align with the program accomplishments, but they align with the Act (in the context of not considering attribution) The method aligns with the RTF’s strengths (objectivity) and avoids its weaknesses (subjectivity) 2.Consider a subset of eligible end users – the typical choices of “Likely Program Participants” – This very likely to get messy. RTF Pre-guidelines: Chaotic RTF Post-guidelines: Orderly

12. Are there implications for the Guidelines? If we go with Option 1, “eligible end users”: No If we go with Option 2, “likely program adopters”: Yes – We could go two ways: Add the ability to consider “likely program participants” (or “eligible end users”)? Change to “likely program participants” only? – Either way, this would significantly change the meaning of current practice for the RTF

13. Proposed Motion “I __________ move the RTF choose to pursue the following option with respect to the guidelines definition of current practice: – Option 1: ‘typical choices of eligible end users’ OR – Option 2: ‘typical choices of likely program participants’ OR – Option 3: ______________”

14. Extra Slides

15. Other Outstanding Guidelines Issues Related to “Current Practice” Baseline Year – Recommendation to be more specific about using the most up-to-date data and avoid having the RTF make forecasting assumptions Incorporating Code or Standard into Baseline – Recommendation to add a statement on how to deal with sales data that include products that are not compliant with the standard or code Hierarchy of Current Practice Data – Recommendation to say sales data are most often the best – Recommendation to describe when to use average and when to use mode – Recommendation that use of data from multiple points in time are better (one point in time might be misleading) Representativeness of Data – Recommendation to add a sentence in the guidelines to the effect of: All sales data are not created equal Comparability with the Council’s Plan – Recommendation is to have RTF use current practice baseline where the Plan used current practice baseline (non-res lighting: RTF uses pre-conditions; Plan uses current practice) Include Recent Program Participants, or Not – Recommendation to add statement like this: Typically, the RTF does not exclude from its current practice baseline recent program participants. The guiding assumption is that programs permanently change the market; their effect on current market practice efficiency is “sticky”. This may not always be the case, however. In some cases, there may be evidence to show the program does not permanently change the market practice efficiency and in theses cases the RTF may adjust the current practice baseline accordingly. 15