Direction on Guidelines Savings Definition Path: CONTINUED Remaining Useful Life (RUL) and Measure Interaction Regional Technical Forum February 19, 2014

January RTF Meeting Presentation Presentation Decision made on – Current Practice Baseline – Pre-Conditions Baseline Decision to postpone to February the discussion of RUL and Measure Life – Members asked to send alternate language, or concerns to staff. 2

Input Received Since January Meeting From Staff – Edited “vote” on Measure Interactions Now “General Population Characteristics” a “Yes****” for Lifetime Savings and First- year Savings. (previously a “No”) – If program participants match general population – Modified Proposed Motion Language From Others – … 3 +: Remember that “Option 3”, which was approved late last year, was a method to prorate “last measure in” savings to avoid under-counting (or over-counting) total savings. (Ex: Option 3 + )

Measure Interactions 4

Proposal: “To the extent practical, measure identifiers should be used to account for significant measure interaction. For example, the identifier ‘heating system type’ could be used to account for the interactions between envelope improvements and heat pumps. When measure identifiers are not sufficient to account for all significant interactions, measure savings should be estimated using data expected by the RTF to represent program participants during the sunset period. These data should describe the interactive measures present when each measure was installed, and which interactive measures were installed simultaneously. Data collected directly from a sample of recent program participants is likely to serve these needs if the characteristics of the program participants are not expected to be changing quickly. For measures where interactive measures are not expected to be installed simultaneously, general population characteristics or characteristics of eligible sites may be judged to sufficiently represent program participants. The methods used to deal with measure interaction should be documented in the summary sheet.” 5

“Significant” “Interaction is significant if the RTF determines that it is likely to account for more than 10%* of the measure savings. ” What tools would the RTF like to use to determine “significance”? What is the appropriate level of effort? 6 * Staff has interpreted this to mean +/- 10% (not +/- 5%).

Proposed Significance Test Procedure 1.Identify Measure 2.Identify all possible Interactive Measures 3.Define the proposed expected conditions for each interactive measure, estimate savings. – Example: General Population Characteristics, if available (and characteristics of subset of eligible sites, if available). – The expected conditions for interactive measures are constant across the Baseline and Efficient-case Conditions. 4.Determine conditions for each interactive measure where Measure savings differ by +/- 10% from savings calculated using proposed expected conditions (“Book-ends”) 5.RTF judges whether measure interaction is expected to be significant and whether candidate proxy is reasonable. – To help, we’ll look at distribution of existing conditions (RBSA), technically feasible minimums and maximums, etc. 7

Measure Interaction Decision Choices 1.Interaction is not significant (  Proven) 2.Include interactive measure as a measure identifier (  Proven) 3.Use available data (  Proven) I.Program Data, if representative II.General Population Characteristics Data, if representative III.Other Data, if representative 4.Collect data (  Planning or Provisional) 8

Example 1 Measure – Thermostatic Shower Restriction Valve, Retail Delivery Interactive Measure +/- 10% Book-end Expected Condition (RBSA) +/- 10% Book-end Showerhead2.00 gpm2.21 gpm2.44 gpm Electric Water Heater Type HPWH (51%) 99.7% Resistance Resistance (0.2%) GFX (ran out of time) Source: RBSA 9 “+/- 10% Book-end”: Condition of the interactive measure which cause measure (i.e. TSRV) savings to vary by + or – 10% from the measure savings calculated using the “expected condition” of the interactive measure. +/- 10% Book-ends

Electric Water Heater Type 1. Savings interaction with water heater typeis not significant NoNot true. 2. Include water heater type as a measure identifier MaybeWould be difficultfor programs to pull off with a retail delivery 3.I. Use availablerepresentative program data NoNo data available 3.II. Use RBSA data asrepresentative of program YesBecauseof tiny fraction of HPWH in Region, RBSA water heater mix likely to represent program. 4. Collect water heater type data on a sample ofmeasure installations MaybeGood savings reliability, but program would need to be designed in a way to allow contact with participantsdifficult with retail delivery GFX……… – 4. Collect showerhead flow rate data on a sample ofmeasure installations MaybeGood savings reliability, but program would need to be designed in a difficult with retail deliveryway to allow contact with participants– 3.I. Use availablerepresentative program data NoNo data available3.II. Use RBSA data as representative of program MaybeMay not be representative of program.Small gap between green bars. -Measure could be packaged with low flow showerhead, or -Program might be designed to target high flow showerheads 2. Include showerhead flow rate as a measure identifier MaybeWould be difficultfor programs to pull of with a retail delivery Example 1 – Interactive Measure Decisions 10 MeasureDecision ChoiceDecisionNotes Shower- head 1. Savings interaction with showerheadis not significant NoNot true.

Example 2 Measure: Attic Insulation – R-0 to R-38 “Back of the Envelope” – 1344 ft 2 prototype, Portland Weather Interactive Measure +/- 10% Book-end Expected Condition (RBSA where Attic = R-0, electric heat) +/- 10% Book-end WindowsU-0.57U-0.67U-0.94 Infiltration0.50 ACHn0.62 ACHn0.75 ACHn Htg. System Heat Pump (40%) 24% HP Resistance (12%) Wall Ins.R-13~ R-7~ R-5 Floor Ins.~ R-11~ R-5~ R-1 Duct Tight. 10% Supply 12% Return 12% Supply 17.5% Return 23% Supply 23% Return CC&SPTCS15% PTCS0% PTCS Lighting 90% CFL (6%) 30% CFL 0% CFL (3%) Source: RBSA 11 RBSA

Level of Effort: Huge! (if no data) Weatherization Example Analyze Each Measure (33 iterations) – For each heating system: Heat Pump, eFAF, Zonal Attic: R0-38, R11-38, R19-38 Floors: R0-30, R11-R30 Windows: Double-0.30, Single-0.30, Walls, Duct Sealing, CC&S, Infiltration – In each heating zone? (99 iterations) Analysis and Decisions will need automation 12 Because of the difficulty for programs, the RTF may not want to deal with significant measure interaction through further disaggregation of measures (i.e. more measure identifiers). Instead, it may wish to consider use of RBSA data (choice 3.II) or program data collection (choice 4) for weatherization measures.

Decision Measure Interactions “I ________ move to adopt the following guidelines language: To the extent practical, measure identifiers should be used to account for significant measure interaction. For example, the identifier ‘heating system type’ could be used to account for the interactions between envelope improvements and heat pumps. When measure identifiers are not sufficient to account for all significant interactions, measure savings should be estimated using data expected by the RTF to represent program participants during the sunset period. These data should describe the interactive measures present when each measure was installed, and which interactive measures were installed simultaneously. Data collected directly from a sample of recent program participants is likely to serve these needs if the characteristics of the program participants are not expected to be changing quickly. For measures where interactive measures are not expected to be installed simultaneously, general population characteristics or characteristics of eligible sites may be judged to sufficiently represent program participants. The methods used to deal with measure interaction should be documented in the summary sheet.” 13

Remaining Useful Life (RUL) 14

RUL Proposal: – For all pre-conditions measures, estimate RUL based on best available information. If RUL is likely longer than the 20 year planning horizon, then RUL equals measure lifetime. 15

UES Example: Grocery ECMs for Display Cases (Replace existing Shaded Pole Motor with new ECM) 16 Today Measure Life = Life of new ECM (RUL = EUL) Proposed Measure Life = Remaining life of existing Shaded Pole Motor Note: 6-year estimate of remaining life of existing shaded pole motor is for illustration only. Note: The issue of forecasting the future current practice (at time = RUL) will be discussed later, after the RTF decides on RUL. Future Current Practice?

UES Example: Attic Insulation R11-R38 (Add insulation to an existing attic with R11, go to R38) 17 Today Measure Life = Life of insulation (RUL = EUL) Proposed Measure Life = Remaining life of existing R11 =

Standard Protocol - Discussion Two Optional Paths, depending on measure – “Deem” an RUL for all installations Similar to UES – Cannot “deem” the same RUL for all installations Similar to Custom – See next slides. 18

Custom Measure Example: Chiller Early Replacement 19 Today Measure Life = Life of new ECM (RUL = EUL) Proposed Measure Life = Remaining life of existing chiller Note: 3-year estimate of remaining life of existing chiller is for illustration only.

Custom Measure Issue: RUL is unknown and the fate of the measure depends on its value If RUL is big enough for cost-effective measure… If RUL estimate too short, measure not cost-effective… 20

Decision Remaining Useful Life “I _______ move to adopt the following guidelines language: – For all pre-conditions measures, estimate RUL based on best available information. If RUL is likely longer than the 20 year planning horizon, then RUL equals measure lifetime.” 21

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(Old) Decision Measure Interactions “I ________ move to adopt the following guidelines language: To the extent practical, measure identifiers should be used to account for significant measure interaction. For example, the identifier ‘heating system type’ could be used to account for the interactions between envelope improvements and heat pumps. – When measure identifiers are not sufficient to account for all significant interactions, measure savings should be estimated using data from a representative sample of recent program participants. These data should describe the interactive measures present when each measure was installed, and which interactive measures were installed simultaneously. If collection of recent program participant data is not practical, and a reasonable proxy for participant data is available, measure savings should be estimated using this proxy. The methods used to deal with measure interaction should be documented in the summary sheet.” 23