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2013 SDG&E Summer Saver Load Impact Evaluation

2013 SDG&E Summer Saver Load Impact Evaluation. Dr. Stephen George DRMEC Spring 2014 Load Impacts Evaluation Workshop San Francisco, California May 7, 2014. Agenda. Summer Saver program overview Ex post methodology and results Ex ante methodology and results

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2013 SDG&E Summer Saver Load Impact Evaluation

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  1. 2013 SDG&E Summer Saver Load Impact Evaluation Dr. Stephen George DRMEC Spring 2014 Load Impacts Evaluation Workshop San Francisco, California May 7, 2014

  2. Agenda • Summer Saver program overview • Ex post methodology and results • Ex ante methodology and results • Relationship between ex post and ex ante

  3. SDG&E’s Summer Saver program is a CAC direct load control program • The program is available to both residential and small commercial customers • Participants can select from multiple cycling options with corresponding variation in the annual incentive payment • Enrollment is expected to stay relatively constant in the near future • The number of enrolled customers increased by less than 3% from 2012 to 2013.

  4. The ex post evaluation methodology differs between the residential and commercial program segments • Residential ex post impact estimates were developed using two randomly selected groups, with each group alternating as the treatment and control group during load control events • Total sample of 1,460, split roughly evenly into A and B groups – group sizes were limited due to desire to minimize M&E’s impact on DR capability • Impacts estimated as difference between A and B groups for each event, adjusted slightly for differences between the groups during hours leading up to the event period • Based on whole building interval data • Due to small commercial population and the desire to maximize the aggregate load impacts (e.g., not hold back a large control group), the commercial ex post impact estimates were developed using the difference in loads between cycled customers and a statistically matched control group from the non-participant population

  5. The randomly assigned residential A/B groups are well-matched on the 5 highest nonevent system load days in 2013

  6. Loads for the statistically matched control group and the participant population of commercial customers are also similar on the five highest system load days in 2013

  7. Ex post load impacts were based on a simple difference calculation with a small same-day adjustment Unadjusted Adjusted Residential 50% cycling average kW load impact per premise on 9/6/2013

  8. Average 1-5 PM event load impact was 20.8 MW – two events covering later hours of the day delivered fewer MW

  9. The same methodology was used to produce ex ante impacts for both residential and commercial participants • Load impacts between 2 and 4 PM for all events in 2010 through 2013 were regressed against the average temperature from midnight to 5 pm (mean17) • The regression model parameters were used to predict load impacts under ex ante weather conditions for 2 to 4 PM • Impacts for other hours were based on the ratio of impacts from 2 to 4 PM to impacts in those hours for 2013 events Average Ex Post Load Impacts and Ex Ante Predictions from 2 to 4 PM for Residential 50% Cycling Participants

  10. The largest ex ante aggregate impacts for Summer Saver are predicted to occur in September under both 1-in-2 and 1-in-10 year weather conditions

  11. Relationship Between Ex Post and Ex Ante Estimates *This value is less than the ex post value in table on slide 7 because value on slide 7 is only for the four events with common hours from 1 to 5 PM whereas this is based on all 6 ex post 2013 events **Nexant has recommended that SDG&E re-examine their development of ex ante weather values prior to next year’s evaluation

  12. For comments or questions, contact:Stephen GeorgeSenior Vice President, Utility Servicessgeorge@nexant.comorCandice ChurchwellSenior Consultantcchurchwell@nexant.comNexant, Inc.101 Montgomery St., 15th FloorSan Francisco, CA 94104415-777-0707

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