1. Deemed Savings Methodologies Reid Hart, PE Associate Director, Technical Research July 2009 – Regional Technical Forum

2. 2 Deemed Saving Methodologies Need for a New Deemed Method Relevant Baseline Parameters Approaches Decision Framework Matrix Expected Value Deemed Savings Seeking Approval as Provisional Method

3. 3 Need for a New Deemed Method Current approaches –Custom savings require pre-review and approval –Calculators work well with energy auditor –Deemed savings desired for contractor delivery Limits on deemed savings –Very few commercial HVAC items –Savings may be excessively conservative –Approval of deemed savings not always timely Desired Method –Covers range of conditions –Arrives at appropriate program-wide savings

4. 4 Relevant Baseline Parameters Typically: Building Type & Vintage –Vintage not account for retrofit changes –Building types can be generalized Meta Parameters (Require Separate Savings) –Major climate zones –Heating fuel type Analyzed Baseline Parameter Variation –Internal loads: lighting; density –Envelope: glazing; perimeter/area ratio –Schedule –Measure specific parameters

5. 5 Measure Specific Baseline Parameters Premium Ventilation Package as an exmple: –Economizer found changeover –Economizer maximum outside airflow –Minimum outside air setting (Example field data) Source: Ecotope EWEB study – 2001

6. 6 Parameters for Premium Ventilation ParameterSymParameter variation in baseline BEFORE measure is installed Internal LoadL+1.8 LPD, 1.5 plug, 100 sf/person LPD=1.8 w/sf LPD; eQuest defaults DensityL-1.0 w/sf LPD; eQuest defaults VentilationV+37.6 cfm/person Minimum=31 cfm/person (typical) V-22.6 cfm/person GlazingG+Low-e Argon, double pane Type=Double pane, solar Bronze G-Single Pane EconomizerE++B, double stage ChangeoverE+C, single stage =D or Snap Disk E-Failed Economizer EconomizerM+80% Max OSA Max OSA=65% Max OSA M-50% Max OSA

7. 7 Individual Baseline Parameter Impact on Savings

8. 8 Parameter Sensitivity

9. 9 Unit Change Minimizes Some Parameters kWh/square foot to kWh/ton

10. 10 Approaches Site specific approaches –Custom analysis –Field based monitoring –Field-data driven model –Energy bill adjusted parametric tool –Parametric tool (calculator) –Simplified analysis (e.g. lighting spreadsheet) Deemed approaches –Matrix method / decision framework –Deemed savings (vintage, building type, climate) –Unit rebate –Expected value deemed method

11. 11 Decision Framework Matrix Focus on most sensitive parameters; group results

12. 12 Matrix Results; Provide Savings Table Internal Density Base ConditionL-L=L+ Savings Matrix 1.0 w/sf1.8 w/sf call center Ventilation Minimum V-  15% =-- V=  20% +=- V+  25% +++= Condition Deemed Savings FromGas HeatHP Heat TableGasElectric Abovetherms/tonkWh/ton - 36214433 -27182557 =44363985 +634061336 ++753841479

13. 13 Expected Value Deemed Savings Uses decision analysis methodology –Typical for supply-side resource risk assessment –Allows multiple parameters or influences –Expert judgment can be applied to parameter probability distribution

14. 14 Decision Tree for Expected Value Analysis Each influencing variable assigned states, each with –Probability of occurrence –Impact on savings

15. 15 Parameter Savings Impact and Probabilities ParameterSymParameter variation Factors for % of neutral savings in baseline BEFORE Gas Heat HP Heat measure is installedProbabilityGasElectric Internal Load L+ 1.8 LPD, 1.5 plug, 100 sf/person 20%0.9090.7320.825 LPD= 1.8 w/sf LPD; eQuest defaults 45%1.000 DensityL- 1.0 w/sf LPD; eQuest defaults 35%1.2951.00031.212 VentilationV+37.6 cfm/person25%0.6591.0271.162 Minimum=31 cfm/person (typical)50%1.000 V-22.6 cfm/person25%1.2820.9790.806 GlazingG+Low-e Argon10%0.8610.9290.869 Type=Double Bronze40%1.000 G-Single Pane50%1.0791.1181.103 EconomizerE++B, double stage5% 0.5000.750 ChangeoverE+C, single stage30% 0.7150.895 =D or Snap Disk45% 1.000 E-Failed Economizer20% 1.1091.040 EconomizerM+80% Max OSA20% 0.8970.964 Max OSA=65% Max OSA70% 1.000 M-50% Max OSA10% 1.0821.029

16. 16 Simplified Interaction Adjustment Simplified correction adjustment factors – limit adjustment Parameter Combination Impacts and Probabilities Higher quality as runs limited cf multiple regression Compare to NeutralLPD/ Density Econo ChangeoverGlazing Ventilation MinimumEcono Max Factor of All Combined Run Combination Adjustment Plus1.2121.0401.1031.1621.0291.6631.5170.912 Minus0.8250.8950.8690.8060.9640.4990.4240.850 Simplified approach to adjust for combination impact from multiple parameter changes Parameter Combination Probability Gas HeatHP Heat GasElectric InteractionLim+All parameters increase10%0.8650.9240.912 factorsavg() 25%0.9320.9620.956 from full1Single Parameter change30%1.000 combinationavg() 25%1.2150.8250.925 Lim-All parameters decrease10%1.4300.6490.850

17. 17 Program-wide Savings Distribution Probability of different savings results based on range of baseline influences and combinations

18. 18 Program-wide Expected Value (EV) Range of possible savings shown Expected value represents program-wide results

19. 19 Compare Matrix & Expected Value Matrix Framework Whole building understanding needed Multiple saving values Site specific savings Gaming inputs possible Representation difficult beyond two parameters Multiple possible savings or rebates make it difficult for contractor delivery 1944 runs required for 5 parameters needing 243 cases (3 states @, 2 climates, 2 heat types) Expected Value No need for information outside discipline Single saving value Program-wide savings Cannot game Multiple parameters can be considered Single savings and rebate amount makes contractor planning and marketing easy 96 runs required for 5 parameters needing 12 cases (3 states @, 2 climates, 2 heat types)

20. 20 Further Research Current analysis is an “example” without full development; need –further develop expected values –research into extant building characterization data –“committee of experts” to develop probabilities for parameters Evaluate the differences in expected value and range of results for (kWh/unit) vs. (kWh/sf) vs. (kWh/ton) results. Use a regression model for high impact parameters to determine acceptability of simplified interactive method Find and test other software tools for expected value analysis Explore past program impacts on long term results as economy of scale takes hold, explore influence factor for projection Develop a step-by-step Expected Value Deemed Savings method for use by others in the region

21. 21 Seeking Approval of Deemed Expected Value as Provisional Savings Method Goal: Accelerate new measure adoption with balance between savings accuracy and information needed Next step in premium ventilation is to develop pilot program approach with evaluation –For ease of contractor delivery, would prefer single rebate approach –Seeking approval to use the expected value method for two-year pilot approach –After pilot and evaluation, can update and continue or seek different approach May also consider use of Deemed Expected Value for other measures that come before RTF

22. 22 Questions? Contact Information: Reid Hart, PE Associate Director, Technical Research Portland Energy Conservation, Inc. 503-961-6142 rhart@peci.org www.peci.org