Electric “Grid” Savings and Non-Electric Benefits for Residential HVAC-affected UES Measures Regional Technical Forum March 20, 2013

Overview For residential measures that effect heating and cooling usage: – RTF electric savings estimates should be reliable from an electric utility planning perspective (i.e. “Grid Savings”). Measured Savings are considered reliable. – There appear to be non-electric benefits the RTF can account for in its cost-effectiveness tests. Measured Savings < Engineering Savings. Primary questions: – Is the following proposed framework for “Grid Savings” and NEB’s correct? – How should RTF monetize non-electric benefits? 2

Framework 3

4 Engineering Savings (“The Whole Pie”) Definition: Estimated electric energy savings based on physics (lower UA = lower heating energy use). Example: Engineering model assumes 100% electrically heated houses and “typical” usage.

5 Measured Electric Savings (a.k.a “Grid Savings”) Definition: Electric energy savings for the population, measured through submetering or billing studies.

6 Non-Electric Benefits Definition: Portion of the Engineering Savings that apply to the following two non-electric components: Fuel Savings (Non-electric) -Example: Occupant stops using their wood stove in the efficient-case, in favor of the electric heating system. -Example: Occupant continues using their wood stove, but uses less wood because of the lower house heat loss. Increased Comfort (a.k.a. “Takeback”) -Example: Occupants operate their house at a warmer (winter) and cooler (summer) temperature in the efficient- case.

7 Engineering Correction Definition: Adjustment to engineering savings to account for non-typical usage. Example: Partial Occupancy; occupants are away for the winter months and leave t-stat at a very low setting.

8 Not to Scale – These will vary by program, region, modeling method, etc. – Some slices of the pie could be zero (or negative).

Long-Term Effects Non-Electric Fuel usage and “Comfort Level” varies depending on economic conditions and other factors. – Billing analyses & metering studies are “snapshots in time”. For the same measure, the NEB’s could vary year-to-year. – Note how this could change Measured Electric Savings – Engineering Savings would see less change, if any. 9 We’re not likely to solve this issue today. Instead, since the data sources will vary, corrections for “long-term effects” will need to be made on a measure-by-measure basis per RTF judgment.

Uncertainty Engineering Savings and Measured Electric Savings carry with them uncertainty – If the uncertainty is large, it could (and should) call into question including Non-Electric Benefits. For Example: 10 We’re not likely to solve this issue today. Instead, since the data sources will vary, decisions on including Non-Electric Benefits will need to be made on a measure-by-measure basis per RTF judgment.

Examples DHP Weatherization 11

IDItemSource/MethodHeating Zone 1 Heating Zone 3 A Engineering Savings Metering Study 4000 IDItemSource/MethodHeating Zone 1 Heating Zone 3 A Engineering Savings Metering Study 4000 B Measured Electric Savings Billing StudyAll Sites IDItemSource/MethodHeating Zone 1 Heating Zone 3 A Engineering Savings Metering Study 4000 B Measured Electric Savings Billing StudyAll Sites C Measured Electric Savings + Non-electric Fuel Savings Billing Study Filtered for No Supplemental Fuel IDItemSource/MethodHeating Zone 1 Heating Zone 3 A Engineering Savings Metering Study 4000 B Measured Electric Savings Billing StudyAll Sites C Measured Electric Savings + Non-electric Fuel Savings Billing Study Filtered for No Supplemental Fuel Non- electric Benefits Fuel SavingsC – B IDItemSource/MethodHeating Zone 1 Heating Zone 3 A Engineering Savings Metering Study 4000 B Measured Electric Savings Billing StudyAll Sites C Measured Electric Savings + Non-electric Fuel Savings Billing Study Filtered for No Supplemental Fuel Non- electric Benefits Fuel SavingsC – B Increased ComfortA - C Using DHP as an Example 12 Grid Savings (kWh) Non-Electric Benefits (need to monetize) Notes: 1. All values in kWh/yr. 2. Values and method are for example only – we’ll discuss DHP measure specifics later. 3. Engineering Correction is assumed to be 0 kWh/yr based on design of Metering Study to include randomly selected sites.

IDItemSource/Method AEngineering Savings SEEM runs calibrated to RBSA “post” t-stat setting; houses with “good” electric & gas bills only T-stat: 68°F pre & post BEngineering Savings – Increased Comfort SEEM runs calibrated to RBSA “pre” and “post” t-stat setting; houses with “good” electric & gas bills only Tstat: 65°F pre 68°F post CEngineering Correction Rough estimate based on RBSA data % of houses with electric & gas heat only and with poor PRISM R-square DNEB Fuel Savings Rough estimate based on 2 sources i. RBSA: % of heat supplied by “other” fuels in electric heat homes ii. DHP: % of fuel savings in the DHP measure Measured Electric SavingsB – C – D Non Electric Benefits Fuel SavingsD IDItemSource/Method AEngineering Savings SEEM runs calibrated to RBSA “post” t-stat setting; houses with “good” electric & gas bills only T-stat: 68°F pre & post BEngineering Savings – Increased Comfort SEEM runs calibrated to RBSA “pre” and “post” t-stat setting; houses with “good” electric & gas bills only Tstat: 65°F pre 68°F post IDItemSource/Method AEngineering Savings SEEM runs calibrated to RBSA “post” t-stat setting; houses with “good” electric & gas bills only T-stat: 68°F pre & post BEngineering Savings – Increased Comfort SEEM runs calibrated to RBSA “pre” and “post” t-stat setting; houses with “good” electric & gas bills only Tstat: 65°F pre 68°F post CEngineering Correction Rough estimate based on RBSA data % of houses with electric & gas heat only and with poor PRISM R-square IDItemSource/Method AEngineering Savings SEEM runs calibrated to RBSA “post” t-stat setting; houses with “good” electric & gas bills only T-stat: 68°F pre & post BEngineering Savings – Increased Comfort SEEM runs calibrated to RBSA “pre” and “post” t-stat setting; houses with “good” electric & gas bills only Tstat: 65°F pre 68°F post CEngineering Correction Rough estimate based on RBSA data % of houses with electric & gas heat only and with poor PRISM R-square DNEB Fuel Savings Rough estimate based on 2 sources i. RBSA: % of heat supplied by “other” fuels in electric heat homes ii. DHP: % of fuel savings in the DHP measure IDItemSource/Method AEngineering Savings SEEM runs calibrated to RBSA “post” t-stat setting; houses with “good” electric & gas bills only T-stat: 68°F pre & post BEngineering Savings – Increased Comfort SEEM runs calibrated to RBSA “pre” and “post” t-stat setting; houses with “good” electric & gas bills only Tstat: 65°F pre 68°F post CEngineering Correction Rough estimate based on RBSA data % of houses with electric & gas heat only and with poor PRISM R-square DNEB Fuel Savings Rough estimate based on 2 sources i. RBSA: % of heat supplied by “other” fuels in electric heat homes ii. DHP: % of fuel savings in the DHP measure Measured Electric SavingsB – C – D Non Electric Benefits Fuel SavingsD Increased ComfortA – B IDItemSource/Method AEngineering Savings SEEM runs calibrated to RBSA “post” t-stat setting; houses with “good” electric & gas bills only T-stat: 68°F pre & post BEngineering Savings – Increased Comfort SEEM runs calibrated to RBSA “pre” and “post” t-stat setting; houses with “good” electric & gas bills only Tstat: 65°F pre 68°F post CEngineering Correction Rough estimate based on RBSA data % of houses with electric & gas heat only and with poor PRISM R-square DNEB Fuel Savings Rough estimate based on 2 sources i. RBSA: % of heat supplied by “other” fuels in electric heat homes ii. DHP: % of fuel savings in the DHP measure Measured Electric SavingsB – C – D IDItemSource/Method AEngineering Savings SEEM runs calibrated to RBSA “post” t-stat setting; houses with “good” electric & gas bills only T-stat: 68°F pre & post Using Weatherization as an Example 13 Note: This method is shown for illustration of the framework only; it has not been reviewed by the RTF and may not meet the RTF’s guidelines.

Next Steps In both examples, Non-Electric Benefits are quantified in kWh’s. We need to then monetize the Non-Electric Benefits – (assuming they’re not zero) 14

ProCost Inputs 15 Data Source(s) kWh/$ Conversion

How to Monetize the Non-Electric benefits? Option 1: Convert each Non-Electric Benefits into Dollars – Non-Electric Fuel Savings Convert kWh savings to cords of wood savings to dollar savings – Issue: Many assumptions needed (Btu/cord; efficiency of stove, $/cord, pollution benefit, etc.) – Increased Comfort Value at the cost of electricity – Occupant chose to pay for more electricity, so value of comfort should be at least equivalent to the price of electricity, if not more. – Issue: Split between Increased Comfort and Non-Electric Fuel Savings is unknown. Option 2: Value both Non-Electric Benefits at the cost of electricity – Same logic as for Increased Comfort above – The “many assumptions” for converting kWh savings to cords of wood to dollar savings would likely be “calibrated” to this value. (Value of wood calibrated to be no lower than value of electricity.) Issue: Use Retail or Wholesale cost of electricity? – Guidelines specify avoided costs (wholesale). – Which is a better proxy for consumer economic value of non-electric fuel savings? increased comfort? 16

Decisions 1.Adopt the presented framework for quantifying Measured Electric Savings and NEB’s? – Current Framework NEB’s have not been (explicitly) included in the cost-effectiveness test. Measured Electric Savings have sometimes included NEB’s. – “Long-term” savings. – Proposed Framework Quantify Measured Electric Savings and NEB’s according to framework. – Any decision to adjust values for “long-term effects” or uncertainty would be explicit and measure-specific. Include NEB’s in cost-effectiveness test. 2.How to Monetize NEB’s? – Which Option? Option 1: Convert each Non-Electric Benefits into Dollars (wood & electricity); or Option 2: Value both Non-Electric Benefits at the cost of electricity – Which value of electricity? Retail? Wholesale? – Other Options 17

Background Slides 18

Related slides from the January 2014 RTF Meeting (“SEEM 94 Calibration to RBSA Data” Presentation) 19