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Impact Evaluation of SCE’s 2013 Summer Discount Program

Impact Evaluation of SCE’s 2013 Summer Discount Program. DRMEC Meeting, San Francisco. May 7, 2014. Navigant Reference: 170652. SCE SDP Impact Evaluation » Presentation Outline. 1. Introduction. 2. Impact Estimation Approach. 3. 4. Results. Conclusions and Recommendations.

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Impact Evaluation of SCE’s 2013 Summer Discount Program

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  1. Impact Evaluation of SCE’s 2013 Summer Discount Program DRMEC Meeting, San Francisco • May 7, 2014 • Navigant Reference: 170652

  2. SCE SDP Impact Evaluation » Presentation Outline 1 Introduction 2 Impact Estimation Approach 3 4 Results Conclusions and Recommendations

  3. SCE SDP Impact Evaluation » Introduction • SDP is an A/C direct load control program with approximately 300,000 residential participants and 10,000 commercial participants • The vast majority of residential participants are subject to 100% cycling and are located in the “LA Basin” Local Capacity Area (LCA) • The distribution is very similar for commercial participants, although commercial participants may also choose to be subject to 30% cycling

  4. SCE SDP Impact Evaluation » Introduction • Commercial customers come from a variety of industries, but A/C tonnage controlled is primarily in schools

  5. SCE SDP Impact Evaluation » Introduction • Residential participants were curtailed 11 times and commercial participants were curtailed four times through the summer of 2013

  6. SCE SDP Impact Evaluation » Presentation Outline 1 Introduction 2 Impact Estimation Approach 3 4 Results Conclusions and Recommendations

  7. SCE SDP Impact Evaluation » Impact Estimation Approach • All impacts were estimated using fixed-effects regressions applied to panel data • Residential Impacts • Estimated using a sample of ~75% of total enrolled participants • Data were divided into six “strata” corresponding to unique combinations of cycling strategy and LCA • Separate regressions were estimated for each stratum • Separate regressions were used for ex-post and ex-ante results • Commercial Impacts • Estimated using a sample of ~95% of total enrolled participants • Separate regressions were estimated for each of 14 “sub-group” of interest For example: • sub-group 1 includes all commercial participants, • sub-group 3 includes all participants from the “Outside LA Basin” LCA, • sub-group 7 includes all participants subject to 100% cycling strategy and • sub-group 10 includes all Retail Store participants. • Separate regressions were used for ex-post and ex-ante results

  8. SCE SDP Impact Evaluation » Impact Estimation Approach • The Residential Ex-post regression models impacts as a function of each unique event hour observed in 2013 • Data set used includes only the hours from noon to midnight on non-holiday weekdays • Nearly identical specification used for commercial customers, except that no snapback (ss,r,t) included • Decision to not explicitly model snapback for commercial customers based on a combination of results when variables are included (either trivial or spuriously large) and simple visual examination of commercial sub-group load profiles on event days

  9. SCE SDP Impact Evaluation » Impact Estimation Approach • The Residential Ex-ante regression models impacts as a function of cooling degree hours • Data set used includes only the hours from noon to midnight on non-holiday weekdays • Snapback is modeled as a function of how many hours it has been since the event occurred, interacted with the cumulative cooling degree hours observed during the event itself • As above, commercial model is nearly identical, but without any snapback variables included

  10. SCE SDP Impact Evaluation » Presentation Outline 1 Introduction 2 Impact Estimation Approach 3 Results 4 Conclusions and Recommendations

  11. SCE SDP Impact Evaluation » Results • Inspection of fitted values and estimated baselines vs. actuals suggests that estimated models are a reasonable representation of reality • For most stratum/event combinations, fitted values track actuals very closely and implied baselines appear reasonable. In some cases fits are remarkably good, as in example below for September 6th residential event • Similar plots for all events, by strata and aggregations of strata (for residential participants) and by sub-group (for commercial participants) can be found in Appendix E of Navigant’s final impact evaluation report

  12. SCE SDP Impact Evaluation » Results • Excluding the final summer event, the average Residential Ex-post DR impact in 2013 was 0.9 kW per participant • Also excluding the final summer event, the average impact of snapback in the first hour immediately following an event was 0.4 kW • Note that the final summer event (Sept 30th) was only a single hour, between 7pm and 8pm and occurred when the average outdoor temperature was only 73 degrees F. No significant impact was estimated for that event. • Average impacts are highest in the most populous participant group: LA Basin customers subject to 100% cycling • Estimated average impacts are considerably higher than in PY2012 principally because curtailment is no longer “staggered” as it was in PY2012. Staggering curtailment resulted in the first curtailment group’s snapback offsetting second group’s DR impact, reducing overall average DR impact Impacts by LCA/Cycling Strategy

  13. SCE SDP Impact Evaluation » Results • For a 1-in-10 weather year, and “typical event day”, the average forecast Residential Ex-ante impact per participant is 1 kW • The average forecast impact of snapback in the first hour immediately following an event is 0.9 kW. • This is considerably higher than the first hour estimated snapback for historical impacts due to the embedded ex-ante assumption that forecast curtailment events are 5 hours long. In PY2013, the average event length was only 2 hours, and the longest event was 4 hours • As expected given ex-post results, average impacts per participant are highest in the most populous participant group • Estimated average ex-ante impacts are very similar to those estimated in PY2012. Overall average estimated impact for a 1-in-10 weather year on a typical event day from the PY2012 evaluation was 0.9 kW per participant Impacts by LCA/Cycling Strategy

  14. SCE SDP Impact Evaluation » Results • The average Commercial Ex-post DR impact overall was 3.8 kW per participant, but varied considerably by sub-group. • No snapback was estimated because no consistent or reasonable parameter estimates were obtained when snapback variables were included and because a visual inspection of the data indicate that, if present, snapback is trivial. • As would be expected, customer sub-groups that on average have more tons of A/C also on average contribute more of an impact.

  15. SCE SDP Impact Evaluation » Results • The average Commercial Ex-ante DR impact overall for a 1-in-10 weather year on a “typical event day” was 4.6 kW per participant. • Note that all PY2013 observed events were only a single hour in length, whereas the ex ante forecast events are all five hours in length. Although no snapback was observable in the data set available to Navigant, it is reasonable to suppose that for longer (i.e., five hour) events some snapback will be present.

  16. SCE SDP Impact Evaluation » Results • In PY2013, the SDP program delivered an average of 171 MW of DR per event. • Average impact excludes the final September 30th event.

  17. SCE SDP Impact Evaluation » Results • The forecast ex ante impact of the SDP program, given 2015 forecast enrollment is 350 MW for a typical event day, in a 1-in-10 weather year

  18. SCE SDP Impact Evaluation » Presentation Outline 1 Introduction 2 Impact Estimation Approach 3 Results 4 Conclusions and Recommendations

  19. SCE SDP Impact Evaluation » Conclusions and Recommendations • Residential SDP capacity is reliable and consistent. Commercial SDP capacity is less certain. • Residential ex ante estimates have been very consistent year-over-year indicating that the capacity offered by these customers is consistent and predictable • Residential snapback effects in the hour immediately following each event are consistent with previous years • Navigant recommends that customers be dispatched in sub-groupings or on a regional basis, rather than being dispatched all together for the duration of the SDP events • Commercial events in PY2013 were only a single hour long, however ex ante forecast impacts cover a five-hour period • Navigant recommends that SCE call commercial participants for longer periods in each event in PY2014.

  20. Greg Wikler, Project Manager Director San Francisco, CA 415.399.2109 greg.wikler@navigant.com Peter Steele-Mosey, Lead Analyst Managing Consultant Toronto, ON 416.956.5050 peter.steele-mosey@navigant.com

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