1 NORTHWEST ENERGY EFFICIENCY ALLIANCE Northwest Ductless Heat Pump Pilot Project Impact & Process Evaluation: Billing Analysis Ecotope, Inc. February 20, 2013

2 Agenda Introduction Research Objectives Recap of Metering Results Methodology Highlights of Findings Conclusions Q & A

3 Introduction

4 DHP Impact & Process Evaluation Overview UES Workbook Billing Analysis ~4,000 Participants Market Progress Evaluation ~300 Participants Field Monitoring 95 Participants Lab Testing 2 units

5 DHP Evaluation Timeline 2009 Install field meters Launch lab tests Collect data for Wave 1 market progress evaluation 2010 Wave 1 market progress report Ongoing field monitoring 2011 Lab analysis report Wave 2 market progress report Decommission field sites 2012 Metering report 2013 Billing analysis report Cost effectiveness analysis UES workbook Final Summary report

6 Research Objectives

7 Billing Analysis Research Objectives  Assess the overall savings and the space heating savings from the DHP installations in the pilot project  Establish savings in electric space heating brought on by this equipment  Determine the impact of occupancy and other “takeback” effects on observed savings  Assess the impact of supplemental fuels on DHP savings  Confirm results of previous metering study and lab testing

8 Recap of Metering Results

9 Metered Analysis Summary  Total savings derived from the heat output of the DHP  Billing savings derived from the pre and post installation bills and metered heating use  Simple regression analysis (CDA) to develop determinants of savings  SEEM calibration based on metered and baseline heating estimates  Temperature adjustments, 66.8° to 69.5°  Calibrated to heating energy use and savings

10 DHP Total Savings Results Cluster Savings from COP (kWh/yr) n MeanSD Willamette Puget Sound Inland Empire Boise/Twin Eastern Idaho Total

11 DHP Bill Savings Results Cluster DHP Savings (kWh/yr) n MeanSD Willamette Puget Sound Inland Empire Boise/Twin Eastern Idaho Average/Total

12 Modeled Savings Estimates, SEEM Cluster Calibrated to Bills Pre 66.8 ° F - Post 69.5°F (kWh/yr) Calibrated to COP Pre 66.8°F - Post 66.8°F (kWh/yr) n MeanSDMeanSD Willamette Puget Sound Inland Empire Boise/Twin Eastern Idaho Average/Total

13 Billing Analysis Methodology

14 Distribution of DHP Pilot Sites (n=3,899)

15 Data Collection  Bills requested for all pilot sites (3,899)  3,748 sites received, 3,629 sites with useable pre and post installation records  PRISM (VBDD) analysis  Estimated heating energy, savings with DHP installation  Include R 2 measure of the quality of the heating estima te  All sites that had adequate bills evaluated  Installation questionnaire  House size and customer demographics  Supplemental heating  Installation cost

16 Highlights of Findings

17 All Useable Cases Cluster Space Heating Savings All CasesScreened Cases kWh/yrn n Willamette Puget Sound Coastal Inland Empire Boise/Twin Eastern Idaho Tri-Cities Western Montana Total

18 Supplemental Fuels  High incidence of supplemental fuels in pilot program  Overall 33.2% of participants report supplemental fuels  RBSA region wide electric heat customers report 35.9% reported supplemental fuels  Clear indications of large impact on savings  Larger incidence of supplemental fuel use in Eastern market clusters  Western Montana 67%  Other rural areas (Western and Eastern) wood heat saturation of ~40%  Supplemental fuels assigned based on installation questionnaire  Similar to the screening process in selecting the metering sample

19 Supplemental Fuels

20 Screened VBDD Results Screened Datasets Space Heat Consumption (kWh) Electric Space Heat Saved (kWh) n Pre InstallPost Install All Sites with Valid Bills Mean SD All R 2 > R 2 > Supplemental Fuel Not Used All R 2 > R 2 > Supplemental Fuel Used All R 2 > R 2 >

21 CDA Regression  Specified as an alternative to screening  n=3621  Use robust regression specs to reduce impact of scatter  Specification: SH saved =c 1 SH pre +c 2 SuppFuel+C c 1 and c 2 : estimated coefficients C: constant term

22 Definitions of CDA Variables  The coefficient on pre-installation space heat (c 1 ) predicts the space heating savings (controlling for other factors).  The coefficient on supplemental fuel use (c 2 ) predicts reduction in savings.  The constant term accounts for the other factors that reduce savings (thermostat settings, erratic occupancy, etc.).  Supplemental fuels coefficient and the constant term account for the savings reduction due to occupant effects: non-energy and supplemental fuel benefits.

23 Regression Results Climate Zone Segment Parameter n c1c1 c2c2 C Western Eastern , W. Montana , All , SH saved =c 1 SH pre +c 2 SuppFuel+C

24 CDA Predicted Space Heating Savings Cluster Predicted Savings n MeanSD Willamette34362,0552,086 Puget Sound33081, Coastal29972, Inland Empire18231, Boise/Twin Eastern Idaho Tri-Cities Western Montana Total

25 Segmented Regression Results

26 CDA Observations  CDA regression recovers the mean savings estimated  The CDA analysis conducted on the metered sample:  c1=.470 for western climates.240 for eastern climates  c 2 is essentially zero (the sample was screened)  Constant term in this sample is zero  20% difference between the billing analysis results and measured DHP heat output

27 Conclusions

28 Conclusions  Once similar screening for supplemental heat is done: results agree with metered analysis results.  Supplemental fuels reduce savings ~1000 kWh  W. Montana requires more severe adjustments  The impact of DHP on space heat without the take back effects:  48% in the western climates  22% in the eastern climates  Program design may need to be modified for more severe climates

29 Questions & Answers