1. Overview of the 2009 LIEE Impact Evaluation Workshop 1: “Overview of Lessons Learned” October 17, 2011

2. Study Background  Statewide Evaluation  Project manager - CPUC  Contract manager – Southern California Edison  Prime research contractor – EcoNorthwest  Subcontractors – Westhill Energy & Consulting, Wirtshafter Associates, Phil Willems, Michaels Engineering, Quantum Market Research, John Stevenson 1

3. Purpose of Impact Evaluation Determine Program Measure Savings Impact Estimates for PY2009 In particular, evaluation sought to: Estimate first year gas and electric energy savings and coincident peak demand reduction Estimate savings in aggregate and by measure and by housing type where feasible Explore additional billing regression models to improve savings estimates for certain measures (evaporative coolers, furnace repair, and replacements). 2

4. Research Method Multiple sources of data collection and analyses  Billing analyses of PY 2008 data to estimate PY 2009 savings  Phone surveys with participants & non participants  Non participant comparison group = PY2009 LIEE participants  Gathered demographics & changes in home, household, & behaviors relevant to energy use  Inquiry focused on select measures (evap coolers, furnace repair/replace, weatherization)  On-sites at participants’ homes  Gathered quality of installations, measure retention, reasons for removal, use of measures, post-participation behavior changes  Inquiry focused on select measures (evap coolers, furnace repair/replace)  Included a customer interview & detailed walk-through of the home 3

5. Research Method (cont) Use of data to produce savings estimates considered multiple regression models Full population Model Phone Survey Model On-site Model Ultimately only billing data used to produce estimates Phone and onsite data used to assist with interpretations of estimates (not included in model) 4

6. Key Impact Results – via billing regression  PY2009 impact estimates are lower than PY2005 eval. impacts  PY2009 electric savings 22% lower than in PY2005, lowest in SCE  Gas savings more variable year to year, but PY2009 gas savings 50% lower than PY2005 eval. impacts  Refrigerators and lighting account for 82% of the total program electric savings  Cooling, DHW, and air sealing/envelope measures make up the majority of the remaining savings. 5

7. Key Findings – via survey & onsite data  Most furnace repair homes have a non working system  Lack of heat savings may be due to low heat loads and use of supplemental heating sources prior to participation  Evaporative coolers often not used correctly resulting in reduced savings  Program education is having limited effect on participants 6

8. Recommendations Full data population model offers best estimate of measure savings. Surveys and on-sites offer useful information, but had limited applicability for model used to determine savings estimates. Continue to target evaporative coolers in hottest climates Improve or add information/education on proper use of evaporative coolers Restrict furnace repairs & replacements to homes with large weather dependent loads. Target more extreme climate zones to increase savings for weather-dependent measures. ECONorthwest7

9. For More Information: Impact Evaluation of the 2009 California Low-Income Energy Efficiency Program. Final Report (June 16, 2011) Prepared for the CPUC, SCE, PG&E, SoCalGas, and SDG&E, by EcoNorthwest. Full report and appendices available on the CALMAC website at: http://www.calmac.org/search.asp http://www.calmac.org/search.asp 8