Commission Staff Report

Transcription

1 STATE OF CALIFORNIA Edmund G. Brown Jr., Governor PUBLIC UTILITIES COMMISSION 505 VAN NESS AVENUE SAN FRANCISCO, CA Commission Staff Report Lessons Learned From Summer 2012 Southern California Investor Owned Utilities Demand Response Programs May 1, 2013 Performance of 2012 Demand Response programs of San Diego Gas and Electric Company and Southern California Edison Company: report on lessons learned, staff analysis, and recommendations for program revisions in compliance with Ordering Paragraph 31 of Decision

2 ACKNOWLEDGEMENT The following Commission staff contributed to this report: Bruce Kaneshiro Scarlett Liang Uejio Tim Drew Rajan Mutialu Dorris Chow Paula Gruendling Taaru Chawla Jennifer Caron Alan Meck

3 TABLE OF CONTENTS EXECUTIVE SUMMARY... 1 Chapter 1: Introduction... 5 I Summer Reliability and Demand Response Programs... 5 II. Energy Division November 16, 2012 Letter and the Staff Report... 6 Chapter 2: Demand Response Program Load Impact... 8 I. Summary of Staff Analysis and Recommendations... 8 II. Different DR Load Impact Estimates... 9 III. Comparison of DR Daily Forecast and Ex Post Results... 9 IV. Comparison of the 2012 Ex Post to the 2012 Resource Adequacy (RA) Chapter 3: Demand Response Program Operations I. Summary of Staff Analysis and Recommendations II DR Program Trigger Criteria and Event Triggers III. DR Events Vs. Peaker Plant Service Hours IV. Peaker Plant Comparison V. Conclusions Chapter 4: Residential Demand Response Programs I. Summary of Staff Analysis and Recommendations II. Residential Peak Time Rebate (PTR) III. Residential Air Conditioning (AC) Cycling Chapter 5: Non Residential Demand Response Programs I. Summary of Staff Analysis and Recommendations II. Background and Summary of Utility Data III. Commercial Air Conditioning (AC) Cycling IV. SCE s Auto DR V. SDG&E s Demand Bidding Program (DBP) Chapter 6: Flex Alert Effectiveness I. Summary of Staff Analysis and Recommendations II. Background III. Utility Experience with Flex Alert IV. Customer Experience V. The Future of Flex Alert VI. DR Program Ex Post Load Impact Results on the Flex Alert Days Chapter 7: Energy Price Spikes i

4 I. Summary of Staff Analysis and Recommendations II. Definition of Price Spikes III. DR Programs and Price Spikes IV. Conclusion Chapter 8: Coordination with the CAISO I. Staff Recommendations II. DR Reporting Requirements in Summer III. DR Reporting Requirements for Appendix A: Highlight of 2012 Summer Weather & Load Conditions Appendix B: Energy Division November 16, 2012 Letter Appendix C: Descriptions of DR Load Impact Estimates Appendix D: SCE 2012 Monthly Average DR Program Load Impact (MW) Appendix E: SCE 2012 DR Program Load Impact by Event (MW) Appendix F: SDG&E 2012 Monthly Average DR Program Load Impact (MW) Appendix G: SDG&E 2012 DR Program Load Impact by Event (MW) Appendix H: SCE 2012 DR Program Overview Appendix I: SDG&E DR Program Overview Appendix J: SCE Historical DR Event Hours Appendix K: SCE Historical Number of DR Events Appendix L: Summary of SCE s Reasons for the 2012 DR Triggers Appendix M: SDG&E Historical DR Event Hours Appendix N: SDG&E Historical Number of DR Events Appendix O: Utilities Peaker Plant Total Permissible vs. Actual Service Hours Appendix P: Ex Post Demand Response Load Impact on Flex Alert Days Appendix Q: CAISO Energy Price Spikes Appendix R: Utilities Demand Response Reporting Requirements Appendix S: Additional Information ii

5 EXECUTIVE SUMMARY This report is prepared by Energy Division in compliance with Ordering Paragraph 31 of D The purpose of this report is to provide the lessons learned from the 2012 Demand Response (DR) programs operated by San Diego Gas and Electric Company (SDG&E) and Southern California Edison Company (SCE) (Utilities), and to recommend program or operational revisions, including continuing, adding, or eliminating DR programs. Below are highlighted conclusions and recommendations in the report. To see all recommendations, please go to each chapter in the report. In summary, Energy Division makes the following overarching conclusions about the Utilities DR programs: Forecast vs. Ex Post: While a few DR programs met or even exceeded their daily forecast when triggered, on average the ex post results for all program events diverge from the daily forecast by a considerable degree. The majority of programs either provided a mixed performance (the program both over and underperformed relative to its forecast) or were poor performers (consistently coming up short relative to its forecast). Of particular note are the Utilities Peak Time Rebate program 1 and SCE s Summer Discount Plan. 2 (Chapter 2) The divergence between the ex post results and the daily forecasts can be traced to a variety of causes, such as inadequate forecasting methods employed by the Utilities, program design flaws, non performance by program participants and/or program operations. A complete explanation of the reasons for divergence across all programs however, was not possible within the scope and timing of this report. (Chapter 2) 2012 RA vs. Ex Post: Comparing the ex post results to the 2012 Resource Adequacy (RA) forecast is not a good indicator as to how well a DR program performs. RA forecasts are intended for resource planning needs. Ex post load impacts reflect demand reductions obtained in response to operational needs at the time the program is triggered. Resource planning and operational planning have different conditions and serve different purposes. (Chapter 2) DR vs. Peaker Plants: The Utilities used their DR programs fewer times and hours than the programs limits (each program is limited to a certain number of hours or events). In contrast, the Utilities dispatched their peaker power plants far more frequently in 2012 in comparison to historical averages. (Chapter 3) Energy Price Spikes: DR programs are not currently designed to effectively mitigate price spikes in the CAISO s energy market. On many days a DR event was called and 1 SCE s marketing name for Peak Time Rebate is Save Power Day, SDG&E calls it Reduce Your Use. 2 Air conditioning (AC) cycling 1

6 no price spikes occurred, and conversely there were days where price spikes occurred and DR events were not called. The timing and scope of this report did not permit a quantification of the cost of unmitigated price spikes to ratepayers, but in theory, avoidance of these spikes would benefit ratepayers. (Chapter 7) Energy Division also makes the following program specific conclusions about the Utilities DR programs: SCE s AC Cycling Program Forecasting: SCE s 2012 forecasting methodology for its air conditioning (AC) Cycling program (the DR program that SCE triggered the most in 2012) cannot be relied upon to effectively predict actual program load reductions. (Chapter 2) SCE s AC Cycling Dispatch Strategy: SCE s sub group dispatch strategy for its AC Cycling Program (also called Summer Discount Plan) created adverse rebound effects, thereby reducing the effectiveness of the program during critical hot weather days, e.g. 1 in 10 weather. (Chapter 2) SDG&E s Demand Bidding Program: SDG&E Demand Bidding Program produced on average 5 MW of load reduction when triggered, although the US Navy did not participate. The US Navy claimed certain program terms and conditions precluded it from participating in the 2012 program. The Commission s decision to modify the program to a 30 minute trigger may further limit the US Navy s ability to participate. (Chapter 5) Peak Time Rebate Awareness: SCE and SDG&E customers who received utility notification of Peak Time Rebate (PTR) events had higher awareness of the program when compared to customers who were not notified by the utility. More importantly, customers who opted into receiving PTR alerts significantly reduced load. All other customers in the program provided minimal load reduction. (Chapter 4) Peak Time Rebate Free Ridership: The Utilities PTR program has a potentially large free ridership problem, where customers receive incentives without significantly reducing load. SCE paid $22 million (85% of total PTR incentives in 2012) in PTR bill credits to customers whose load impact was not considered for forecast or ex post purposes. 94% of SDG&E s 2012 PTR incentives ($10 million) were paid to customers who did not provide significant load reduction. The inaccuracy of settlement methodology (in comparison to the ex post results) is the main reason for the free ridership problem. The default nature of the program (everyone is automatically eligible for the incentives) aggravates the problem. (Chapter 4). Flex Alert: There is a lack of data to evaluate the effectiveness and value of the Flex Alert campaign. Attribution of savings from Flex Alert is complicated by the fact that load reduction from the Utilities DR programs on the two days Flex Alert was 2

7 triggered in 2012 contributed to reduced system peak load. A load impact evaluation of Flex Alert is planned for (Chapter 6) DR Reports: The Utilities DR daily and weekly reports were useful to the CAISO and the Commission for purposes of up to date monitoring of DR resources throughout the summer. (Chapter 8) In light of above findings, Energy Division recommends the following: DR Evaluation: The Commission should require further evaluation of Utility DR program operations in comparison to Utility operation of peaker plants for the purpose of ensuring Utility compliance with the Loading Order. (Chapter 3) Forecast Methods Generally: The Utilities daily forecasting methods for all DR programs (especially AC cycling and other poor performers) should undergo meaningful and immediate improvements so that the day ahead forecasting becomes an effective and reliable tool for grid operators and scheduling coordinators. (Chapter 2) Forecasting for SCE s AC Cycling Program: SCE should improve forecasting methods for its residential AC Cycling Program with input from agencies and stakeholders. SCE should also pilot more than one forecasting method for the program in (Chapter 2) Forecasting for SDG&E Programs: SDG&E s forecasting methods for its AC Cycling Program (Summer Saver) could be improved doing the following: running a test event and including a correlation variable that accounts for customer fatigue. SDG&E s Capacity Bidding Program forecasting could be improved by including a weather variable. (Chapter 2) SCE s Outreach for Commercial AC Cycling: Through its outreach and marketing efforts, SCE should clearly communicate the new features of its commercial AC cycling program to avoid customer dissatisfaction and dropout. (Chapter 5) Auto DR: Future studies are necessary to explore the load impacts of Auto DR. (Chapter 5) SDG&E s Demand Bidding Program: SDG&E should work collaboratively with the US Navy to design a program to meet the unique needs of the Navy. Key attributes to consider are a day ahead trigger, aggregation of 8 billable meters and a minimum bid requirement of 3 megawatts (MW). (Chapter 5) Peak Time Rebate Design Changes: The Utilities residential PTR program should be changed from a default program to an opt in program, so that bill credits are paid only to customers who opt in. (Chapter 4) SCE s AC Cycling Dispatch Strategy: SCE should reconsider its current strategy of calling groups of residential AC cycling customers in sequential one hour cycling events. Alternatively, if SCE retains its current strategy, it should modify the 3

8 program s incentive structure so that customers who are willing to have their AC units cycled for an entire event (as opposed to just one hour) are compensated more than those who can tolerate only one hour of cycling. (Chapter 4) DR Reports: The Utilities (and Pacific Gas & Electric) should submit daily and weekly DR reports to the CAISO and the Commission for the summers of 2013 and They should follow the same format and data requirements in the 2012 reports, unless otherwise directed by the Commission or Commission staff. (Chapter 8) 4

9 Chapter 1: Introduction I Summer Reliability and Demand Response Programs San Onofre Nuclear Generating Station (SONGS) Units 2 and 3 were taken out of service in January By March 2012, the Commission determined that the outage of SONGS two units could extend through summer Working closely with the Governor s Office, the California Independent System Operator (CAISO), and the California Energy Commission (CEC), the Commission took immediate mitigation actions to ensure that lights stay on in California with the loss of 2,200 MW of capacity provided by SONGS. 3 When considering adding new generation resources, 4 an important action was to further incorporate the Utilities Demand Response (DR) programs into the CAISO s contingency planning and daily grid operations during the summer. This included mapping the Utilities DR programs to grid contingency plans and developing new daily and weekly DR reporting requirements. In addition, the Commission also moved swiftly to approve three new DR programs for summer 2012: SDG&E s Peak Time Rebate (PTR) for commercial customers and Demand Bidding Program (DBP); and SCE s 10 for 10 conservation program for non residential customers. 5 Because of the intensive interagency mitigation effort and relatively cool weather, California grid reliability was not compromised in spite of the SONGS outage. Nevertheless, southern California experienced several heat waves in August and September with the highest temperature reaching 109 F in SDG&E s service area and 100 F for SCE on September The CAISO issued two Flex Alerts: on August 10 and 14. The Utilities triggered all of their DR programs at least once and some on multiple occasions. Throughout the summer, Energy Division (ED) staff monitored the Utilities DR program events on a daily basis and provided weekly briefings to the Governor s Office, the CAISO, and the CEC. Staff observed that, for many event days, the load impact forecasts provided by the Utilities to the CAISO and the Commission in their daily DR reports were inconsistent with the results submitted seven days after each event (referred as the 7 Day report ). In some cases, the Utilities reported much lower load reduction results than they originally forecasted. In addition, load impact forecasts provided by the Utilities throughout the summer were lower than the capacity counted for the 2012 Resource Adequacy (RA) Requirement. This raised a question as to whether the Commission might have overestimated DR load impact for RA purposes or, rather, if the Utilities might have under utilized their DR programs. Sometime in mid summer, the Utilities began to experience price spikes in CAISO s wholesale energy market. Questions were raised on whether the DR programs could be used to mitigate price spikes, and if so, should they be Retired Huntington Beach Units 3 and 4 were brought back on line temporarily. 5 Resolutions E 4502 and E A 1 in 10 (or 10% probability) weather condition in any given years. 5

10 Some of the Utilities DR programs were triggered on as many as 23 events over the five summer months, and many were triggered on two or three consecutive days. Appendix A highlights the DR program load impact on the three hottest days and the three days when SDG&E and SCE experienced highest system peak load. Staff observed that SDG&E s system peak correlate to temperature and biggest DR load reduction happened on the hottest day. On the other hand, SCE s system peak load did not consistently correlate to weather. In contrast, SCE s system load reached its annual peak at 90 F temperature, 10 F cooler than the hottest day in its service territory. Counter intuitively, DR program load impact on a cooler day was actually higher than the amount delivered on the hottest day. This led to questions how the Utilities make decisions to trigger DR programs and whether aspects of the customers experience, such as expectations and fatigue have an effect. In August, CAISO issued two Flex Alerts when it determined a reliability risk due to insufficient supply to meet demand. As expected, the Utilities triggered relatively large amounts of DR programs on both days. CAISO reported that the actual peak load was significantly lower than its hours ahead forecasts and attributed the load drop to Flex Alert events. This parallel dispatch situation raises important questions regarding the effectiveness of the Flex Alert when overlapped with the Utilities DR program events and how customers perceived with these statewide alerts versus local utility DR notifications. Based on the above experience, the Commission concluded that staff should evaluate DR program performance and other lessons learned in order to seek answers to these and other questions. Such lessons could help the Commission to determine the extent of DR program reliability and usefulness and in turn, to the extent to which DR resources can be counted on in CAISO markets and operations. II. Energy Division November 16, 2012 Letter and the Staff Report On November 16, 2012, the Energy Division sent a letter (Energy Division Letter) to the Utilities directing the Utilities to 1) file an application proposing DR program improvements for 2013 and 2014 to mitigate the SONGS outage and 2) provide data and responses to a set of questions on lessons learned from 2012 DR programs. The questions were developed based on the Utilities 2012 demand response experience and fell into six categories: 1. DR Program Performance, which include load impact and program operations, 2. CAISO Market, covering price spikes and market analysis 3. Customer Experience, 4. Coordination with the CAISO and Utility Operations 5. Emergency DR Program Dispatch Order, and 6. Flex Alert Effectiveness The Energy Division Letter is attached in Appendix B of this report. 6

11 On December 21, 2012, the Utilities filed separate applications for the approval of the DR program revisions for 2013 and The Utilities submitted data and responses to the questions attached to the Energy Division Letter and subsequent Assigned Administrative Law (ALJ) rulings for developing the record. 8 Decision (D.) approved certain DR program improvements for and directed the Commission staff to develop a report on the lessons learned from the DR programs in This report is based on a snapshot of data and studies available at the time (i.e. ex post load impact data, utility responses to Energy Division data requests, etc.) On going and future (e.g. Flex Alert load impact analysis per D ) evaluations will shed further light on the issues raised in this report. One point of emphasis in this report is the extent to which the current DR programs delivered their forecasted savings when they were triggered by the utilities. It is important to understand that there are a range of factors that can affect whether a program delivers its forecasted savings targets. Some of these factors can be controlled through good program design, operation and forecasting methodologies. Other factors that can impact program performance are exogenous or outside the utilities control such as temperature, participant enrollment fluctuations, and behavioral or technological changes by the participants. While this report contains certain findings and recommendations for DR programs, we caution against sweeping conclusions or generalizations about DR programs based on this report. The point of this report is to find ways to improve existing DR programs so that they are more useful to grid operators, utilities, ratepayers and participants. 7 A (SDG&E) and A (SCE). 8 On January 18, 2013 and February 21,

12 Chapter 2: Demand Response Program Load Impact I. Summary of Staff Analysis and Recommendations SCE Most of the program event ex post results diverge from the daily forecast by a considerable degree. The daily forecast should be more consistent with the ex post results in order for the day ahead forecasting to be valid and useful for grid operators. Staff recommends that the daily forecasting methods for all programs undergo meaningful and substantial improvements, including more thorough and transparent documentation and vetting through relevant agencies and stakeholders. The Summer Discount Plan (Residential AC Cycling) program forecasting methods in particular requires an audience with a broad panel of agencies and stakeholders. Staff also recommends that SCE pilot more than one forecasting method and conduct interim protocolbased load impact evaluations to identify the most reliable forecasting methods throughout the 2013 summer season. SCE should also be required to address Summer Discount Plan program operation issues before the 2013 summer peak season begins, if possible. Specifically, the strategy of calling groups of customers for sequential one hour cycling events, rather than calling all the customers for the duration of the full event (or other potential strategies), needs to be reconsidered before the program is further deployed. As discussed in detail later in this chapter, this strategy resulted in load increases during the latter hours of events, thereby reducing the overall effectiveness of the program. SDG&E Similar to SCE, many of SDG&E s program event ex post results also diverge from the daily forecast by a considerable degree. The Demand Bidding Program daily forecast was accurate and reliable in predicting ex post results, while the Summer Saver and Capacity Bidding Day Ahead and Day Of program daily forecasts did not accurately nor reliably predict ex post results. The Peak Time Rebate Residential daily forecast was not accurate in predicting ex post results, but consistently underestimated ex post results by approximately 80%. The Critical Peak Pricing and Base Interruptible program did not accurately or reliably predict ex post results, but consistently under predicted ex post load impacts. Due to a weak price signal and inelastic customer demand, the PTR commercial program ex post results were not significant. The CPP E was discontinued as of December 31, Staff recommends (1) including only customers that opt in to receive e mail or text alerts in the PTR residential daily forecast model (2) running a test event to measure % load impact per customer in order to improve CPP daily forecast estimates (3) including a correlation variable in the Summer Saver daily forecast model to account for customer fatigue during successive event days (4) including a weather variable in the CBP daily forecast model in order to have parity with the ex post regression model. 8

13 II. Different DR Load Impact Estimates DR programs load impact are forecasted or estimated at different times for different purposes. The following table summarizes the five different DR load impact estimates that are discussed in this chapter. Detail descriptions and methodologies for each DR program measurement are provided in Appendix C. Table 1: DR Load Impact Estimates DR Load Impact Estimates General Description Purpose Ex Ante for RA (e.g., 2012 RA) A year ahead monthly ex ante load impact potential attributed by individual program under a 1 in 2 weather condition. To determine the RA counting against the Load Serving Entity s system and local capacity requirements. Daily Forecast 7 Day Report Ex Post Results Settlement The Utilities daily estimate of hourly load impact from DR programs during an event period. The Utilities preliminary estimate of hourly load reduction results from each triggered DR program The Utilities most accurate measurement of the load impact results from all of the DR programs triggered in a year. The ex post results are calculated using comprehensive regression models. A measurement of customers load reduction from their specific reference load using a baseline method. To provide the CAISO, CPUC, and CEC the hourly MW provided by DR programs on each event day. To report to the CAISO the load reduction data from the triggered DR programs seven days after each DR event. To report to the CPUC the actual results of the DR events To calculate customers incentive payments for billing purpose. In this proceeding, the Utilities provided the above DR load impact estimates for their DR programs, which are shown in Appendices D to G. III. Comparison of DR Daily Forecast and Ex Post Results A. Overall Program Performance The following section draws on data provided by the Utilities on March 4, in response to the Feb 21, 2013 ALJ ruling, which compares event day forecasts (daily forecast or day ahead forecast) to the event day ex post load reduction estimates. Detailed data and methodological descriptions relevant to this chapter are provided in Appendices C and G. Subsequent to its March 4 filing, SCE updated its ex post results for some of the DR program events in its April 2 Load Impact Report but did not update its March 4 filing accordingly. However, in most cases, the April 2, 2013 updated ex post results are even lower than the March 4 preliminary data, e.g., the AC cycling. Therefore, if the updated data was used, it would further support staff s findings. 9 SCE 03 and SGE 03. 9

14 On average, the ex post results for all program events diverge from the daily forecast by a considerable degree. While some program events were forecasted more accurately and consistently than others, Energy Division staff s overall conclusion is that the daily forecasting methods for all programs requires meaningful and immediate improvements in order for the day ahead forecasting can become an effective and reliable tool for grid operators. Some of the divergence between the ex post results and the daily forecast estimates can possibly be explained by inadequate program design and program operations. This section focuses on the observed differences between the ex post and the daily forecast with an eye towards identifying improvements for day ahead forecasting, and thus does not cover all potential program improvements. Furthermore, many program design and operational improvements that could lead to better ex post results may not be evident by simply inspecting the daily forecast and ex post data. The ex post analysis methods are guided by Commission adopted load impact protocols 10 and the study results are carefully documented in reports prepared by independent consultants managed by SCE staff. However, there are currently no comparable standards and processes guiding the methods for daily forecasting. Indeed, during the course of preparing this report, Energy Division staff became aware that the day ahead forecasting methods are far from transparent, and in some cases lack the robust analysis that is expected of the Utilities. These problems may be somewhat understandable, however, since the daily reports were only formally instituted in While this report is highly critical of the implementation of the day ahead forecasting, it is important to recognize that the 2012 DR events as a whole did indeed reduce participants loads, and some of the program load reductions were consistent with or better than the day ahead forecast. To that end, staff has categorized the demand response programs into three categories (good, mixed, and poor performance) based on how well the program events performed relative to the day ahead forecasts. SCE Programs that performed well yielded load impacts that were consistent with or better than the day ahead forecast. The Base Interruptible Program (BIP) and the Day of Capacity Bidding Program events produced load reductions that were on par with the forecasts. It is worth noting that BIP, the single largest program, was triggered on only one occasion in 2012 however, and this was test event. Program events with mixed performance were not consistent with the day ahead forecast, but sometimes exceeded the forecast. Staff includes the Day ahead Capacity Bidding, Demand Bidding, and the Residential Summer Discount Plan program events in this category because these program events did indeed occasionally exceed the day ahead forecasts by a significant margin. These programs are discussed in greater detail elsewhere in this section and report. While considered to be mid performing programs, they do have many important issues that deserve attention. 10 Decision

15 Program events that were consistently below the forecast are considered to be poor performing programs. All of the Critical Peak Pricing, Peak Time Rebate, Demand Response Contracts, Commercial Summer Discount Plan, and Agricultural Pumping Interruptible program events triggered during 2012 produced load reductions that were lower than forecasted. Table 2: SCE s DR Overall Performance Programs No. of DR Events Daily Forecast Ex Post Difference % Good Performance: Capacity Bidding Program Day of >2 >17% Base Interruptible Program % Mixed Performance: Capacity Bidding Program Day Ahead to % to 86% Demand Bidding Program to 16 40% to 21% Summer Discount Plan (AC Cycling) Res to % to 58% Poor Performance: Critical Peak Pricing < 5 < 11% Peak Time Rebate < 11 < 11% Demand Response Contracts < 70 < 34% Summer Discount Plan (AC Cycling) Com % Agricultural Pumping Interruptible < 19 < 52% SDG&E (Averaged MW over All Events) (Range from Low to High) Utilizing the same criteria for evaluating SCE DR programs, The Base Interruptible Program and the Critical Peak Pricing Program were categorized as good performers, the Capacity Bidding Day Ahead, Capacity Bidding Day Of, Demand Bidding, and Summer Saver (AC Cycling) were categorized as mixed performers, and the Critical Peak Pricing Emergency and residential Peak Time Rebate programs were categorized as poor performers. As stated above, DR program design and operation characteristics also need to be taken into account for a complete evaluation of DR program performance. 11

16 Table 3: SDG&E s DR Overall Performance Programs B. Program Performance During Critical Event Days The critical event days of August 10th, 13th, 14th, and September 14th were selected as a focus because they occurred on Flex Alert days, the service area system peak day, or the hottest days of the year. These are all conditions when demand response resources are most critical. August 10, 2012 SCE Two SCE programs were called on August 10th, a Flex Alert day. The programs triggered during that event were the Demand Bidding Program and the Save Power Day (also known as the Peak Time Rebate program). The load reductions achieved during the Demand Bidding Program event surpassed the forecast by 12%, while the Save Power Day event was below the forecast by 11%. Table 4: SCE s August 10, 2012 Demand Response Events Program Name Number of Events Daily Forecast MW Daily Forecast Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post A B C=B A D=C/A Demand Bidding Program % Save Power Day % Total Ex Post Difference % (Averaged MW over All (Low To High) Events) Good Performance: Base Interruptible Program % Critical Peak Pricing > 2.4 >3.1% Mixed Performance: Capacity Bidding Program Day 7 Ahead to % to 12.2% Capacity Bidding Program Day Of to % to 6.0% Demand Bidding Program to % to 8.0% Summer Saver (AC Cycling) to to 38.7% Poor Performance: Peak Time Rebate Residential < 24 < 73.6% Critical Peak Pricing Emergency < 0.7 < 53.3% 11 SCE did not provide a daily forecast for this event, so the comparison for this event is done with the 7 day report rather than the daily forecast. 12

17 SDG&E Three DR programs were called on August 10 th. The Capacity Bidding Day Ahead program load reduction exceeded the forecast by 1%. Conversely, the Summer Saver and residential Peak Time Rebate forecasts under predicted the forecast by 32% and 75%. Table 5: SDG&E August 10, 2012 Demand Response Events Program Name Daily Forecast MW Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post A B C = B A D=C/A Capacity Bidding Day Ahead % Summer Saver (AC Cycling) % Residential Peak Time Rebate % Total August 13, 2012 SCE August 13, 2012 was the system peak day for the SCE service area, with a peak load of 22,428 MW. As shown in Table 6 below, the Critical Peak Pricing program, a dynamic pricing program for commercial and industrial customers over 200 kw, and the Day Of Capacity Bidding Program were triggered during this day. Again, the Capacity Bidding Programs exceeded the forecast by a few MW. The Critical Peak Pricing program event had satisfactory performance, falling short of the forecast by 15%. Table 6: SCE s August 13, 2012 Demand Response Events Program Name Daily Forecast MW Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post A B C=B A D=C/A Critical Peak Pricing % Capacity Bidding Program (Day Of) % Total SDG&E All three DR programs that were triggered on August 13th, Capacity Bidding Day Of, Summer Saver (AC Cycling), and Critical Peak Pricing, had ex post load impacts that were respectively below daily forecast predictions by 27%, 45%, and 48%. 13

18 Table 7: SDG&E s August 13, 2012 Demand Response Events Program Name Daily Forecast MW Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post A B C= B/A D= C/A Capacity Bidding Day Of % Summer Saver (AC Cycling) % Critical Peak Pricing Emergency % Total August 14, 2012 SCE August 14, 2012 was another Flex Alert day, during which seven events were called, using a variety of DR programs. As shown in Table 8 below, all the events combined were forecasted to reduce loads by 570 MW. However, the ex post load impact evaluations found that the actual load reductions were short of the total forecast by 155 MW. 60% of the 155 MW shortfall is attributed to the Demand Response Contract program. The Agriculture Pumping Interruptible program event was short of the event forecast by 52%. Only the Capacity Bidding Program exceeded the forecasted load reduction, but this only made up 4% of the Demand Response Contract program forecast, and thus was insufficient to cover the overall event day shortfall. It is worth noting that the Demand Response Contract and Capacity Bidding Programs share something in common in that they are both commercial aggregator programs. The reason for the difference in performance between these programs requires further study. It should be noted that SCE s Demand Response Contracts expired on December 31, 2012 and have since been replaced by new contracts that that expire at the end of Table 8: SCE s August 14, 2012 Demand Response Events Program Name Daily Forecast MW Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post A B C=B A D=C/A Demand Response Contracts % Demand Bidding Program % Agriculture Pumping Interruptible % Summer Discount Plan (Res) Group % Capacity Bidding Program (Day Of) % Summer Discount Plan (Res) Reliability % Summer Discount Plan (Com) % Total D

19 SDG&E Four DR programs, Demand Bidding, Critical Peak Pricing, Capacity Bidding Day Ahead, and residential Peak Time Rebate, were called on August 14 th. While the Demand Bidding and Capacity Bidding Program ex post load impacts closely matched the daily forecast, the Critical Peak Pricing and residential Peak Time Rebate did not. Since the Critical Peak Pricing and residential Peak Time Rebate programs are large scale residential programs it is possible that the difference between the forecast and ex post load impacts reflect widely varying customer behavior during DR events. Table 9: SDG&E s August 14, 2012 Demand Response Events Program Name Daily Forecast MW Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post A B C=B A D=C/A Demand Bidding Program % Critical Peak Pricing % Capacity Bidding Program (Day Ahead) % Residential Peak Time Rebate % Total September 14, 2012 SCE September 14, 2012 was the hottest day of the year in both the SCE and SDG&E service areas (see Table 10 below). Understandably, SCE triggered their Summer Discount Plan (residential AC Cycling Programs) during this day. The Capacity Bidding Program was also triggered, with performance comparable to the other Capacity Bidding Program events on critical days discussed above. The September 14 residential Summer Discount Plan events consisted of three separate customer groups sequentially triggered for one hour events. All three one hour events fell considerably short of the forecasted load reductions. Table 10: SCE s September 14, 2012 Demand Response Events Program Name Daily Forecast MW Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post A B C=B A D=C/A Summer Discount Plan (Residential) Groups 5 and % Summer Discount Plan (Residential) Groups 1 and % Capacity Bidding Program (Day Of) % Summer Discount Plan (Residential) Groups 3 and % Total

20 SDG&E On September 14, 2012, the peak temperature in SDG&E s service territory was 109 degrees. The Demand Bidding, Summer Saver, and Base Interruptible Programs ex post load impacts were above the daily forecast in a range between 8% and 167%. Since the absolute value of the Base Interruptible Program load impact is ~ 1 MW, a small increase or decrease in the daily forecast prediction can result in high variability in the percent difference between these two figures. Conversely, the Capacity Bidding Day Of and Day Ahead Programs and the Critical Peak Pricing Emergency Program daily forecasts were below the daily forecast in a range between 12% and 44%. Table 11: SDG&E s September 14, 2012 Demand Response Events Program Name Daily Forecast MW Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post C. Detailed Program Analysis A B C=B A D=C/A Capacity Bidding Program (Day Of) % Capacity Bidding Program (Day Ahead) % Demand Bidding Program % Summer Saver (AC Cycling) % Base Interruptible Program % Critical Peak Pricing Emergency % Total The following section discusses programs and events that produced load reductions forecasted by the daily reports, as well as programs that failed to produce the forecasted load reductions. For this purpose, all programs and events that came within 10% (+/ ) of the forecasted load reductions are considered to be consistent with the daily forecast and all programs and events that were more or less than 50% of the forecasted load reductions are considered to have failed to produce the forecasted load reductions. SCE There were a total of 104 separate events in the SCE service area in Only ten of these events produced the load reductions consistent with those forecasted in the daily reports. As shown in Table 12 below, all of these events produced fairly sizable load reductions, ranging from 59 to 130 MW, with the exception of one Capacity Bidding Program event, which produced a very small load reduction. 16

21 Table 12: SCE s DR Events with Ex Post Results within 10% of the Daily Forecast Program Name Event Date Daily Forecast MW Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post A B C=B A D=C/A Summer Discount Plan (Residential) 08/14/ % Summer Discount Plan (Residential) 08/29/ % Summer Discount Plan (Residential) 08/01/ % Summer Discount Plan (Residential) 08/15/ % Demand Bidding Program 10/17/ % Demand Bidding Program 10/01/ % Summer Discount Plan (Residential) 08/09/ % Summer Discount Plan (Residential) 08/28/ % Capacity Bidding Program (Day Ahead) 07/31/ % Demand Bidding Program 08/08/ % Of the 104 events in 2012, thirty (or about 29%) of the events were more than 50% off of the day ahead forecast. Five of these events produced load reductions that were greater than the forecast, while the remaining 25 were lower than the forecast. The three events with the highest percentage difference below the forecast were very small Day Ahead Capacity Bidding Program events, and thus are not considered the most critical problem. Twenty one of the remaining events were Summer Discount Plan (AC Cycling) events, and these varied markedly off the forecast. 17

22 Table 13: SCE s DR Events with Ex Post Results greater than + 50% of the Daily Forecast Program Name Event Date Daily Forecast MW Ex Post MW Difference Forecast & Ex Post MW % Difference Forecast & Ex Post A B C=B A D=C/A Capacity Bidding Program (Day Ahead) 10/01/ % Capacity Bidding Program (Day Ahead) 10/02/ % Capacity Bidding Program (Day Ahead) 10/05/ % Save Power Days / Peak Time Rebates 09/07/ % Summer Discount Plan (Residential) 06/20/ % Save Power Days / Peak Time Rebates 09/10/ % Summer Discount Plan (Residential) 09/14/ % Summer Discount Plan (Residential) 07/10/ % Summer Discount Plan (Residential) 09/14/ % Summer Discount Plan (Residential) 06/29/ % Summer Discount Plan (Residential) 09/20/ % Summer Discount Plan (Residential) 06/29/ % Summer Discount Plan (Residential) 07/10/ % Summer Discount Plan (Residential) 10/02/ % Summer Discount Plan (Residential) 07/10/ % Summer Discount Plan (Residential) 09/20/ % Summer Discount Plan (Residential) 09/20/ % Summer Discount Plan (Residential) 09/14/ % Summer Discount Plan (Residential) 08/22/ % Agriculture Pumping Interruptible 09/26/ % Summer Discount Plan (Residential) 09/21/ % Summer Discount Plan (Residential) 09/28/ % Agriculture Pumping Interruptible 08/14/ % Summer Discount Plan (Residential) 10/17/ % Summer Discount Plan (Residential) 10/17/ % Summer Discount Plan (Residential) 08/17/ % Capacity Bidding Program (Day Ahead) 10/29/ % Summer Discount Plan (Residential) 08/17/ % Capacity Bidding Program (Day Ahead) 10/18/ % Summer Discount Plan (Residential) 09/10/ % Summer Discount Plan The Summer Discount Plan event variability ranges from 121% below the forecast (with a load increase rather than a load reduction) to 260% above the forecast. Overall, the AC Cycling program represents the most variance 13 of all the SCE DR programs. When all of the variances for individual events are aggregated, the AC Cycling program represents 49% of the total variance. The Pearson Product Moment Correlation between the daily forecast and the ex post load impacts is 0.21, representing a very weak positive correlation. 13 Variance in this context specifically refers to the absolute difference between the daily forecast and the event day ex post load reductions. 18

23 The Pearson correlation between the average event temperature 14 and the event level variance (difference between the daily forecast and the event day ex post load reductions) is 0.37, representing a moderately weak correlation. In everyday language this means that SCE s 2012 Summer Discount Plan forecast method cannot be relied upon to effectively predict the actual program load reductions. In addition, there appears to be little relationship between the event day temperature and the difference between the daily forecast and the event day expost load reductions, potentially ruling out temperature as an explanatory factor for the difference. The Summer Discount Plan was (by far) the most often triggered program in SCE s 2012 DR portfolio. There were 23 separate events, including two early test events 15. Most of the 23 events were split into 3 customer segments such that each group of customers was triggered for only a portion (i.e. one hour) of each event (typically lasting three hours). Three events on 9/14, 9/20, and 9/28 deployed 6 customer segmentations. SCE operated the program in this manner to avoid cycling their customers air conditioners for more than one hour at a time 16. The purpose of this strategy is so customers will be minimally impacted by the loss of one hour of AC services, compared to multiple continuous hours, and in theory the utility would still be able to reduce load when needed. As shown in Table 14 below, the implementation of this strategy, however, resulted in a rebound effect from the groups curtailed in event hours 1 & 2 that added load in hours 2 & 3 as AC units ran at above normal capacity to return the participants buildings to the original temperature set points 17. The net effect was to dampen the average hourly load impact for the entire event period, as illustrated in Table 14. It is possible that the daily forecasts were prepared assuming that all customers would be curtailed at the same time over the entire duration of the event. In such a case, the average hourly load reductions would likely have been larger because all customers would be simultaneously curtailed and the rebound effect would be delayed until after the event was over. This issue is further illustrated in Chapter 2, Section IV Comparison of the 2012 Ex Post to the 2012 Resource Adequacy (RA). Table 14: SCE s Hourly Load Impact from a Sept 14 Summer Discount Plan event Event Hour Ending: Event Hours w/ Rebound Post Event Rebound Event Hour Average Hour Total SCE Final 2012 Ex Post Ex Ante Load Impacts for SCEs SDP filed in R on April 2, The last two events in late October were not included in the ex post analysis. 16 SCE 01 Testimony at SCE Final 2012 Ex Post Ex Ante Load Impacts for SCEs SDP filed in R on April 2,

24 Another potential explanation for the suboptimal performance could be customers exercising the override option in their enrollment contracts with SCE. However, SCE s A testimony 18 indicates that the proportion of customers with an override option is fairly small (consisting of about 1% of the customers enrolled in SDP) and that these customers rarely exercise the override option. Finally, it is possible that transitioning Summer Discount Plan from an emergency program to a price responsive program could have introduced some additional uncertainties that aren t adequately captured by the current forecasting methods. Regardless of the explanation for the unexpectedly low load reductions during these events, it is critical that SCE improve the day ahead forecast for the SDP program as a whole. Energy Division staff reviewed SCE s method for forecasting the Summer Discount Plan program. 19 The methodology, provided in Appendix C, is described in a 1986 internal SCE memorandum and consists of a simple algorithm which estimates the load reduction per ton of AC based on the forecasted temperature. The equation coefficients were determined by a 1985 load reduction study that SCE staff could not locate when requested to do so by Energy Division staff. Without the 1985 load reduction study Energy Division staff could not fully evaluate the forecasting methodology. SCE did provide a revised algorithm which modifies the equation structure. But the underlying methods for estimating those coefficients as yet remain unexplained. This evidence suggests that there is a critical flaw in either the way the Summer Discount Plan events are forecasted or in the operation of the program, or both. The lack of a reliable day ahead forecasting method is a major weakness that undermines the ability to fully consider AC Cycling in the CAISO grid operations. Even if the utilities DR resources are eventually to be bid into the CAISO market, which currently are not, ED recommends that SCE immediately document the forecasting methods to be used for the 2013 season and thoroughly vet the methods with CPUC and CAISO staff and relevant stakeholders to ensure the proposed forecasting methods are reasonable and reliable. Throughout the 2013 summer season (and longer if necessary), SCE should consider piloting more than one forecasting method which should be tested using small ex post load impact evaluations to identify the most reliable forecasting methods. Base Interruptible Program The Base Interruptible Program was triggered only once during the entire 2012 season and this was a test event. This single event produced 573 MW of load reductions on September 26. The load reductions for this event were 59 MW more than the day ahead forecast. It is worth noting that the single Base Interruptible event was more than three times the load reduction of any other SCE program event during 2012, and it was not triggered on one of the critical event days discussed earlier in this section. The Commission should explore a policy requiring more frequent deployments of this program since it appears to have significant, yet underutilized, potential. 18 SCE 01 Testimony at 11, Lines See Appendix S. 20

25 Capacity Bidding Program The Capacity Bidding Program Day Ahead events produced an average load reduction of 0.03 MW across all events. With the exception of three events in October (that were associated with negative load reductions in the ex post analysis) most events produced relatively small load reductions forecasted by the daily report. None of the Capacity Bidding Program day ahead events occurred in August and September when the load reductions are typically most needed. By comparison, all of SCE s Capacity Bidding Program Day Of events exceeded the forecasted load reductions, by an average of 32%. The average load reduction for the Capacity Bidding Program Day Of events was 15.9 MW, over 500 times the load reductions produced by Day Ahead events. This evidence suggests that, unlike the Day Of program, the Day Ahead Capacity Bidding Program may not be serving a useful function in SCE s DR portfolio. Demand Bidding Program The Demand Bidding contracts were called on eight occasions during the summer of Of these eight events, five occurred in August. The first two August events on August 8 and August 10 resulted in load reductions that exceeded the daily forecast by an average of 10%. The third and fourth events on August 14 and August 16 were 34% short of the forecasted load reductions and the fifth event on August 29 was 40% below forecast, suggesting that perhaps a decline in customer participation in events could be explored as a potential factor in diminishing returns. Demand Response Contracts (DRC) Nominated Somewhat surprisingly, there were only two events for which Demand Response Contracts were called. The ex post load reductions for these two events were both around 35% below the daily forecast. Energy Division was not able to examine why this program performed so poorly. As noted earlier, SCE s DRCs expired on December 31, 2012, and have since been replaced by new contracts approved by the Commission. Save Power Days / Peak Time Rebates (PTR) Price Responsive Daily forecasts were not provided by SCE for the four PTR events that occurred in August, thus comparisons between the daily forecast and ex post results are possible for only the two events on September 7 and September 10. Both of the September events were forecasted to reduce loads by 109 MW. Ex post results, however, indicate that the PTR events had no impact at all. In fact, the September 7 event was correlated with a fairly significant load increase of MW. Ex post load reductions were estimated for the four August PTR events, for which dayahead estimates were not provided by SCE. As a proxy for the daily forecast the 7 day reports were used. As shown in Table 15 below, estimated load reductions were between 107 and 108, while the ex post load reductions ranged between 0.02 and 96 MW. 21

26 Table 15: SCE s Peak Time Rebate MW Event Day 7 Day Report Ex Post 8/10/ MW MW 8/16/ MW MW 8/29/ MW MW 8/31/ MW 0.02 MW Given the considerable variability in ex post results for the PTR program events, the dayahead forecasting and event reporting will need significant revision to account for these discrepancies. If the PTR program is going to continue, staff recommends that SCE prepare a proposal for a viable forecast and submit that for staff to review. SDG&E There were a total of 46 DR program events that were triggered on 14 event days in SDG&E s service area from June 2012 October Daily forecasts for twelve DR program events were within + 10% of ex post load impacts. As depicted in Table 16, moderate load reductions ranging from 5 to 17 MW were produced when these events were triggered. Three programs delivered accurate results with a moderate degree of consistency: Demand Bidding Program, Critical Peak Pricing, and Capacity Bidding Program Day Of. Table 16: SDG&E s DR Events with Ex Post Results within + 10% of the Daily Forecast Difference Forecast & Ex Post % Difference Between Forecast & Ex Post Program Name Event Date Daily Forecast MW Ex Post MW MW Demand Bidding Program 10/2/ % Capacity Bidding Program (Day Of) 8/8/ % Capacity Bidding Program (Day Ahead) 8/9/ % Capacity Bidding Program (Day Ahead) 8/14/ % Capacity Bidding Program (Day Ahead) 8/10/ % Demand Bidding Program 8/14/ % Summer Saver (AC Cycling) 9/15/ % Critical Peak Pricing 10/2/ % Critical Peak Pricing 8/21/ % Critical Peak Pricing 9/15/ % Demand Bidding Program 9/14/ % Critical Peak Pricing 8/30/ % A total of 19 DR program events had ex post load impacts that were greater than + 50% of the daily forecasts as depicted in Table 17. In particular, the residential and commercial Peak Time Rebate program ex post load impacts deviated from the daily forecasts by greater than 70%. According to SDG&E, the commercial Peak Time Rebate ex post load impacts were deemed to be not statistically significant. On this basis, SDG&E reported zero load impacts for this program. 22

27 Table 17: SDG&E s DR Events with Ex Post Results greater than + 50% of the Daily Forecast Daily Forecast MW Difference Forecast & Ex Post MW % Difference Between Forecast & Ex Post Ex Post Program Name Event Date MW A B C= B A D= C/A Commercial Peak Time Rebate 8/9/ % Commercial Peak Time Rebate 8/10/ % Commercial Peak Time Rebate 8/11/ % Commercial Peak Time Rebate 8/14/ % Commercial Peak Time Rebate 8/21/ % Commercial Peak Time Rebate 9/15/ % Residential Peak Time Rebate 8/14/ % Residential Peak Time Rebate 8/21/ % Residential Peak Time Rebate 8/11/ % Residential Peak Time Rebate 8/9/ % Residential Peak Time Rebate 8/10/ % Residential Peak Time Rebate 9/15/ % Residential Peak Time Rebate 7/20/ % Capacity Bidding Program (Day Ahead) 10/1/ % Capacity Bidding Program (Day Ahead) 10/2/ % Summer Saver (AC Cycling) 9/14/ % Critical Peak Pricing 8/11/ % Critical Peak Pricing 8/14/ % Base Interruptible Program 9/14/ % Capacity Bidding Program Day Ahead (CBP DA) The percent difference between the CBP DA daily forecast and ex post results respectively ranged from 32% 12% (Table 3). Based upon this assessment, the daily forecasts for CBP DA were not accurate or consistent predictors of ex post results. Since the CBP DA daily forecast model does not have a variable that accounts for weather, and the ex post models do, this methodological difference could account for the variability between the two load impact measures. Another factor that could affect this difference is the percent load impact per customer. Although customers submit load impact bids prior to each DR event, the actual load reduction on the event day may not coincide with the projected load reduction. If weather affects event day load reduction by CBP customers, the addition of a weather variable to the daily forecast model could increase its accuracy. In order to address uncertainty in the percent load reduction per CBP customer, DR test events could be scheduled to measure this value on event like days. Capacity Bidding Program Day Of (CBP DO) Similar to the CBP DA program, the CBP DO daily forecasts were not accurate nor consistent predictors of ex post results based upon the range of the difference, 27.4% 6.0% (Table 2), between the two load impact measures. As stated above, inclusion of a weather variable in the 23

28 daily forecast model and measurement of percent load reduction per customer during test events could increase the accuracy and consistency of the daily forecast model to predict expost load impacts. Demand Bidding Program (DBP) The percent difference between the DBP daily forecasts and ex post load impacts ranged from 8.0% to 8.0% (Table 3) for the three DBP events that were called during the summer. Based upon this result, the DBP daily forecast accurately and consistently predicted ex post load impacts. One caveat for making a general assessment of the DBP forecast model is that only one customer provided load reduction bids for the DR summer events. In order to do so, it would be advised to examine forecast and load impact data from at least 5 10 event days. Commercial Peak Time Rebate SDG&E reported zero ex post load impacts for this program in its March 4 th filing. According to SDG&E, zero values do not imply that no load reduction occurred but that the load impacts were not statistically significant. 20 Therefore, a comparison of daily forecasts and ex post load impacts could not be performed. Based upon conversations with SDG&E, the lack of effectiveness of the commercial Peak Time Rebate program could be attributed to a weak price signal and inelastic customer demand during event periods. SDG&E would be advised to discontinue the commercial Peak Time Rebate program. Residential Peak Time Rebate The percent difference between daily forecast and ex post load impacts ranged from 91.2% to 73.6% (Table 3). This implies that the residential Peak Time Rebate program daily forecast is not an accurate predictor of ex post load impact. However, the residential Peak Time Rebate program daily forecast consistently over predicted the ex post results. Since the ex post methodology only modeled load impacts for customers that signed up to receive e mail or text alerts and the daily forecast model does not, it is possible that the accuracy of the daily forecast model could improve if there was parity between the two methodologies. If only residential Peak Time Rebate opt in customers were included in the daily forecast model this may resolve the discrepancy. As an alternative solution, since the daily forecast consistently over predicted the ex post results, SDG&E might consider derating daily forecasts by a factor of 0.7 to 0.9 when estimating ex post load impacts. Summer Saver (AC Cycling) The range of the percent difference between daily forecast and ex post load impacts, 64.0% 38.7%, presented in Table 3 indicates that the daily forecast is not an accurate or consistent predictor of ex post load impacts. 20 SCE 03 at

29 It should be noted that the both the residential and commercial Summer Saver ex post methodologies (respectively a randomized experiment and a panel vs. customer regression) differed from prior years due to the availability of smart meter data 21. This could account for the difference between daily forecast and ex post results. In addition, both ex post methodologies utilized control and treatment groups, whereas daily forecast methodologies did not. According to this assessment, it would be advised to examine how the daily forecast and ex post models could be harmonized. Based upon a conversation with SDG&E, a temperature squared variable is utilized in the daily forecast model. Compared to SCE s current AC cycling daily forecast model, SDG&E s daily forecast model includes an additional measure of accuracy. However, in order to better predict customer behavior on successive event days or prolonged event hours, SDG&E might consider including an autocorrelation variable in the daily forecast model. Critical Peak Pricing The percent difference between the daily forecast and ex post results ranged from 3.1% 81.1%. This is the only program where the ex post results consistently outperformed the daily forecast predictions. According to SDG&E, the percent load impacts for the Critical Peak Pricing program in 2012 were lower in comparison to 2011 and led to an underestimation in the daily forecast 22. Critical Peak Pricing has approximately ~ 1,000 customers and, as SDG&E claims, any variation in the percent load reduction per customer could lead to high variation in the aggregate impact estimates. This would also be the case for large scale residential DR programs including Peak Time Rebate and Summer Saver (AC Cycling). SDG&E also claims that measurement error might account for differences between load impact category values. However, no explanation is provided to elucidate how the measurement error occurred (e.g. since Smart Meters were not fully deployed in SDG&E s territory during Summer 2012, measured load reductions obtained from analog meters were not accurate). Base Interruptible Program The percent difference between the daily forecast and ex post load impact for the Base Interruptible Program was 166.7%. Since two large Base Interruptible Program customers dropped out of the program, SDG&E was not able to accurately forecast the load impact from the remaining customers. It is possible that further analysis with additional Base Interruptible Program load impact data might shed light on the accuracy of the daily forecasting methods. 21 SDG&E load impact Filing Executive Summary, April 2, 2012 at SGE 03 at

30 Critical Peak Pricing Emergency Due to decreasing customer subscription to this tariff, the CPP E program was discontinued as of December 31, D. Summary of Recommendations Given the divergence between the daily forecast estimates and ex post load impact results, staff makes the following recommendations: The daily forecasting methods for all programs must be improved. The daily forecasting methods should be better documented and should be developed with relevant agencies and stakeholders. SCE should test a number of different forecasting methods for the Summer Discount Plan program. SCE should change the Summer Discount Plan program strategy of calling groups of customers for sequential one hour cycling events. SDG&E should include only opt in customers in the residential PTR daily forecast model. SDG&E should run a test event to improve CPP daily forecast estimates. SDG&E should account for customer behavior during successive event days in the Summer Saver daily forecast model. SDG&E should include a weather variable in the CBP forecast model. IV. Comparison of the 2012 Ex Post to the 2012 Resource Adequacy (RA) A. Summary of the Staff Analysis and Recommendations Comparing the 2012 ex post results with the 2012 RA forecast is not an accurate method of determining how the DR programs performed. RA load forecast represents the maximum capacity DR can provide under a set of condition for resource planning needs. Ex post load impact reflects the demand reduction obtained during actual events in response to operational planning needs. Resource planning and operational planning are different in terms of conditions (i.e. event hours, participation, and temperature) and purposes. However, in summer 2012, the Utilities DR programs had not been utilized to its full capacity even under an extreme hot weather condition. This raises the question of the usefulness of the current RA forecast and whether RA forecast should be changed to reflect the set of conditions reflecting operational needs that include the utilities day to day resource availability limitations and DR dispatch strategies for optimal customer experience. A working group that consist of the CPUC, CEC, CAISO, and the IOUs should be assembled to address the forecast needs (i.e. resource planning, operational planning) and input assumptions (i.e. growth rate, dropout rate) used for forecasting RA. 23 At 61, SDG&E load impact Filing Executive Summary, April 2nd 26

31 B. Background The 2012 RA forecast represents the maximum capacity DR can provide under a set of conditions for resource planning needs. The conditions entail a 1 in 2 weather year 24, portfolio level, entire participation, five hour window event (1 p.m. to 6 p.m.), and enrollment forecast assumption. The 2012 ex post load impacts reflect the demand reductions obtained during actual events in response to operational needs. Operational needs on the event day may not require the full capacity of DR because the condition does not warrant it. Utilities have the discretion to call for a few DR programs with shorter event hours or a smaller group of participants based on their generation and DR resource dispatch strategies. 25 This means an ex post impact may only reflect a 1 hour event window versus an RA forecast that has a 5 hour event window. Therefore, the ex post impact may reflect only a segment of a program s participants versus the RA forecast that assumed the program s entire set of participants. The ex post impact may reflect a lower temperature as versus the RA forecast that has a higher temperature of the 1 in 2 weather year condition. C. Staff Analysis Comparing the 2012 ex post results to the 2012 RA load forecast is not an accurate method on how well the program performs against its forecast. The table below contains August monthly average load impact for the 2012 Resource Adequacy (RA) forecast as filed in the spring of 2011 and the ex post results that occurred in There are stark differences between what the Utilities forecasted a year ahead (RA) and what the results are (Ex Post). On average for the month of August, the variability ranges from 485% (over performance) to 95% (under performance) for SCE and 58% to 97% for SDG&E. The main reason for the discrepancy is because the RA data is used to assist in resource planning, which means it is characterized as a 5 hour event in which all customers are called for the entire period (1 6pm) for the summer. However, ex post results reflect the impact from the actual DR operations, which means that it can be a 1 hour event in which some (not all) customers are called for a short period of time. Other factors that contributed to the discrepancy include temperature, enrollment and dual participation. 24 Represent the monthly peak day temperature for an average year. Exhibit SGE 03, Page SGE 06, Page 6. 27

32 Program Name Table 18: SCE Demand Response Load Impact 2012 Resource Adequacy vs Ex Post August Average (MW) RA Forecast Difference Ex Post RA vs. Ex Post % Difference RA vs. Ex Post A B C=B A D=C/A Demand Bidding Program % Demand Response Contracts % Base Interruptible Program % Capacity Bidding Program Day Of % Summer Advantage Incentive/Critical Peak Pricing % Agricultural Pumping Interruptible % Summer Discount Plan/ AC Cycling Residential % Save Power Days / Peak Time Rebates % Capacity Bidding Program Day Ahead % Summer Discount Plan/AC Cycling Commercial % Program Name Table 19: SDG&E Demand Response Load Impact 2012 Resource Adequacy vs Ex Post August Average (MW) RA Difference Forecast 30 Ex Post 31 RA vs. Ex Post % Difference RA vs. Ex Post A B C=B A D=C/A Critical Peak Pricing Default % Summer Saver/ AC Cycling % Capacity Bidding Program Day Ahead % Capacity Bidding Program Day Of % Base Interruptible Program % Reduce Your Use / Peak Time Rebates % Demand Bidding Program n/a 33 5 n/a n/a Critical Peak Pricing Emergency n/a 1 n/a n/a 26 Exhibit SCE 03, Table Exhibit SCE 03, Table Number based on September average because there were no events for month of August. 29 Number based on July average because there were no events for month of August or September. 30 Exhibit SDG 03, Table 1 31 Exhibit SDG 03, Table 1 32 Number based on September average because there were no events for month of August. 33 DBP was not approved until the year after the 2012 RA forecast was filed. 28

33 Forecasting DR estimate for resource planning needs is different than forecasting for operational needs. Unlike resource planning needs, operational needs on the event day may not require the full capacity of DR because the condition does not warrant it or the Utilities deployed optimal dispatch strategies for customer experience. Utilities have the discretion to call for shorter event hours or a smaller group of participants if the system is adequately resourced for that day. As discussed in Chapter 3, peaker or other generation resources may have been dispatched instead of DR even though such operation would be contrary to the Loading Order. 34 For example, SCE can divide its residential Summer Discount Plan participants into three groups and dispatch each group for one hour of an event, resulting in three consecutive one hour events (see chart below). Approximately 1/3 of the customers can be curtailed in any given hour. Rebound from the groups curtailed in event hours 1 and 2 can reduce the net impact in hours 2 and 3, lowering the average hourly impact for the entire event period. As a result, the average impact per hour can be roughly 100 MW for operation needs. The following figures illustrate the rebound effects from SCE s sub group dispatch strategy for its AC cycling. Figure 1 Source: SCE April 11, 2013 Power Point Presentation on 2012 Residential Summer Discount Program Ex Post vs. Ex Ante Briefing FE6 4B32 8C70 7C85CB31EBE7/0/2008_EAP_UPDATE.PDF. 29

34 However for the RA forecast, resource planning needs require the full capacity of DR. For example, SCE assumed all residential Summer Discount Plan participants would be curtailed at the same time to represent the full program capabilities of a reliability event (see chart below). Subsequent hourly impacts can be larger due to all customers being curtailed at once and rebound effect being delayed until end of entire event window. As a result, the average impact per hour for RA forecast can be roughly 300 MW, which is roughly 3 times greater than ex post in an hour. Figure 2 Source: SCE April 11, 2013 Power Point Presentation on 2012 Residential Summer Discount Program Ex Post vs. Ex Ante Briefing The opposite extreme condition could occur where the ex post result is higher than the RA forecast. In the case of SCE s Demand Bidding Program, the average ex post result is 72 MW, which is 6 times more than the RA forecast of 12 MW (see Table 18). Dual participation was the major contributor to the discrepancy. For customers who enrolled in two programs such as Base Interruptible Program and Demand Bidding Program, the RA forecast only counts the MW in one program (Base Interruptible Program) to avoid double counting. 35 Had the two programs been called the same day, the ex post would have shown a much lower amount for Demand Bidding Program. 35 Portfolio level. 30

35 September 14, 2012 was considered a hot day (1 in 10 weather year condition 36 ), however, SCE still did not dispatch their entire residential Summer Discount Plan participants. Instead, SCE only dispatched a portion of its participants for one hour of an event, resulting in a five consecutive one hour events. On average, SCE received only 6.3 MW 37 for the event, which is a huge underperformance in comparison to RA forecast of 519 MW. 38 This raises the question that if SCE chose not to dispatch all of its Summer Discount Plan participants at the same event hour during a 1 in 10 weather year condition, under what circumstances SCE will dispatch its Summer Discount Plan to its full program capacity. The usefulness of the RA forecast is in question if the utility does not test a DR program to its full capacity. Should the RA forecast process be amended to include another Ex Ante forecast that is based on operational needs including optimal customer experience, and if so what would that entail? D. Conclusion and Recommendations Comparing the 2012 ex post results to the 2012 RA load forecast is not an accurate method in determining DR program performance because the ex post results are in response to operational needs which can be entirely different than resource planning needs. However, in 2012 the RA forecast was not tested to its full capacity. This raises the question of whether RA forecast should be changed to reflect both planning needs and operational needs. A working group that consist of the CPUC, CEC, CAISO, and the IOUs should be assembled to address the forecast needs (i.e. resource planning, operational planning) and input assumptions (i.e. growth rate, drop of rate) used for forecasting RA. This working group should meet in December/January annually and come up with a set of input assumptions (i.e. growth rate, drop off rate) used for forecasting DR estimates. 36 Represent the monthly peak temperatures for the highest year out of a 10 year span. Exhibit SGE 03, Page Christensen Associates Energy Consulting 2012 Load Impact Evaluation of Southern California Edison s Residential Summer Discount Plan (SDP) Program, April 1, 2013, Table 4 3d. 38 Exhibit SCE 03, Table 1, 2012 RA for the month of September. 31

36 Chapter 3: Demand Response Program Operations I. Summary of Staff Analysis and Recommendations The 2006 to 2011 data shows that the Utilities historically triggered their DR programs far below the program limits in terms of number of events and hours. Even with the SONGS outage, the Utilities did not trigger their DR programs in 2012 summer more frequently as anticipated. Almost all of the Utilities 2012 DR program events and hours fall within the historical averages or below the historical maximum. However, staff was surprised to find that the Utilities dispatched their peaker power plants (peaker plants) three to four times more frequently in 2012 than the historical averages. The peaker plant service hours were closer to the plants emission allowances than the DR events to the program limits. Staff observed a trend where some DR program events decreased from 2006 to 2012 and yet peaker service hours increased in the same period. This trend raises a concern that the Utilities had under utilized DR programs and over relied on peaker plants. Under the Loading Order, DR is a preferred resource and intended to avoid the building and dispatching of peaker plants. Due to the time constraints and lack of additional information, Staff was unable to fully address this question and the reasons behind these trends in this report. Therefore, staff recommends in future DR program Measurement and Evaluations, the Commission evaluates the DR program operations and designs in comparison with the peaker plant operations to ensure the utilities compliance with the Loading Order. Specifically, the staff recommends that the Commission: 1. Require the Utilities to provide both DR event and peaker plant data and explanations for the disparity between historical DR event hours and peaker plant service hours in future DR evaluations and the next DR budget applications. The Utilities should include the DR and peaker plant hourly data and explain why they did not trigger DR programs during any of the hours when the peaker plant was dispatched. This information will inform the future DR program designs to improve the DR usefulness. 2. Require that DR historical operations be reflected in the input assumptions for the Ex Ante forecast and the evaluation of the program cost effectiveness. 3. Address the Loading Order policy in DR planning and operation and utilization of peaker plants in the next DR Rulemaking and the Utilities energy cost recovery proceedings. II DR Program Trigger Criteria and Event Triggers Appendices H and I are a summary of the Utilities 2012 DR program trigger criteria and the event triggers. The DR program trigger criteria consists of a list of conditions, which is selfexplanatory depending on the type of the program, e.g., Emergency Program triggers are based on system contingencies and non Emergency Program triggers also include high temperature, 32

37 III. heat rate (economic), and resource limitations. The 2012 event triggers were the actual conditions that led to the Utilities decisions to call DR events. While the DR trigger criteria provides some general ideas on how DR programs are triggered, there is lack of transparent information on the Utilities DR operations, e.g., when and how the Utilities made decisions to trigger a DR program. It is necessary to evaluate the DR performance not only from load impact perspective, but also from the DR operations to determine the DR reliability and usefulness as a resource. Staff analyzed the DR event data and gained some understanding on how the Utilities had utilized DR programs and how useful the programs were. DR Events Vs. Peaker Plant Service Hours How do the number compare to the 2012 limit and historically? As shown in Appendices J and K, SCE has a few DR programs with unlimited number of events or hours: Demand Bidding Program, Save Power Days (Peak Time Rebate), and Summer Discount Plan Commercial (Enhanced). Others have various event/hour limits ranging from 24 hours/month to 180 hours/year or 15 events/year. 39 For the DR programs with an event limit, most of them did not attain the maximum number of events and/or hours except for SCE s Summer Advantage Incentive (Critical Peak Pricing). 40 In summer 2012, SCE triggered 12 events for its Critical Peak Pricing, which is within the range of 9 to 15 events/year. Other DR programs event hours were well below the limits. For example, SCE s residential Summer Discount Plan (AC cycling) is the second to highest triggered programs with 23 DR events and 24 event hours in 2012, which is still far below the 180 hours of its event limit despite the SONGS outage. The Base Interruptible Program (BIP) had only one test event for two hours in However, SCE s DR program event hours were either within the program historical ranges or below the maximum except for Agricultural Pumping Interruptible with 7 hours in 2012 as comparing to 0 to 2 from 2006 to What were the reasons for the differences between the 2012 DR event numbers and hours and the event limits? SCE explained that the reasons for the differences between the 2012 DR event numbers and hours vary for each program, which is summarized in Appendix L. 41 The reasons can be characterized for the three types of DR programs as: 1) trigger conditions, 2) optimal dispatches, and 3) no nomination As discussed above, DR program operations are based on the trigger criteria set for each program. For the non Emergency Programs, SCE indicated that optimizing performance and minimizing customer fatigue is an additional factor considered in its decision to trigger a DR program. SCE s optimal dispatch strategy may have resulted in the DR events and hours far 39 SCE 02, Appendix E, Table 2 A at E 4 and E Id. 41 SCE 02, Appendix E, at E 6 and E 7. 33

38 below the maximum hours and events for the programs. For example, SCE s Summer Discount Plan is available for 180 hours annually. However, customers would probably never expect that this program will be triggered close to 180 hours based on their experience to date with the program. As shown in Appendices M and N, staff finds a similar trend with SDG&E s DR event data. IV. Peaker Plant Comparison Most of SCE s non Emergency Programs include resource limitation as a program trigger. Therefore, in theory, one would expect that SCE would trigger DR programs before dispatching its peaker plants in accordance with the Loading Order. In light of the SONGS outage, the Commission anticipated more SCE and SDG&E DR events in 2012, yet SCE dispatched peaker plants substantially more than DR programs (compared to their historical averages as discussed below. How do the historical DR events compare to the utilities peaker plants? SCE provided the permit and service hours for four of its own peaker plants, three were located in the SONGS affected areas, which is shown in Appendix O. 42 SCE historically dispatched its peaker plants about 9% to 16% of the permissible service hours annually. As shown in the table below, during the same period, SCE triggered its non Emergency DR programs 11 to 106 hours on average. However, in 2012, SCE dispatched its peaker plants three to four times more than the historical average. On the other hand, SCE s 2012 DR event hours were less than the historical range. SDG&E s peaker plant and DR event data show a similar trend as SCE. For example, SDG&E s Miramar ran 4,805 hours out of 5,000 hours of emission allowance. In contrast, its Critical Peak Pricing with the most triggered hours was dispatched 49 hours out of 126 hours of annual limit. Table 20: SCE: DR Event Hour Vs. Peaker Plant Service Hours Range 2012 Peaker Plants Hours Hours Non Emergency DR Hours 2 64 Hours SDG&E: Peaker Plants Hrs Hrs. Non Emergency DR Hrs Hrs. In addition, staff observed that the Utilities highest DR event hours occurred in 2006 and 2007 during the summer heat storms but the highest peaker plan hours occurred in This data suggests that the Utilities under utilized DR programs and over relied on its peaker plants, which is inconsistent with the Loading Order. 42 SCE 01, Appendix C, Tables 9 and 10 at Page

39 In its comments on the DR Proposed Decision, SCE disagreed with the suggestion of under utilization of DR programs based on the 2012 DR events. SCE argued that (s)imply because SCE did not dispatch all of the programs available hours does not mean the programs should have been dispatched more Optimal utilization (of DR) ensures the necessary amount of load drop to enable a reliable grid 43 SCE should explain why it dispatched its peaker plants substantially more last summer instead of DR and whether SCE s optimal dispatch of DR or the trigger criteria or designs resulted in SCE s increased reliance on peaker plants. Due to the time constraint and absence of the Utilities explanations, staff is unable to comprehensively address this issue in this report. The Utilities data warrants further evaluation to ensure the usefulness of DR resource as a replacement of peaker plants and the compliance of the Loading Order. V. Conclusions Consistent with D , staff finds that most of SCE s DR programs did not attain the maximum number of events and/or hours except for SCE s Critical Peak Pricing. The Utilities total numbers of DR events and hours in 2012 were within the historically average, but far from the program limits. However, in contrast, staff found that SCE owned and contracted peaker plants were dispatched far more in 2012 in comparison with the historical averages. Some peakers were much closer to their emission allowance than the DR hours were to their operating limits. Staff reaches a similar conclusion with SDG&E s DR programs in comparison with its peaker plants. If the Utilities have historically never triggered their DR programs close to the available hours, there is a concern with how realistic these limits are. There is a reliability risk if the Utilities are relying on a DR resource that has never been used to its full capacity. In addition, the DR cost effectiveness should reflect the historical operations. Staff recommends the Commission to address the issue in future DR evaluation and budget approval proceedings. 43 SCE Opening Comment filed on April 4, at

40 Chapter 4: Residential Demand Response Programs I. Summary of Staff Analysis and Recommendations Analysis of Residential programs included Peak Time Rebate (PTR) and AC Cycling. Overall, customers seem satisfied with the programs based on utility reports and surveys. However staff encountered problems with program design and operation that need to be addressed to improve reliability and effectiveness of the programs. For PTR, staff found that customers who received utility notification of events have higher awareness of the program when compared to customers who were not notified by the utility or received indirect notification such as mass media alerts. More importantly, data for both utilities show that customers who opted into receiving alerts were the only group that significantly reduced load. For both utilities, customers defaulted on MyAccount to receive alerts did not reduce load significantly. However, the entire eligible customer class qualifies for bill credits, which resulted in a problem of 'free ridership.' Both utilities should modify PTR from a default to an opt in program, where only customers opting to receive event alerts would qualify for bill credits. For SCE's Residential AC Cycling staff found that the current group dispatch strategy is resulting in a rebound effect. The rebound effect impacts the actual load reduction the program is capable of producing. Staff recommends SCE to (1) align the maximum program event duration with customer preference for shorter events to improve forecast, and to (2) reconsider its incentive structure to favor participation in longer event duration. Finally, both utilities should take advantage of AMI infrastructure and related enabling technology that could improve program delivery, reliability and customer experience. II. Residential Peak Time Rebate (PTR) A. Overall Customer Experience For both utilities, customers were generally satisfied with the program. For SCE, customers seem satisfied with the level of incentives, the time between notification and event. However customers would like more information regarding the program and bill credits. SDG&E s customers reported overall customer satisfaction with the program, but similar to SCE s customers, would benefit from more information and outreach. Level of awareness for both utilities seems higher amongst customers who chose to sign up to receive notifications. This is reflected in the overall load reduction verified by ex post data. Only customers who signed up for event notification significantly reduced load. For PTR, none of the utilities noticed evidence of customer fatigue, but this does mean it did not occur; just that it was not noticeable. 36

41 B. SCE s Peak Time Rebate/Save Power Day 1) Summary Customers who received utility notification of events have higher awareness of the program when compared to customers who were not notified by the utility. More importantly, customers who opted into receiving alerts were the only group that significantly reduced load. Customers defaulted on MyAccount to receive alerts and the remaining customers not directly notified by the utility did not reduce load significantly. SCE considered only customers who received alerts in their forecast and ex post verification. However, the entire eligible customer class qualifies for bill credits. Awareness of the program, reflected by the willingness to sign up for receiving alerts, seems to indicate more willingness to reduce load. This factor should be considered in program design. Staff identified an issue with free ridership, where customers are paid even though they didn t significantly reduce any load. Staff recommends changing PTR from a default program to an opt in program, paying bill credits only to customers who opt in to participate. 2) Background D approved Save Power Day, SCE s Peak Time Rebate (PTR) rate. The decision approved bill credits of 0.75c/kWh reduced with an additional 0.50c/kWh for customers with enabling technology. This is a default program for residential customers with a smart meter and has been available since The program provides incentives to eligible Bundled Service Customers, who reduce a measurable amount of energy consumption below their Customer Specific Reference Level (CSRL) during PTR Events. 44,45 The utility may call events throughout the year on any day, excluding weekends and holidays. Events will take place between 2pm and 6pm on days an event is called. Participants receive a day ahead notification of the event. Bill credits will be paid in each billing cycle based on the sum of events called and usage reduction during the period. 46 Bill credits will be recovered from the respective customer class through the Energy Resource Recovery Account (ERRA). During 2012, SCE started defaulting customers on MyAccount to receive notifications, with the remaining customers not directly notified by the utility. Alternatively, customers may choose to opt in to receive alerts. As of November 30th, approximately 4 million customers are on PTR and 824,000 were signed up to receive notifications (via MyAccount). 47 According to SCE, 44 SCE Schedule D Domestic Service, sheet 3 45 CSLR: peak average usage level is the customer s average kwh usage during the 2:00 p.m. to 6:00 p.m. time period of the three (3) highest kwh usage days of the five (5) non event, non holiday weekdays immediately preceding the PTR Event. The CSRL is used to determine the customers kwh reduction for each PTR Event in order to calculate the rebate. 46 SCE Schedule D Domestic Service, D Att. C at SCE 01 Testimony at 27, lines 11,

42 approximately 60,000 customers have opted in to receive alerts in 2012 during the summer months. 48 3) Lessons Learned In support of its Application, SCE provided data to highlight lessons learned from the 2012 program year. Customer awareness Awareness of the program is higher amongst the group of customers whom the utility notified of events: 66% of notified respondents were familiar with the program but only 43% were familiar in the group not notified 49. When prompted for awareness of events, the same pattern is noticeable. 72% of respondents in the group receiving notifications who were aware of the program claimed awareness of specific events, compared to 40% in the group not receiving notifications. When including customers aware and the ones prompted with information about the program, 55% of the notified group was aware but only 23% of the nonnotified respondents was aware. 50 Customer satisfaction There was no information regarding customer perception of fairness of savings/incentive levels in SCE s data, however customers seem to link participation with expectation of savings as 80% of respondents identified earning bill credits as important for participation 51. Moreover, participants seem to be willing to participate even in the face of low savings. 52 Event notification The majority of respondents aware of the program found out about events via utility notification (over 60% for the opt in group). Close to 23% of respondents in the overall population found out about events in the news. 53 According to results of the customer surveys, about 90% of customers notified of the event and about 56% of customers not notified but aware of the event, were happy with the amount of time between notification and event 54. It appears that a day ahead strategy could be adequate, however customers were not prompted regarding preference for a day of reminder, so it is not clear from the lessons learned if this could increase awareness and response. SCE requested to add a day of notification in their Program Augmentation Application, which the Commission denied due to lack of evidence of need communication with SCE (4/5/2013) 49 SCE 02 Appendix A at 3.It is important to note that the surveys only represented results for two groups: customers notified by the utility and customers who were not notified. Defaulted customers and customers not defaulted into receiving notifications from the utility were bundled together under notified customers. 50 SCE 02 Appendix A at 4 51 SCE 02 Appendix B at SCE 02 Appendix B at SCE 02 Appendix A at 5 54 SCE 02 Appendix A Save Power Day Incentive/Peak Time Rebate Post Event Customer Survey at D , at 28 38

43 Customer preference Another survey showed that customers would benefit from more information about the program, most specifically in terms of expectations of savings. The majority of customers would prefer to be notified by and they believe that a reminder at the beginning of the summer would help them to be more ready to participate. 56 Program utilization PTR has no limits on the number of events called, with maximum of 4 hours per event. SCE called 7 events, 28 total event hours in 2012 and did not observe evidence of customer fatigue. The trigger criterion was temperature for all events. 57 Although SCE explains the need to balance usefulness with the preservation of the resource 58, the program appears underutilized in Still, this is the first year of the program. Other findings SCE states that third party providers such as telecommunication companies, cable companies, security providers, retailers, and manufacturers of thermostats or providers of home automation services are potential partners to reach untapped load reduction potential in the residential sector 59. As part of their Program Augmentation Applications, SCE has proposed a pilot to explore this market and the Commission has approved funding for this pilot. 60 4) Analysis of settlement and ex post data Ex post load impact SCE only calculated ex post data for customers notified of events; it did not verify ex post load impact for customers not notified by the utility. This indicates that this group was not expected by SCE to reduce load significantly. SCE s 2012 Load Impact Report found that customers who opted into event notifications reduced a statistically significant average of 0.07kWh per hour. 61 The same report found that customers defaulted into receiving notifications did not produce statistically significant load impact. 62 Incomplete data does not allow staff to verify with certainty the differences in load reduction between all participant groups (opt in, defaulted in notification and the remaining of the population). However staff looked at the all the data SCE provided to look for evidence of what is most likely happening. 56 SCE 02 Appendix B Save Power Days Research Study Results at SCE 03 March 4, 2013 Appendix B Table 4; SCE o1, Appendix C at SCE 01, Appendix C at communication with SCE April 10, D , OP Load Impact Evaluation of Southern California Edison s Peak Time Rebate Program Christensen Associates Energy Consulting (4/1/2013) at 1. This figure is slightly lower than what the 0.097kW reported on SCE 03 March 4, 2013 at Id at 24 39

44 It is interesting to notice that for the first four events, customers defaulted did reduce load although not significantly, but for the three last events, their load in fact increased. In contrast, the opt in group, to various degrees, reduced load for all events. The ex post results varied considerably between events, even though the temperature seems fairly constant and not extreme. It would be interesting to investigate why such variability and how it could help to improve ex post results to improve reliability of the program. A more detailed analysis of impact can be found on the sections above. Event Date Customers who opted into alerts (a) Table 21: 2012 Ex post Load Impact by Group (MW) (Average Event Hour) Customers defaulted into alerts excluding Opt in alerts (b) Customers not notified directly of events (c) Temperature (d) 7/12/12 N/A N/A N/A 80 8/10/ N/A 89 8/16/ N/A 89 8/29/ N/A 92 8/31/ N/A 86 9/7/ N/A 84 9/10/ N/A 89 Source: communication with SCE (3/25/2013); SCE 01 Appendix C Table1 Settlement data analysis In 2012, SCE paid a total of $27,349,008 in incentives for PTR residential customers. 63 SCE provided full settlement data, which shows evidence of a potentially large free ridership problem, where customers receive incentives without significantly reducing load. 63 communication with SCE (4/5/2013) 40

45 Table 22: Settlement Load Reductions MW (Average Event Hour) Event Date Customers who opted into alerts (a) Customers defaulted into alerts excluding Optin alerts (b) Customers not notified directly of events (c) Event Settlement (d) 7/12/ ,613 1,839 8/10/ ,018 8/16/ ,499 1,821 8/29/ /31/ ,166 9/7/ ,105 1,332 9/10/ ,049 1,250 Average (MW) % 4.9% 11.3% 83.9% 100.0% Average Participants 60, ,430 1,265,544 1,486,165 % 4% 11% 85% 100% Source: communication with SCE (4/5/2013) According to settlement data, 84% of bill credits were paid to customers whose load impact was not considered for forecast or ex post purposes. In addition, 11% of incentives were paid to customers defaulted into receiving notifications and did not produce statistically significant load impact. 64 This means that in fact 95% of all incentives were paid to customers who either were not expected to or did not reduce load significantly Load Impact Evaluation of Southern California Edison s Peak Time Rebate Program Christensen Associates Energy Consulting (4/1/2013) at 24 41

46 Event Date Customers who opted into alerts (Expost MW) (a) Table 23: 2012 PTR Incentives Paid Customers defaulted into alerts excluding optin alerts (expost MW reduction) (b) Customers not notified by SCE (c) Total 7/12/12 $254,572 $419,794 $4,836,197 $5,510,563 8/10/12 $166,245 $403,752 $2,480,819 $3,050,816 8/16/12 $261,825 $699,568 $4,495,547 $5,456,940 8/29/12 $110,681 $252,931 $1,734,182 $2,097,794 8/31/12 $157,557 $398,093 $2,939,474 $3,495,124 9/7/12 $181,406 $496,648 $3,312,785 $3,990,840 9/10/12 $184,349 $418,665 $3,143,816 $3,746,830 Total $1,316,635 $3,089,451 $22,942,822 $27,348,908 % 5% 11% 84% 100% Source: communication with SCE (4/5/2013) As there is no ex post data for customers not directly notified by the utility (either opted to receive or defaulted in notification), it is not possible to verify their actual impact and if it would be significant or not. However, based on the fact that not even defaulted customers reduced load significantly and findings from SDG&E (see next section), it is fair to assume that results for that group would not be significant. Incentives and capacity cost It is possible to notice difference in cost of capacity between the group who opted in to receive notification and the group defaulted to receive notifications. In this report, staff normally used the average event hour reductions. But as in SCE s case there is such variability in ex post results, staff will use average hourly impact for all events as a simple way of showing that the average capacity produced by the defaulted group is nearly six times more expensive than the average capacity produced by the opt in group. 42

47 Event Date Customers who opted into alerts (MW) (a) Table 24: 2012 PTR Cost of Capacity Incentives paid to the group per event (b) Customers defaulted into alerts excluding Optin alerts (MW) (c) Incentives paid to the group per event (b) 7/12/12* N/A $254,572 N/A $419,794 8/10/ $166, $403,752 8/16/ $261, $699,568 8/29/ $110, $252,931 8/31/ $157, $398,093 9/7/ $181, $496,648 9/10/ $184, $418,665 Average Total $1,062,064 $2,669,657 Cost of Capacity $75.34 $ Source: communication with SCE (4/5/2013). Staff did not include the 7/12/12 event in the calculation as there is not ex post data for this event. 5) Findings Based on analysis of program design, settlement and ex post load impact and customer participation data for the summer of 2012, staff has found the following: The program, as approved in the decision, pays the same amount of incentives for all customers enrolled into the program. There is additional incentive for customers who have enabling technology. There are differences in performance, awareness and willingness to reduce load between customers who were notified directly by the utility and customers who were not. Customers are overall satisfied with notification mode, timing and level of incentives. There is not enough information to determine if customer fatigue is an issue. Ex post analysis of customers who opted into alerts significantly reduced their load in comparison to customers only defaulted into alerts. This indicates that customer willingness to participate (indicated by the action to sign up for alerts) may help improve load reduction. Incomplete ex post load impact results show load reduction for customers notified by the utility both who have signed up and defaulted into receiving alerts. No results were available for the entire population. It is not possible to verify if incentives paid to non notified customers did not result in significant load reduction, but the fact that SCE does not include this group in its forecast and ex post results indicates that their load impact is not significant. 43

48 There is potential free ridership issue in SCE s PTR. C. SDG&E s Peak Time Rebate/Reduce Your Use 1) Summary Overall, customers are satisfied with the program. There is difference, however, in load awareness and load reduction between customers who opted into receiving alerts and the rest of the population. Only customers who opted into receiving utility notification significantly reduced load. However, the entire population qualifies for bill credits. Awareness of the program, reflected by the willingness to sign up for receiving alerts, seems to indicate more willingness to reduce load. Staff identified an issue with free ridership, where customers are paid even though they didn t significantly reduce any load. Staff recommends changing PTR from a default program to an opt in program, paying bill credits only to customers who opt in to participate. 2) Background D approved the Reduce Your Use program, SDG&E s Peak Time Rebate (PTR) rate, the first dynamic rate of such design approved by the Commission 65. The program has been available since the summer of 2012, with a pilot in The program is implemented as proposed: A two level PTR incentive with a higher level payment for customers who reduce electric usage below an established CRL [customer reference level] 66 with enabling demand response technology, and a lower level payment to customers without such technology. 67 Customers receive a bill credit of 0.75$/kWh with an additional credit of 0.50$/kWh for customers with enabling technology. SDG&E s tariff lists programmable communicating thermostats (PCTs), AC cycling, pool pump cycling as examples of technologies eligible for the 0.50 /kwh additional incentive. 68 Commission has approved the addition of In Home Displays (IHD) to the list of enabling technologies in SDG&E s tariff. 69 The utility may call events throughout the year without limit to the number of events called. Events will take place between 11am and 6pm on days an event is called and participants receive a day ahead notification of the event. Bill credits will be paid in each billing cycle based 65 SCE s Save Power Day program was approved in 2009 on D Defined as the total consumption for the PTR event period averaged over the three (3) highest days from within the immediately preceding five (5) similar non holiday week days prior to the event. The highest days are defined to be the days with the highest total consumption between 11 a.m. and 6 p.m. The similar days will exclude weekends, holidays, other PTR event days, and will exclude other demand response program event days for customers participating in multiple demand response programs. SDG&E PTR Tariff. 67 D at SDG&E PTR tariff defines enabling technologies as to be initiated via a signal from the Utility, either directly to the customer or the customer s device, or via a third party provider to the customer or the customer s device that will reduce electric energy end use for specific electric equipment or appliances, is included in a designated Utility demand response program, and that is acceptable to and approved by the Utility, subject to the verification of processes necessary to safeguard confidential and proprietary Utility and customer information. 69 D , OP 22 44

49 on the sum of events called and usage reduction during the period. Bill credits will be recovered from the respective customer class through the Energy Resource Recovery Account (ERRA). 70 The utility can call only one event per day with a maximum of 7 hours. 3) Lessons Learned In support of its Application, SDG&E provided data to highlight lessons learned from the 2012 program year. For PTR, SDG&E conducted three post event surveys. Customer Awareness Results of the surveys showed differences in level of awareness between the three main groups 71 of customers participating in PTR: customers who actively opted into day ahead event notifications (opt in), customers registered onto MyAccount and receiving event notifications (default) and customers not directly notified by the utility, but notified via mass media (no MyAccount). In general, the opt in group demonstrated the highest level of awareness of the PTR events. About 83% of the opt in group was aware of the program concept events and bill credit, compared to 43% of respondents in the defaulted group and 40% in the no MyAccount group. 72 Customer Satisfaction Customers are generally satisfied with the amount of incentives paid. 73 Customers also seem generally satisfied with number of notifications, although respondents did indicate that more promotion and information about the program would be beneficial. 74 SDG&E indicated that is working to resolve issues of notification encountered in 2012 as well as working to improve customer education for using online tools. 75 Overall, customers responded positively to the program. Program Utilization In the summer of 2012, SDG&E called 7 events, a total of 49 event hours, and all events were called due to temperature 76. Given that this program has no limit of events, the program seems underutilized. However SDG&E states that even if a temperature point is reached, the program may not be necessarily called, as system need is assessed internally. This approach also takes into consideration customer experience. 77 Customer Fatigue SDG&E states that it is difficult to determine if customer fatigue is an issue, but ex post results show that when program was called three days consecutively in August, the load impact 70 SDG&E GRC Phase 2 Settlement at SDG&E in post event surveys segmented customers into more than the groups analysed in this report, but to simplify the analysis, staff looked only at the main three groups of participants. 72 SGE 02 February 4 th, 2013 Attachment 6 (Table 5) 73 SGE 02 Revised appendix X at SGE 02 Feb 4 th, 2013 Att. 5 Table 13, Att. 6 Table 9 75 SGE 02, Revised Attachment 1 Revised Appendix X at19 76 SGE 02, Revised Attachment 1 Revised Appendix X Table SGE 02, Revised Attachment 1 Revised Appendix X at 14 45

50 was lowest on the last day. 78 Temperature does not seem to be a factor as the day with the lowest reduction had similar temperature to two preceding days. Still, the result does not seem conclusive. Enabling Technology Event Date Table 25: Customer Fatigue 79 Average Event Hour Reduction (MW) Temperature ( F) 8/9/ /10/ /11/ Enabling technology seems to be improving load reduction as preliminary results show that customers with In Home Display (IHD) saved 5% to 8% on average during events, while customers without saved between 0% to 2%. 80 Effort to reduce usage during events SDG&E investigated as part of post event surveys what actions customers would take on event days and the level of effort made to respond. While actions taken were hypothetical, i.e. do not reflect reported actions taken, respondents in all three groups seem aware of possible actions to reduce load. For instance 38% of opt in respondents, and around 30% of MyAccount and 30% no MyAccount said they could unplug electronics. 41% of the opt in, 23% of my account and 19% on no MyAccount would turn off AC. When prompted about the effort made to reduce usage during the August 14 th event, 33% of opt in respondents indicated having made a lot more effort than usual in comparison to around 10% for MyAccount and 10% no MyAccount respondents. 54% of the opt in respondents and around 40% of MyAccount and 40% of no MyAccount groups said they made somewhat of an effort. Finally 13% of the opt in, 50% of the MyAccount and 44% of the no MyAccount made no more or less effort than usual to reduce load. 81 The results seem to indicate that respondents in all groups, irrespective of IOU notification, may have made an effort to reduce load and did know what options they had to do so. Still, expost load reduction shows that only the opt in group, about 6% of the entire population, significantly reduced load, contradicting assumptions that mass media or defaulting customers into alerts could generate significant reduction. 78 SGE 02, Revised Attachment 1 Revised Appendix X at Source: SGE 02 Attachment 1, Revised Appendix X, Table 2 6; SGE 03 March 4th Table SGE 02 February 4 th, 2013 at 5, Lines SGE 02 February 4 th, 2013 Attachment 6 (Table 11 and 12). 46

51 4) Analysis of settlement and ex post data Ex post load impact Awareness of the program and willingness to participate (in the form of signing up to receive alerts) seem to be an important factor in load reduction. This is supported by analysis of ex post data. The opt in group was the only group to produce statistically significant load reductions 82. Event Date Customers who opted into alerts (a) Table 26: Ex Post Load Reductions 83 (Average Event Hour MW) Customers on MyAccount excluding Opt in alerts (b) Customers not on MyAccount excluding opt in alerts (c) Temperature (d) 7/20/ /9/ /10/ /11/ /14/ /21/ /15/ Settlement analysis Based on average hour load reduction used for settlement calculation, 94% of incentives were paid to customers either defaulted to receive alerts on MyAccount or customers not on MyAccount and 6% were paid to customers that opted into alerts. 84 When compared to expost data, only customers who opted into alerts, or about 4% of the total population enrolled on PTR, significantly reduced load. 85,86 This points to an issue of free ridership, where customers receive incentives without significantly reducing load. 82 SGE 01a, at Source: SGE 02 Attachment 1, Revised Appendix X, Table 2 6; SGE 03 March 4th Table SGE 02, Attachment 1, Revised Appendix X Table 3 and SGE 03 March 4, 2013 Table SGE 02, Attachment 1, Revised Appendix X at 4 and Table For PTR residential and small commercial the participants represent the customers who proactively opted into alerts and the enrollment number represents all the customers who were eligible to receive a bill credit. Fifty percent of residential customers are enrolled in MyAccount and received an e mail alert. SGE 02, Attachment 1, Revised Appendix X at 4. 47

52 Table 27: Settlement Load Reductions MW 87 (Average Event Hour) Event Date Customers who opted into alerts (a) Customers on MyAccount excluding Opt in alerts (default) (b) Customers not on MyAccount excluding opt in alerts (c) Event Settlement (d) 7/20/ /9/ /10/ /11/ /14/ /21/ /15/ Average (MW) % 5.9% 49.4% 44.7% 100.0% Average Participants 45, , ,250 1,171,232 % 4% 48% 52% 100% Incentives and capacity cost In 2012, SDG&E paid out $10,134,879 in incentives for PTR residential customers. 88 If assuming the estimate MW reported to the CAISO (7 day Report), the program maximum expected capacity was an average event hour impact of 45.8 MW (event hours). 89 This implies a capacity cost of approximately $221/kW. According to ex post data, the actual capacity generated was an average event hour of 8.2MW resulting in a cost of capacity of $1,232.7/kW. This cost will be recovered from the residential class of customers. 5) Findings Based on analysis of program design, settlement and ex post load impact and customer participation data for the summer of 2012, staff has found the following: The program, as approved in a Commission decision, pays the same amount of incentives for all customers enrolled into the program. There is additional incentive for customers who have enabling technology. 87 Source: Adapted from SGE 02 Attachment 1, Revised Appendix X, Table 2 5; SGE 03 March 4th Table SDG&E AL 2420 E, at SGE 02, Attachment 1, Revised Appendix X Table 3. 48

53 There are differences in performance, awareness and willingness to reduce load between the three main groups of participants: customers who opted to sign in to receive alerts, customers defaulted into MyAccount to receive event alerts and customers not yet on MyAccount and not being directly notified by the IOU and who finds out about events via mass media. There is not enough information to determine if customer fatigue is an issue. Ex post load impact results show only customers who signed in to receive alerts significantly reduced load. 94% of incentives paid did not result in significant load reduction. Free ridership is an issue in SDG&E s PTR, where the majority incentives were paid to customers who did not significantly reduce load. Based on incentives paid during the summer of 2012, the cost of capacity is five times higher when adjusting forecasted load impact by ex post load impact. D. Staff Recommended Changes for PTR It is clear that free ridership is an issue that needs to be addressed. It is an issue when forecasting load reduction the forecasted impact would be much higher than what could be verified, and results in additional costs to ratepayers. While free ridership in most cases is a baseline and settlement methodological issue, this issue could be partially alleviated by changes in program design. Incentives should reward and encourage customer engagement. Therefore, staff recommends changing PTR from a default program to an opt in program, eliminating incentives paid to customers not actively choosing to receive event alerts and keeping the current incentive level to customers who sign up to receive alerts and use enabling technologies. Staff suggests the following incentive structure: Table 28: Propose Program Structure Group $/kwh Opt in to receive alerts 0.75 Opt in to receive alerts and Enabling Technologies Not opt in 1.25 Not a participant in the program This approach to PTR would ensure that customers are rewarded for the level of action they are prepared to take. If this proposed level of incentives were in place in 2012, it could have reduced the amount of incentives paid by about 95% as shown below To simplify the calculation, staff ignored the additional $0.50/kWh for enabling technology. These incentives would be paid in addition to the $0.75 /kwh. 49

54 Table 29: Iillustration of Staff Proposed Changes for SCE Current Incentive Structure Group Incentive Level ($/kwh) Capacity (MW Ex post*) Total incentive paid ($) Cost of capacity ($/kw) All ,349, Proposed Incentive Structure Opt in ,328,160 No opt in Potential reduction 95% * Ex post for the entire program Table 30 Iillustration of Staff Proposed Changes for SDG&E Current Incentive Structure Incentive Level Group ($/kwh) Capacity (MW Ex post*) Total incentive paid ($) Cost of capacity ($/kw) All ,108,082 1, Proposed Incentive Structure Opt in ,750 No opt in Potential reduction 94% * Ex post for the entire program While issues of baseline and settlement methodology are out of the scope of this analysis and would demand a much more in depth investigation, it is possible to attempt to alleviate the impact of free ridership by limiting PTR bill credits to customers who do not opt to participate. Utilities should focus on encouraging customers to adopt enabling technologies. Perhaps some of the resources saved by having a three tier structure of incentives could be used to subsidize enabling technologies to enable direct load control. Also, utilities should explore alternatives to service delivery such third party entities. SCE found that the interest of third parties is shifting towards the residential sector and such opportunities should be seriously explored. Finally, utilities should track as part of their ex post verification efforts, if the presence of enabling technologies significantly improves load reduction and if there is difference between different technologies used. In addition, utilities should look to investigate if customer fatigue is an issue, especially in view of the SONGS outage potentially increasing the trigger of PTR events

55 III. Residential Air Conditioning (AC) Cycling A. Overall Customer Experience Customers were generally satisfied with the program. For SCE, 2012 was the year the program was transitioned from emergency to price trigger. SCE reports customers have kept a positive view of the program and regarded incentives an important part of participating in the program. Customers did report that they prefer shorter and more frequent events as opposed to longer events. SDG&E also reports overall customer satisfaction but points that the majority of customers complaints were due to uncomfortable temperatures due to the unit cycling on/off. Also, SDG&E reports customers were satisfied with the level of incentives. No utilities reported customer fatigue, although SDG&E had three events in consecutive days and load reduction dropped. However, without analyzing other factors, such as humidity and customer perceptions of discomfort, amongst other factors, that could have contributed to load impact reduction, it is not possible to say with certainty if it did occur or not. A. SCE s Summer Discount Plan 1) Summary SCE s AC Cycling changed its event trigger structure from emergency to price. Customers seem satisfied with the current program design. Staff has identified that the program has issue of rebound effect and recommends that the program design should be changed to include an additional level of incentive that would cater to customers willing to cycle their unit for the entire event duration in below. 2) Background As part of a D , SCE agreed to transition the Residential Summer Discount Plan (Res SDP) from emergency to price trigger and to bid Res SDP s load in the CAISO market for dispatch. D authorized revisions to SCE s program to enable the changes agreed to in a settlement. 91 As currently designed, Res SDP offers an annual incentive for customers who wish to participate in the program. The program offers two choices for cycling duration as well as gives customer the choice to override an event up to five times in the year for slightly lower incentives. Incentives are calculated according to size of the equipment, cycling duration and override option: D at SCE Schedule D SDP, sheet 1; SCE 01 Testimony Table II 2 51

56 Table 31: SCE Residential AC Cycling Incentives Option Incentive p/ Summer Saver day p/ ton 100% cycling maximum savings (based on 4.5 ton unit) 50% cycling maximum savings (based on 4.5 ton unit) Standard Option Override Option $0.36 (100% cycling) $0.18 (50% cycling) $0.18 (100% cycling) $0.09 (50% cycling) $200 $100 $100 $50 SCE Res SDP program has approximately 307,000 customers with an expected load reduction of 466MW. 93 Events can be dispatched year round with a maximum of 180 hours and each event can last up to six hours. In 2012, SCE paid a total of $51,882,087 in incentives. 3) Lessons Learned The 2012 summer season proved to be a transition year for this program. Customers had to transition from an expectation of little service reduction to expecting several disruptions throughout the year. Overall, SCE asserts that customers continue to have a positive view of the program. Lessons learned from the transition in 2012 showed that bill savings are an important element for customer participation. The majority of customers opted for the Standard Option preferring savings to override capability, and the ones who chose to override rarely used it. 94 Only 1.5% of customer who left the program did so due to the program changes. Preliminary findings of customer surveys found that customers prefer shorter events even if more frequent. SCE experimented with different event duration calls and found that as events got longer, customer dissatisfaction increased. In 2012, SCE triggered 23 events for a total of 24 hours, for reasons of temperature, CAISO Emergency and evaluation. Because the program changed the trigger condition and design in 2012, historical comparison would not be accurate. But data shows that Res SDP was called more often than in previous years. 95 B. SDG&E s Summer Saver 1) Summary Customers seem satisfied with the program. The program performed in accordance with past years. Staff does not recommend any changes to the program design. 93 SCE Schedule D SDP, sheet 1; SCE 01 Testimony at 9, Lines Load impact based on ex ante estimates from Commission Monthly Report (12/21/2012) 94 SCE 01 Testimony at 11, Lines SCE 03 March 4, 2013, Appendix B Table 4. 52

57 2) Background The Summer Saver program is a 15 year long term contract based procurement run by Comverge. 96 Comverge is responsible for installing, removing and servicing the AC unit. Summer Saver is a direct load control program where a device is installed on the premise to cycle the AC Unit when an event is called. It has a day of notification, meaning customers receive event notification on the day of the event. The program runs May through October. Customers are eligible to annual incentives for participation based on the cycling option and size of the unit and participation period: 97 Table 32: Summer Saver incentives Cycling Option Res Bus 30% N/A $ 9.00 Per ton 50% $ $ Per ton 100% $ N/A Per ton The Summer Saver program had around 28,500 residential and commercial customers enrolled in The majority of participants are residential customers 23,948 in 2012, and this distribution has been fairly consistent since The program has an event limit of 15 events or 120 event hours. The utility can call one event per day and events run for minimum 2 hours and maximum 4 hours. Events can be called anytime from 12pm to 8pm on event days. In 2012, the utility called 8 events or 29 event hours, an average of 3.6 hours/event. Events will be called based on temperature and system load ) Lessons Learned Residential customers were responsible for 84% of load reduction during the 2012 summer. SDG&E paid $2.5 million in incentives to residential customers for 18.6 MW average event hour. The majority of customer complaints were due to uncomfortable temperatures due to the AC cycling. 101 Overall, customers seem satisfied with the level of incentives as SDG&E reported that less than 1% of customers who left did so due to unfair incentives consumer/find a program 97 money/demand response/summer saver program and communication with SDG&E on (3/4/2013) 98 SGE 02, Attachment 1, Revised Appendix X Table communication with SDG&E (4/4/2013) 100 SGE 02, Attachment 1, Revised Appendix X Table SGE 02, Attachment 1, Revised Appendix X at SGE 02, Attachment 1, Revised Appendix X at 20 53

58 SDG&E did not report evidence of customer fatigue for Summer Saver, although it recognizes that this does not mean fatigue does not occur, just that it is not measurable. 103 Expost load impact results showed that when the program was called three days consecutively there was a drop in the load reduction. However, SDG&E states that there is not enough information to suggest that this is a result of fatigue. Humidity or outside temperature being lower in the last day than the previous day amongst other factors could have contributed to lower load reduction in the last day. Table 33: AC Cycling customer fatigue 104 Ex post average over event period (MW) Date Res Res+Com Temperature 9/13/ /14/ /15/ The frequency of events called has been fairly consistent throughout the program availability (with a few exceptions like 2008), with the program being called in 2012 according to historical average. But when compared to program design, it seems under utilized. Still, there is a higher incidence of events in comparison to event hours inferring events are more frequent, but shorter. 103 SGE 01, Direct Testimony of Michelle Costello at SGE 02 Attachment 1, Revised Appendix X, Table 2 6; SGE 03 March 4th Table 2; communication (4/3/2013). 54

59 Table 34: SDG&E Summer Saver Historical Comparison of Number of Events and Event Hours 105 Year Event hour (year) Event hours called Number of events (year) Events Called Average Average historical performance compared to design 24% 51% 2012 compared to historical average According to average According to average C. Staff Recommended Changes for AC Cycling Staff does not have any recommendations to change in program design for SDG&E at this point. SDG&E s is a mature program and customers seem fairly satisfied with the offerings. SCE s program trigger just changed from emergency to price and customers seem satisfied with the program overall. However, last summer SCE deployed a new dispatch strategy of which it divided the customers into three to six subgroups with one hour per event per subgroup instead of the whole group triggered for the entire event duration. While such strategy is optimal for customers comfort, as discussed in Chapter 2, such strategy caused a rebound effect 106 Program design should help correct this issue. First, the program as designed states that events can last up to six hours, even though customers seem to prefer shorter event durations and dissatisfaction went up as event duration increased 107. Also, SCE counts a total of six hours per event for RA purposes. SCE needs to review the program proposal to reflect 105 Based on SGE 02, Attachment 1, Revised Appendix X Table Effects of an event in subsequent hours, when electricity usage may exceed the curtailed customers reference load, as air conditioners work to return residences to original temperature set points Load Impact Evaluation of Southern California Edison s Residential Summer Discount Plan (SDP) Program at Staff does not have more detailed information on customer preference or what would be the ideal event duration before customers drop off the program. 55

60 customer preference if customers will not favor being cycled for 6 hours the program should not have such long event duration proposal. Moreover, SCE should explore new ways of delivering the program, i.e. using temperature control via a PCT instead of a switch in the equipment that cycles the unit off/on. This could allow for longer event duration while maintaining customer engagement as the unit would never be off completely 108. In fact, both SDG&E and SCE should take advantage of AMI infrastructure and related enabling technology that could improve program delivery, reliability and customer experience. 108 D at 27 states that innovative approaches via using PCTs and OpenADR could enable shorter event duration. At the time, the Commission did not have data that reflected the rebound effect which may discourage short event durations. This issue should be taken into consideration when designing the approved pilot. 56

61 Chapter 5: Non Residential Demand Response Programs I. Summary of Staff Analysis and Recommendations The analysis of customer experience for DR programs for commercial customers focuses on three key commercial programs: AC Cycling, Auto DR and Demand Bidding Program (DBP). Staff recommends that the outreach and marketing of the new features of SCE s AC Cycling program be clearly communicated to the customers to avoid customer dissatisfaction and dropout. In addition, Staff finds that there is limited evidence that the Auto DR program coupled with the Critical Peak Pricing (CPP) rate provides evidence of greater load impact than the load impacts obtained by customers on the CPP rate alone. As a result, Staff recommends that future studies continue to explore the load impacts of Auto DR. Staff recommends SDG&E and the Navy collaboratively design a Navy only DBP program to meet the unique needs of the Navy. Key attributes of the program would include a day ahead trigger, aggregation of 8 billable meters and a minimum bid requirement of 3 MW. II. Background and Summary of Utility Data In response to the Energy Division letter, SCE and SDG&E provided data on the commercial customer experience and commercial customer participation in the non residential DR programs. Customer enrollment and participation numbers during events by program were provided as well as the load impacts that those customers produced. In addition, SCE and SDG&E provided qualitative information on the commercial customer experience of the DR programs including how customers felt about the incentives offered, whether customers were fatigued by consecutive DR events and if the customers felt that too many DR events were called. SCE and SDG&E also provided information on the efficacy and customer experience of DR event notification. Overall, SDG&E reported that the customer experience was positive, and that it tried to deliver notification to drop load earlier than required (for both commercial and residential customers). Among the various non residential program offerings, SDG&E offers a Capacity Bidding Program (CBP) where participants can choose between a day ahead and a day of program. Participants are required to reduce their usage by 20 kw or more. Program participants receive a capacity payment and receive an energy payment for the hours of reduction. However, the program also carries penalties for a reduction of less than a 50% pledge. The customer feedback for this program came from aggregators 109 who suggested that increasing the incentives could potentially increase enrollment in CBP. SDG&E offers a Demand Bidding Program and has two enrolled non residential customers in this program. In 2012, the Demand Bidding Program was offered on a day ahead basis with incentives to customers for reducing their demand during an event. In response to SDG&E s 109 An aggregator is an entity that aggregates or combines customer load and makes it available for interruption. 57

62 questions about incentives, the DBP customers indicated that the incentives were not high enough. The Commission adopted SDG&E proposal of changing this program from a day ahead to a day of, 30 minute trigger program 110. Another SDG&E non residential program offering is the Peak Time Rebate(PTR) program (Commercial). On event days, participating customers are required to reduce their electricity use during the event duration. Customers can sign up to be notified of events in advance. Commercial customers signed up for alerts at a much lower rate than residential customers and also provided less load reduction. Most likely, this is due to limited ability to reduce load between 11 a.m. and 6 p.m. SDG&E included three post event PTR surveys, which provided results of residential and small commercial customers experiences to the PTR event. Key trends were: Small commercial customers were generally aware of Reduce Your Use days. However, event specific awareness was lower. Small commercial customers indicated that they face different challenges than residential customers in responding to PTR events. Feedback on program improvement from commercial customers included the following comments: commercial customers stated that they were not able to reduce more and were already doing what they could; small commercial customers indicated that they would benefit from advanced notification; and finally, they stated that responding to events would affect their business operations or customer comfort. General program feedback from SDG&E indicated that estimating the effects of customer fatigue on load impacts is difficult. When event days are called in a row, there are many varying factors, such as events being called on different days of the week, varying temperatures on event days, that it is difficult to determine whether the change in load impact is due to multiple event days or other influencing factors. SDG&E describes its experience with PTR events called in quick succession, and indicates that preliminary load impacts were lowest on the last day. This may be due to customer fatigue. For the other programs, the load impacts did not show evidence of customer fatigue. Again, this is not conclusive of customer fatigue not being present. Customer fatigue was simply not measurable relative to other variations in load impacts between events. SCE launched a Summer Readiness Campaign in April 2012 in order to prepare the customers for the upcoming summer. Overall the customer experience was responsive and positive. SCE offers many non residential DR programs similar to the programs offered by SDG&E. These programs include an AC Cycling program. This program offers customers various AC Cycling options where the utility can directly turn off the customer s air conditioner when needed. Customers receive a credit based on several factors, including the program cycling options that they choose and the AC unit cooling capacity. SCE has proposed changes to this 110 D at

63 program and has requested the ability to call events not just for emergency reasons, but also for when the prices are high. Another non residential program offered is the Auto DR program. The program provides incentives to offset the cost of purchase and installation of technology to help the customer automatically manage their load. The customer determines their load control strategy and presets it in the technology. With the technology in place, the program automates the process of reducing demand by sending a signal from a central system to the customer s automated control system, which then automatically reduces usage during program event duration. During the 2012 Summer Event Season, the Demand Response Help Desk (for large business customer DR program) received 1,410 calls. 21% of those calls were related to program events, however, none of the callers indicated that there were too many events or that the incentive payments were inadequate. Non event calls (79%) pertained to program eligibility, questions about enrollment, assistance with online tools and other general program information. In mid August, SCE conducted market research to gauge customer awareness of enrollment campaigns and SCE messaging, customer actions in response to the campaigns, and attitudes towards SCE and energy conservation. Overall, most of the residential and small business customers heard the campaign message and attempted to reduce their usage. Most of the customers understood the need to conserve energy over the summer and attempted to do so. Customer awareness was raised and the campaign prompted some customers to enroll in SCE programs. Customer attitudes about reliability and avoiding outage remained strong. SCE did not observe customer fatigue during 2012 event season for DR programs in general. The programs are able to avoid multiple consecutive days of events by flexibility in the dispatch triggers of the programs. III. Commercial Air Conditioning (AC) Cycling A. SCE s Summer Discount Plan In December 2012, SCE conducted a pilot telephone survey on several programs, including the Summer Discount Plan (SDP) program 111. The overall sample size was 200 business participants, though the sample size varied by the question being asked. The satisfaction with the program was moderate, with only 72% of the participants aware that their business was enrolled in SDP. The Decision (D ) approved SCE s proposed changes to the SDP Commercial program, and we examine the commercial customer experience, as presented through this survey, in detail. Overall, a larger percentage (81%) of participants felt that the program was worthwhile. Of the three main touch points identified, billing was the key and customers were moderately satisfied with this touch point. Relatively few participants (18%) had reasonably high familiarity with the program details. Customers who had high familiarity tended to be more satisfied. Customers who received targeted SDP communication were more familiar and more satisfied with the program. 111 Service Delivery Satisfaction Recalibration: Summer Discount Plan 2012 Pilot Survey. 59

64 Most of the business participants were SCE customers at home (86%) and were predominantly male (63%). There were three main touch points, which had a significant impact on satisfaction. Billing, enrollment and events were key drivers, with billing being the highest priority driver, and events being the lowest priority driver. Customers had difficulties identifying the discount and not thinking the discount was fair given the effort it took to participate. For enrollment, customers were primarily concerned with delays in the device installation. Customer reasons for event dissatisfaction were, specifically, the time, day, and frequency of events as well as a perception of fairness. The satisfaction with the billing was 78%, which was considered to be at a moderate level compared to other SDP touch points. 83% received paper bills, while 19% received electronic bills. 17% could not easily find the discount on the SDP bill. The top two comments on the SDP bill were to provide a separate line item of discount and offer a bigger discount/lower rate. The bill currently includes a separate line item for the discount so customers are not able to find it and need to be reminded that it is there. The problems with event attributes were low (8%). Satisfaction with enrollment was modest (78%). 7% experienced problems with enrollment with most of the problems being related to confusions (amount of the discount, expected savings) or delays (waiting for the device to be installed, multiple visits, and multiple phone calls). The more satisfied customers were the ones that were aware that: 1. They receive a discount regardless of event. 2. The indicator light identifies an event in progress. 3. Events occur between June 1 to October The maximum duration of event is 6 hours. Relatively few participants (18%) had reasonably high familiarity with the program details. Most business participants were aware of the 100% and 50% cycling options. Awareness of the methods (indicator light, SCE.com) of determining whether the device was currently cycling the AC off was at less than half of the respondents. Only 22% of the respondents knew the correct start and end months of the program; many of the other customers did not know or did not provide correct answers to the question. Those that were correct tended to be more satisfied with the program. Only 12% of the respondents identified the correct 6 hours that an event can last. 21% said that there was no limit, and they were less likely to be satisfied with the program. 57% of the respondents who knew that they receive discounts whether or not the events were called were more likely to be satisfied as a result. The number of events did not impact satisfaction. When investigating the reasons for program satisfaction, 36% of the respondents were happy with the program and 17% responding that there was a good discount provided. 19% of the comments were negative. 11% of this feedback was related to financial reasons such as the bill being too high, or that the bill increased, or that the discount was small. Bad customer service was also another negative at 5%. 60

65 Around a third of the customers provided suggestions for improving the SDP. In this feedback, financial comments were paramount, with the following reasons being cited: Lower rates (5%) Bigger discount (5%) Better communication (4%) A large percentage of participants (77%) did not know the discount amount. Participants who are most satisfied are likely to know the discount dollar amount. Participants with moderate to high familiarity were more likely to have received recent communication from SCE. All types of communication boosted familiarity though the written method was the dominant form. B. SDG&E s Summer Saver Program The findings in this section are based on KEMA s process evaluation of the 2008 Summer Saver program 112. At the time of the evaluation, the program had 4,500 commercial participants (and even greater number of residential participants). Commercial customers can chose between 30% and 50% cycling options and choose between 5 day and 7 day option. To the extent to which commercial customer experience was provided, it is cited in this report. For other cases, general feedback is cited. Since this information is dated, we used it primarily for general feedback on the Summer Saver Program at SDG&E and as a means of comparing the AC Cycling programs of SCE and SDG&E. A key conclusion of the report included improving the program marketing and informational materials to reduce program dropouts and attract more interested customers. Better information about cycling frequency could have resulted in less dissatisfaction and drop out. Discomfort and program cycling were most often the top reasons for dropout. Better marketing could have reached customers who are interested in the program. The report recommended customizing marketing messages to customer subgroups. Surveys of Summer Saver participants and non participants discovered that bill credit messages had greater appeal to lower income customers while environmental messages had greater appeal to higher income customers. With regard to cycling options, the report recommended to reduce program complexity by reducing the number of cycling options. A related cycling recommendation was to not increase the cycling frequency. Currently the program cycles times a year, and participants indicated that they were uncomfortable during Summer Saver control events. The key reason that participants joined the program was for the financial incentives. 112 Process Evaluation of SDG&E Summer Saver Program, March 19,

66 Key Lessons Learned from the AC Cycling Programs When comparing the feedback received for the AC Cycling program for SCE and SDG&E, a clear recommendation emerges marketing, clear communication and managing expectations is a key facet of the program. When customers know what to expect, they tend to be more satisfied with the program. SCE customers with high familiarity of program attributes fared better and were more satisfied. SDG&E could also improve marketing and information materials to reduce dropouts and attract interested new customers 113. Clarifying the program and making it less complex is important to attract and retain customers. Targeting those messages, by subgroups in the case of SDG&E, is another useful method in attracting customers based on their values and priorities, whether they are financial or environmental. D approved SCE s proposal of modifying its commercial program from a reliability based DR program to a program that can be dispatched for economic purposes. The new trigger will allow the program to be called when there are high wholesale market prices, which occur during times of extreme temperature or when the system demand is higher than expected. Additionally, SCE will consolidate the Base and Enhanced commercial programs into one program with different features, and proposes that the SDP be made available year around. The key program changes are outlined below: Table 35: Program Element Current Design Approved Design Curtailment Event Trigger Emergency Only Emergency and Economic Program Availability Events can occur June 1 September 30 Events can be called year round with a maximum of 180 event hours during a calendar year. Event Duration 6 hours Multiple events may occur in a single day, with varying durations. Maximum 6 hour interruption in a day. Customer Cycling Options 30%, 40%, 50%, and 100% 30%, 50%, 100% With the movement to an economic based program and the new program features, it is paramount that the marketing campaign clearly explain the changes, such as the duration of the event, which is now expected to be shorter, yet the programs can be called year around. Billing changes should also be made to assist customers in identifying discounts. SCE customer feedback on program improvement was largely financial. SCE s new program design has new incentive levels. The new proposed enhanced program will pay a greater incentive per ton/month than the current enhanced program, and the new incentive should be communicated clearly to the participants, whether it is through clear bill presentation or marketing efforts or a combination of the two. 113 This survey is dated, so SDG&E may have made marketing modifications to alleviate some of the concerns presented above. 62

67 In 2012, the Summer Discount Plan Commercial was triggered once for 5.6 hours 114. With its movement to an economic based program, which can be called when wholesale market prices are high, it is likely to be called more frequently. The Capacity Bidding Program Day Ahead (CBP DA) had a heat rate trigger condition in 2012, and that program can be used as an example of how frequently a non emergency based program may be called. In 2012, the CBP DA was called 12 times. The proposed changes for SCE s AC Cycling program may provide the needed megawatts this summer and will also benefit customers who are often financially motivated. However, these expected changes need to be communicated in a clear way to avoid customer dissatisfaction and possible customer dropout of the program. If the marketing program is managed carefully, SCE s Summer Discount Program for Commercial customers can be a useful source of load impact for the summers of 2013 and IV. SCE s Auto DR Auto DR is a technology program whereby customers receive an incentive to install equipment to improve the ability for load reduction during a DR event. Auto DR is considered to provide a better load shed as described in the Decision (D ): Limited data suggests that ADR customers have a higher participation rate in DR programs and provide better load shed. Data also suggests that customers on dynamic rates perform better with ADR. SCE s Auto DR customers pre program the level of DR participation and when a DR event is called, the Auto DR technology enables the facility to automatically participate. This method reduces the necessity of a manual response. All non residential customers must have an interval meter and participate in an available price responsive DR program. As of 2013, customers are paid 60% of technology incentives during installation testing verification; 40% of eligible incentives are paid according to participation in a DR program 115. By the end of 2012, SCE Auto DR program funding was 100% subscribed 116. In the Application, SCE requested approval for an additional $5 million for Auto DR which would be earmarked for projects in the Target Region. The majority of the funding ($4,200,000) was for the technology incentive payments. The key questions which arose were what the customer experience was with the Auto DR program and how effective were customers in shedding load when events were called. In the Application, SCE does not have a breakdown of DR programs by those customers who participate in Auto DR. To understand customer experience better, we refer to other studies done on the efficacy of Auto DR and customer feedback on the program. CPP is a rate that sets a higher price for electricity during critical peak days. In return, the customer receives a reduction in the non peak energy charge, demand charge or both charges. 114 SCE SCE 03 at SCE 02 at

68 A report on the non residential CPP presents the estimated ex post load impacts of Technology Incentives and Auto DR participants on average for 2011 CPP Event 117. SCE called 12 CPP events in 2011 over the months of June and September. On average, each event had 3,006 participants. For SCE s CPP customers for 2011, the percentage load impact was 5.7% for the average event and the average load impact was 11.6 kw. There were 35 CPP customers on Auto DR, and they provided a percentage load impact of 21%. The average load impact was 103 kw. Based on this information, customers on Auto DR and CPP provide a greater load reduction than customers on the CPP rate alone. To further understand Auto DR and its potential to provide load impacts, we examine a study by Enernoc on CPP 118. SCE and SDG&E offer Technology Assistance and Technology Incentives Programs. SDG&E s Technical Assistance program provides customers with energy audit services to identify potential for energy cost reduction and encourage participation in DR and EE programs. The Technology Incentive program at SDG&E provides financial incentives and on bill financing (interest free) for customer adoption and installation of DR measures and enabling technologies. The EnerNOC study outlines the barriers to response to an event. The main barrier for those customers which were the bottom performers, or the low performing participants, is the lack of ability to reduce demand because of business needs, and that responding to an event would negatively impact business functions. Examples of these limitations included a need to maintain a temperature for preventing produce from spoiling or to protect sensitive equipment from damage, or just for reasons of comfort of staff. A related barrier to response is the lack of knowledge on how to reduce load. Additional barriers included lack of enabling technology, however, this is not identified as a top concern. Most of the top responders, or the high performing participants, are able to easily shift their processes or shut down heavy energy using equipment, and respond to events. However, few of the top responders use technology to automate their response. The main barrier to responding to events is the ability to respond and not suffer negative business consequences. For businesses which have the capacity to respond and not be negatively impacted as a result, technology is a possible solution which can be explored. Due to the small population size, only 16 technology enabled customers were interviewed. The majority of those interviewed were SCE customers. This is a small sample size and the feedback should be interpreted with caution. Half of these customers said that the technology was important for their response, and the other half stated that they would have stayed on the CPP rate without the technology. Four of the customers interviewed do not utilize the technology installed; 3 of these customers respond to events. Select feedback includes: The load we shed is entirely enabled by the Auto DR technology SCE technology enabled California Statewide Non Residential Critical Peak Pricing Evaluation, p California Statewide CPP Research on Improving Customer Response, December 3,

69 Most of the bottom responders do not use technology to respond and are not aware of options in this regard. From the quantitative data, Auto DR customers on the CPP program provide greater load impacts than those customers on CPP without enabling technology. However, the data above, though limited due to the small sample size, can provide direction for continued research. With the additional Auto DR funding request in SCE s application, the participant pool continues to grow. With this growth, it is possible to conduct better studies with more robust results. Studies can attempt to get to benefits provided by Auto DR, in particular the load impact which can be attributed to Auto DR and which, in its absence, could not have been achieved. V. SDG&E s Demand Bidding Program (DBP) The Commission approved SDG&E s Demand Bidding Program in the middle of summer 2012 as a part of the mitigation efforts to address SONGS outage. 119 SDG&E called 3 Day Ahead DBP events and obtained a load reduction of 5.1 MW, 5.4 MW and 4.6 MW. During the course of 2012, SDG&E spent $44,192 on this program, which was minimal comparing to its residential PTR program costs of $10 million for only 4 MW of load reduction. The recent DR decision (D ) approves SDG&E s proposed continuation of its Demand Bidding Program modified from a day ahead to day off, 30 minute product. The purpose of this modification was to align the program with the Energy Division Letter and provide programs that can provide quick response capability. In its comments, the Navy stated that the DBP with a 30 minute trigger would only permit participation from entities with automated demand response systems, in effect reducing participation. The Navy requests the continuation of the day ahead program. The Navy states that the 2012 DBP did not allow for the Navy s participation and the change to a day of, 30 minute program will further limit the Navy to participate. Instead the Navy proposes a day ahead program, with some modifications. The Navy proposes that the customer be allowed to aggregate 8 billable meters. The second proposal is to lower the minimum bid requirement from 5 MWh to 3 MWh. The Navy states that it may not be able to produce 5MWh at a single geographic location and cites its experience of August 2012, when during a Demand Reduction test, the Navy shed 4MWh from a multitude of shore facilities on three Navy Installations. SDG&E responded to the Navy s comments, and explained why it believes the Navy did not participate in the 2012 DBP. SDG&E understand that the Navy will participate in an emergency program; however, the DBP is not a day ahead emergency program. In its response, SDG&E indicated its willingness to work with the Navy and create a demand response program to meet the Navy s unique needs. 119 In Resolution E 4511 on July 12,

70 Staff recommends that SDG&E and the Navy collaboratively develop the Navy only DBP program, which will address the following issues raised in the Navy s comments to the DR Proposed Decision: A day ahead trigger to enable the Navy to appropriately plan for the event. 2. The ability to aggregate 8 billable meters. 3. Lower minimum bid requirement from 5 MW to 3 MW. Experience from the Demand Reduction test demonstrates that the Navy has the ability to reduce load and be a useful DR resource for SDG&E s system during the summer. 120 Filed on April 9, 2013 in A

71 Chapter 6: Flex Alert Effectiveness I. Summary of Staff Analysis and Recommendations The Flex Alert campaign has not been evaluated since Earlier evaluations from suggest that the impacts of an emergency alert have ranged from an estimated 45 MW to 282 MW. The utilities have identified areas to improve communication between CAISO and the utilities when alerts are triggered and cancelled. The utilities also question whether customers are confused about the differences between a Flex Alert event and local Peak Time Rebate events. The utilities cite several reasons to consider transitioning Flex Alert from a utility funded program, to a CAISO led and funded program. Staff finds that there is a lack of data to evaluate the effectiveness and value of the Flex Alert campaign. Staff agrees with the utilities that an evaluation in the current program cycle is needed. Staff finds that there is merit to the utilities proposal to terminate Flex Alert as a rate payer funded and utility led activity after Rather than providing recommendations in this report staff defer to the proceeding that is currently reviewing the utilities statewide marketing, education and outreach applications, (A , A , A , and A ) and the Phase I Decision in that proceeding, D II. Background Flex Alert is the current name of a statewide marketing campaign that asks Californians to conserve or shift electricity when the CAISO determines that there is a risk that electricity supply may not be adequate to meet demand. 121 This alert campaign is approved through CPUC decision and the CPUC authorizes the three investor owned electric utilities to provide the total budget. One utility acts as the lead utility, and contracts with a marketing agency to develop TV and radio ads, and purchase advertising time. The marketing agency purchases advertising slots throughout the state to run the ads during the summer season, when demand is likely to be highest and the grid is more likely to be constrained. CAISO triggers an alert based on grid conditions and informs the utilities and the marketing agency. The marketing agency swaps out informational advertisements with emergency alert messages, calling a Flex Alert and asking Californians to do three things during a six hour window of time on a specific day 1) turn off unnecessary lights, 2) set air conditioners to 78 degrees, and 3) wait until after 7PM to use major appliances. Individuals and businesses also have the opportunity to sign up to receive or texts notifying them that there will be an alert. Flex Alert Performance in 2012 In 2012, two Flex Alert events were called on August 10 and August 14. Initially Flex Alerts were triggered on August 9 for August However, the Alerts for August 11 and 12 were later cancelled. A formal evaluation of Flex Alert was not conducted in The utilities did 121 From the name for emergency alerts was Power Down, and from they were referred to as Flex Your Power Now. 67

72 not conduct any analysis to determine an estimate of the impacts that resulted from either Flex Alert event. SDG&E was concerned that customers would not recall the difference between Reduce Your Use, which provides customers a bill credit, and Flex Alert, which provides no monetary benefits. In the event that customers did not understand the difference between Flex Alert and Reduce Your Use, SDG&E wanted to avoid customer frustration that could occur when customers reduced their usage during a Flex Alert but were not paid for it. To mitigate confusion, SDG&E triggered its Reduce Your Use program on the same days when Flex Alerts were called. There were three days when the utility triggered a Reduce Your Use event when there was no Flex Alert. However, the utility claims that the weather on the three Reduce Your Use event days was atypical, and therefore the utility cannot determine the load reductions attributable to Flex Alert by comparing Flex Alert days with the days when Reduce Your Use was called and Flex Alert was not. 122 SCE also states that with the limited data available the utility cannot determine the effect of a Flex Alert. SCE did a basic comparison of two days with similar conditions when the same DR programs were dispatched, one day with a Flex Alert and one day without and concluded that Flex Alert could be counter productive because SCE s total system load was higher on the day the Flex Alert was called. 123 In comparison, there have been three evaluations of the alert campaign in its history: , , and The evaluation did not estimate the impact of an alert event. The evaluation reported that the system wide demand response impact on Flex Alert days, (including all other demand response programs that were called), ranged from 200 MW to 1100MW. The impact from Flex Alert was a portion of this total. The evaluation estimated the load impacts associated with alert events, specifically from customers adjusting their air conditioner settings in response to the ads. Although, the study estimated impacts ranging from 93 MW to 495 MW, 124 in 2008 the consultant redid its analysis with revised assumptions and adjusted the estimate to be between 45 MW and 75 MW. 125 The 2008 evaluation estimated load impacts based on customers turning off lights, and adjusting air conditioners. The study estimated that impacts from alert events in 2008, based on customers taking these two actions ranged from 222MW to 282 MW. 126 Since 2008 there has been a long gap since Flex Alert has been evaluated. In 2009 and 2010 no Flex Alert events were triggered. In 2011 there was one event, but there was no evaluation. Given that Flex Alert has not been evaluated since 2008, and the utilities seem unable to draw any conclusions about load impacts attributable to Flex Alert events, it is reasonable to plan an evaluation for the summer of The Commission issued a Decision on the utilities 122 SGE 02 at SCE 01 at Flex Your Power Now! Evaluation Report, Summit Blue Consulting, May 22, 2008, p A link to this report is provided in Appendix S Flex Alert Campaign Evaluation Report, Summit Blue Consulting, December 10, 2008, p A link to this report is provided in Appendix S. 126 Id. 68

73 statewide marketing application on April 18, The Decision includes a directive to evaluate the program. 127 III. Utility Experience with Flex Alert SCE identified three weaknesses with the implementation of Flex Alert. First, the utility states that challenges exist because neither a utility nor the PUC own the trademark to the name Flex Alert. Second, the utilities did not receive advanced notice from the CAISO when a Flex Alert was triggered or cancelled. Third, inability of the CAISO to accurately forecast the duration of an alert resulted in confusion, when an alert was cancelled. 128 The utilities state that they were contacted by CAISO at the same time that news media and the general public was informed about a Flex Alert. CAISO held weekly calls with the utilities to discuss weather forecasts and the likelihood a Flex Alert would be called. However, when an alert was triggered the utilities learned of the event through a robo call, automated or text message, which are the same methods used to inform residential customers and media outlets. The utilities would prefer to have advanced notification so that they are able to strategically coordinate their own DR program initiation, and to proactively communicate with customers. The cancellation of the weekend alerts on the 11 th and 12 th also caused confusion. SDG&E claims that both internal staff and local media were confused about whether or not conservation and Reduce Your Use days were still necessary. 129 SCE acknowledges that it is inefficient and costly to re contact media outlets to cancel alerts. Flex Alert radio and television commercials continued to air throughout the weekend, because the marketing agency was not able to give the media stations adequate time to switch the messages before the ads were locked in for the weekend. To add to the confusion, CAISO s website continued to indicate there was a Flex Alert even though the agency had issued a press release stating the weekend alert events were cancelled. 130 Prior to the start of the 2013 Flex Alert season, the utilities, CAISO and the marketing agency should discuss the weaknesses identified by the utilities from The organizations should use their expertise and the recommendations from past Flex Alert evaluations to identify methods to improve the timeliness of communication and ensure that implementation is as efficient and effective as possible. IV. Customer Experience Only one utility, SCE, conducted a survey in 2012 to determine customer awareness and reaction to the 2012 Flex Alert campaign. Although SDG&E did not conduct a survey, the utility raised concerns that both customers and the media seem confused about the difference between Reduce Your Use events and Flex Alert. 131 SCE found that 10 percent of surveyed 127 D , Ordering Paragraph SCE 01 at SGE 02, Attachment 1 at SCE 01 at SGE 02, Attachment 1 at 26 69

74 customers were confused about the difference between the utility s Peak Time Rebate and Flex Alert. 132 SCE reported the following results from its survey of 400 customers. 133 Nearly 60% of residential customers reported hearing or seeing a Flex Alert advertisement 54% of small business customers reported hearing or seeing a Flex Alert message 25% of residential customers surveyed reported that they took steps to reduce electricity use on a Flex Alert day 21% of small business customers reported taking steps to reduce when a Flex alert was called Compared with past evaluations customer recall of Flex Alert ads has increased from one evaluation period to the next. In , 12 percent could recall hearing or seeing an ad, compared to 15 percent in , and 23 percent in A formal evaluation in 2013 can help determine if the jump in awareness reflected in SCE s survey results is an accurate reflection of the trend. The 2013 evaluation should take into account the variety of mechanisms used to relay information about alerts to customers. For example, 2012 was the first year that the utilities conducted outreach through Community Based Organizations to help prepare customers for a Flex Alert event. Another highlight from SCE s survey is that 25 percent of residential customers took action in response to an alert. This percentage is also an increase from past evaluation results. In past years between 10 and 21 percent of residential customers reported taking action in response to the ads. 135 However, SCE s survey failed to determine whether customers accurately understood the message that a Flex Alert is intended to convey. All three prior evaluations found that customers did not understand that they were supposed to adjust their behavior for just the day of the Flex Alert event. Instead customers reported continuing to conserve during afternoon hours every day since the event had been called. 136 While conservation has its own benefits, the purpose of a Flex Alert is for customers to shift load during a brief peak event. It will be important for utilities, the CAISO and the marketing agency to continue to strive to accurately relay this concept, and for an evaluation to determine if the right message is getting through to customers. The utilities made one specific recommendation to improve the program in They proposed to continue community outreach partnership efforts in 2013 and 2014 in the 132 SCE 01 at SCE 01 at Process Evaluation of the 2004 / 2005 Flex Your Power Now! Statewide Marketing Campaign, Opinion Dynamics Corporation, July 24, 2006 p. 5; Flex Your Power Now! Evaluation Report, Summit Blue Consulting, May 22, 2008, p. 90; 2008 Flex Alert Campaign Evaluation Report, Summit Blue Consulting, December 10, 2008, p. 83. Links to these reports are provided in Appendix S. 135 Id. 136 Id. 70

75 demand response proceeding. The Commission adopted a Decision on April 18, 2013, which approves these requests. V. The Future of Flex Alert SDG&E sites a passage from the SCE s testimony in its Statewide Marketing Application which identifies several reasons that the Commission should consider that CAISO take full control of the statewide emergency alert campaign starting in SDG&E states that they support the recommendation made by SCE. SCE s testimony states that since 2004 the utilities have funded alerts through ratepayer dollars. However, when alerts are called, the results benefit customers outside of the utilities service territories as well, yet neither CAISO nor nonutility Load Serving Entities contribute to the funding. SCE also pointed out that from only one alert was triggered. Increased growth in utility demand response programs has positively impacted grid reliability, the utility states. SCE found that balancing utility specific regulatory constraints with the CAISO desired scope of the program was challenging. As an example CAISO requested to share emergency alert messaging with Baja Mexico to promote energy conservation in that region. SCE s testimony goes on to state that the utilities do not have the discretion of when to trigger the program. SCE recommended that Since CAISO triggers the program, the CAISO should assume total ownership of, and authority over it. SCE requests that this recommendation is approved during so that CAISO has the opportunity to seek funding in it GMC cost recovery. 137 The Commission adopted a Decision on Phase 1 of the utilities statewide marketing application on April 18, The Decision authorizes a total of $20 million to be spent on Flex Alerts between now and the end of The Decision also directs the program to be evaluated. The Decision includes a directive for the utilities to work with CAISO to develop a proposal for the transfer of the administration and funding of the Flex Alert program to the CAISO or another entity, effective in The Decision directs SCE to submit the proposal in the Statewide Marketing Proceeding by March 31, VI. DR Program Ex Post Load Impact Results on the Flex Alert Days As shown in tables below, all three utilities triggered a DR event for some of their DR programs during the two Flex Alert days with a total of 739 MW of load reduction from 4:00 5:00 p.m. on August 10, 2012 and 432 MW from 3:00 4:00 on August 14, The CAISO reported that the actual system peak load during the peak hours between 3:00 p.m. to 5:00 p.m. were significantly lower than its forecasts and attributed the load drops to its Flex Alerts. However, the data suggests that a large or some portion of the load reduction came from the DR programs. Appendix P shows the ex post load impact for each of the utilities DR programs on the two Flex Alert days. 137 SGE 02, Attachment 1 at D at

76 Table 36: Utilities DR Program Ex Post Load Impact on the Flex Alert Days 139 Utility 8/10/12: Ex Post (MW) 3:00 4:00 p.m. 4:00 5:00 p.m. SCE SDG&E 8 27 PG&E /14/12: Total SCE SDG&E PG&E No Events Total Provided to staff through s. Data source: the utilities April 2, 2013 Load Impact Reports (links to the reports are provided in Appendix S). 72

77 Chapter 7: Energy Price Spikes I. Summary of Staff Analysis and Recommendations Because most DR programs are dispatched a day ahead or several hours ahead of events, it is difficult for the utilities to effectively use DR programs in response to real time price spikes. There were many days where price spikes occurred but DR programs were not called, and conversely there were days where DR programs were called but no price spikes occurred. 30 minute or 15 minute DR programs could respond to price spikes much more efficiently. II. Definition of Price Spikes For the purposes of this report, a price spike day was defined as any day where the average hourly real time price hit $150/MWh or more in any 3 or more hours from HE12 HE18. This definition is designed to evaluate only those hours where DR could respond. By restricting the definition to HE12 HE18 the definition considers only those hours where DR can be called. By also restricting the definition to days where 3 or more hours were above $150/MWh, this eliminates days with momentary jumps in price that DR could not reasonably be expected to respond to. III. DR Programs and Price Spikes Using the definition above, SCE had 67 hours that averaged $150/MWh or more across the hour, with 7 days where 3 or more hours averaged $150/MWh or more across the hour. SDG&E had 126 hours that averaged $150/MWh or more across the hour, with 18 days where 3 or more hours averaged $150/MWh or more across the hour. DR events overlapped real time price spikes with varying success. SCE was successful on 2 out of 7 days, whereas SDG&E was successful on 4 out of18 days. 140 Table 37: Number of Days with Energy Price Spikes SCE SDG&E Days that DR events successfully overlapped price spike days (3 or more hours of $150/MWh) between HE12 HE Number of price spike days (3 or more hours of $150/MW) between HE12 HE Days that DR events were called Days that DR events were called but without price spike ($150/MWh) occurring 31 6 Days with at least 1 price spike of $150/MWh Most of the utility price responsive DR programs are currently designed to be called a full day ahead of when the load reductions are needed. The existing programs therefore do not have real time hourly prices as a trigger. They are triggered by other market indicators such as heat rates and forecasted temperature. According to SCE, price spikes occur with 2.5 minutenotice, and that any resource that could be used to mitigate price spikes would have to be 140 For a more complete chart, see Appendix Q. 73

78 IV. already bid into CAISO s market awaiting CAISO dispatch instructions 141. DR programs are currently not bid into CAISO s market. To the extent that DR programs were triggered when price spikes occurred, it is outside the scope of this report to quantify the impact of DR programs on those price spikes. The quantification of those impacts would require some method of modeling what the prices would have been but for the load impacts of the DR programs. In theory, DR should have had some impact on prices given that DR events overlapped price spike days on a few occasions. Demand response on those days, in theory, probably had some downward impact on the equilibrium price (i.e. mitigating the price spikes). Conclusion DR programs are not able to address real time price spikes because of their current design, and because the programs are not yet bid into CAISO markets. The Utilities should design new DR programs that enable them to mitigate real time price spikes in anticipation that these programs will be bid into CAISO markets. 141 A , SCE Exhibit 1, pages

79 Chapter 8: Coordination with the CAISO I. Staff Recommendations Because the Utilities current DR programs are not integrated into the CAISO wholesale energy market, there is no market mechanism to inform the CAISO how much DR capacity exists in the system on daily and hourly basis. Such information is important for the CAISO s operational consideration. The utilities Weekly and Daily DR reports developed in summer 2012 are a valuable alternative to make their DR resource more visible to the CAISO. Staff appreciates the Utilities efforts in the development and submission of the Daily and Weekly DR reports. Staff agrees with the CAISO that all three utilities should submit the Daily and Weekly DR reports in summers 2013 and The utilities (including PG&E 142 ) DR reporting requirements for is summarized in Appendix R. II. DR Reporting Requirements in Summer 2012 As discussed above, prior to the summer 2012, under the oversight of the Governor s Office, the Commission worked closely and intensively with the CAISO, the CEC, and the Utilities on the contingency planning to mitigate the potential affects from the SONGS outage and ensure system reliability throughout the summer. One of the initial steps was to identify the Utilities DR resources available to address the five different types of system contingencies such as transmission, voltage collapse, generation deficiency, etc., which is referred as the mapping of the DR programs. The next step was to develop a mechanism to inform the CAISO how much Day Ahead and Day of DR capacity is available on a daily and hourly basis. Unlike other generation resources, currently, DR is not integrated in the CAISO s wholesale energy market. Under the CAISO s DR Resource User Guide, 143 the Utilities are required to only submit the forecast and results for the triggered DR programs. Therefore, if no DR program is triggered, the CAISO is blind to how much DR capacity exists in the system. With an exception of the Emergency Program, the DR programs are dispatched by the utilities, not the CAISO. This operation as well as the reporting requirements as set in the CAISO s guide since 2007 had not presented any problem in the past when the system had sufficient resources. However, in light of the SONGS outage, CAISO emphasized the importance of a daily communication on the Utilities DR programs so the CAISO s grid operator could request the Utilities to dispatch their DR programs if and when they are needed. Working cooperatively with CAISO and the Commission staff, the Utilities developed and submitted the Daily DR reports from June 1, 2012 to October 31, The Utilities continued to submit the results of the DR events seven days after each event (referred as the 7 Day Report ) consistent with the 142 As staff guidance only because PG&E is not subject to this proceeding. 143 DRAFT Version 1.0, August 30,

80 CAISO s guidance. Staff provided to the Governor s Office the data from the Daily and the 7 Day reports in weekly briefings during the summer III. DR Reporting Requirements for In its DR application, SCE proposed to eliminate the Weekly and Daily DR reporting requirements because it did not find these reports provided value for SCE. SCE recommends transition back to the 2007 CAISO User Guide but suggests that the CAISO should update and publish for all DR Providers. 144 In its protest to SCE s application, the CAISO objects SCE s proposal and requests that the Utilities resume the Daily DR reports after the winter season ends. The CAISO contends that (t)he underlying purpose of the date forecasting and publication was to benefit the system operator rather than the IOUs themselves. The ISO finds good value in the daily demand response reports. Because the report mechanism, the ISO is no longer blind to how much DR capability exists in the system in a daily and hourly basis, if and when it is needed. 145 Staff finds that these reports not only have value to the CAISO, but also to the Commission. Through the Daily and 7 Day reports, staff was able to monitor and provide timely DR status to the Governor s Office throughout the summer. There were a number of lessons learned leading the development of the comprehensive questions on the DR performance. Therefore, staff recommends the continuation of all of the DR reports submitted in 2012 for as summarized in Appendix R. 144 A , SCE 1, at p A , CAISO s Comments filed on January 18,

81 Appendix A: Highlight of 2012 Summer Weather & Load Conditions 146 Date Max Temp Max RA Temp DR Ex Post Peak Load ( F) ( F) Load Impact (MW) (MW) 8/10/ ,282 8/13/ ,428 9/14/ ,799 10/1/ N/A 80 21,355 10/17/ ,609 SCE Date Max Temp ( F) SDG&E Max RA Temp ( F) Ex Post Load Impact (MW) Peak Load (MW) 8/13/ ,266 8/17/ ,266 9/14/ ,592 9/15/ ,313 10/2/ , Include event days with top three highest temperatures and peak load. 77

82 Appendix B: Energy Division November 16, 2012 Letter Provided in a separate PDF file 78

83 012 RA Appendix C: Descriptions of DR Load Impact Estimates The 2012 Resource Adequacy (RA) load is a monthly forecast estimate of the load reduction attributed to individual DR programs under a 1 in 2 weather year condition. This value is utilized in load resource planning and it is based on a year ahead forecasted customer enrollment. SCE s Methodology In SCE s A March 4 th Response To ALJ s February 21, 2013 Ruling Requesting Applicants To Provide Additional Information, 2012 RA MW is based on SCE s ex ante load impact results under a 1 in 2 weather year condition, portfolio level, and average hourly impacts from 1pm to 6pm in May Oct. and from 4pm to 9pm in Nov. Apr. The PTR, Residential and Commercial Summer Discount Plan (AC Cycling) methodologies are outlined by the following steps: 1. Defining data sources 2. Estimating ex ante regressions and simulating reference loads by customer and scenario 3. Calculating percentage load impacts from ex post results 4. Applying percentage load impacts to the reference loads; and 5. Scaling the reference loads using enrollment forecasts 147 Summer Discount Plan (AC Cycling) & Peak Time Rebate (PTR) 2012 SCE Resource Adequacy Protocols Program Details 148 Time of Day (hour) Day of week Variables for Monday and Friday Month Cooling degrees Heating degrees SDG&E s Methodology The 2012 Resource Adequacy MW is based on SDG&E s ex ante load impact results under a 1 in 2 weather year condition, portfolio level, and average hourly impacts from 1pm to 6pm in May Oct. and from 4pm to 9pm in Nov. Apr. The forecast is calculated in accordance with the load impact protocols 149. The forecast is calculated by multiplying (1) historical load impact per participant as a function of weather and (2) SDG&E s forecast of the number of participants per program. Load Impact Per Participant Details of RA protocols obtained from SCE DRAFT 2012 Ex Post Ex Ante Load Impact for SCEs PTR pg Details of RA protocols obtained from SCE DRAFT 2012 Ex Post Ex Ante Load Impact for SCEs SDP D Detailed information on RA protocols obtained from San Diego Gas & Electric Company Response to Administrative Law Judge s Ruling Requesting Applicants to Provide Additional Information pg. 14 and communication with Kathryn Smith, SDG&E. 79

84 The first step in the process is the development of a regression model. The model used in the analysis includes the following input variables: temperature, day of week, month, and participant loads prior to the DR event (i.e. participant loads at 10 a.m.). A 1 in 2 weather year condition was used as an input variable in the regression model and it represents the monthly peak day temperature for an average year. SDG&E utilized historical weather data to calculate monthly system peak temperatures. In the event that DR program enrollment, baselines, or the number of DR events changed significantly, data from prior years was utilized. Regression variable coefficients in the 2011 Ex Post model were utilized for the 2012 RA forecast model. After the impact per participant regression model is developed, the model is re run with average monthly peak temperature values. The output is the historical load impact per participant as a function of weather. SDG&E s Forecast of the Number of Participants per Program The forecasted number of participants per DR program is obtained by examining historical trends and program designed change SDG&E Resource Adequacy Protocols Program Details 151 ACSAVER BIP A CBP DA/DO CPP D CPP E 1 in 2 weather data for monthly system peak day Enrollment estimates by customer type (residential and commercial) and by cycling option (Res 50%, 100% cycling; Com 30%, 50% cycling). Time of Day, Day of Week, Month, Temperature (shape and trend variables (and interaction terms) designed to track variation in load across days of the week and hours of the day). Forecasted load in the absence of a DR event (i.e. the reference load) Participant s Firm Service Level Estimates of over or under performance TOU period variables (binary variables representing when the underlying TOU rates changed during the day and season) Simulated per customer reference loads under 1 in 2 weather year condition and event type scenarios (e.g., typical event, or monthly system peak day) Estimates of reference loads and percentage load impacts, on a per enrolled customer basis, based on modified versions of the ex post load impact regressions. Estimated percentage load impacts combined with program enrollment forecasts from SDG&E to develop alternative forecasts of aggregate load impacts. Forecasts were developed at the program and program type (e.g., DA and DO) level. Load impacts for existing CPP D customers were prepared for based on per customer reference loads and load impact estimates from the ex post evaluation, and enrollment forecasts. The enrollment forecast for CPP D is calculated using opt out rates by NAICS Forecast is based on prior event data and accounts for temp. & customer growth 151 Details of RA protocols obtained from Executive Summary of the 2011 SDG&E Measurement and Evaluation Load Impact Reports 80

85 PTR Com & Res There are five major assumptions required to compute the expected PTR load reduction from residential customers. 1) The meter deployment rate, 2) the rebate price, 3) the participation rates, 4) the average load, and 5) the elasticity which determine the percent impact per customer when combined with the prices. Average load is based upon SDG&E s load research and daily load profile data. Average daily energy use per hour in the peak and off peak periods Elasticity of substitution between peak and off peak energy use Average price during the peak and off peak pricing periods Change in elasticity of substitution due to weather sensitivity Average cooling degrees per hour during the peak period. Change in elasticity of substitution due to the presence of central air conditioning 2012 Adjusted RA The DR load impact for 2012 Adjusted RA is a monthly estimate of the expected load reduction attributed to individual DR programs that accounts for current customer enrollment. This value is utilized in load resource planning. SCE s Methodology Adjusted RA is calculated by taking the 2012 RA value and dividing by the 2012 RA enrollment to get the average RA load impact per customer. The average RA load impact per customer is multiplied by the number of ex post customers that were dispatched. The adjusted RA value accounts for the difference between the number of customers forecasted for RA and the number of customers actually enrolled during the ex post events; i.e. the adjusted RA represents what RA would have been if SCE had had perfect knowledge of enrollment for 2012 SDG&E s Methodology The adjusted 2012 RA load forecast is obtained by multiplying the 2012 RA impact per customer by the number of current enrolled customers. SDG&E did not adjust its 2012 RA load forecast for weather or other variables. DR Daily Forecast and CAISO s 7 Day Report The daily forecast is intended to provide an estimate of the expected hourly load reduction per DR program during an event period. The CAISO s 7 day Reports provide load reduction data that is calculated and reported to the CAISO seven days after a DR event. SCE s Methodology AC Cycling SCE s daily forecast for the Summer Discount Plan is calculated using an algorithm derived from a 1985 AC cycling load reduction analysis report. The algorithm is a linear equation: MW Reduction = [a + b x (T x k)] x t 81

86 Where: T = Temperature forecasted for the following business day in Covina, CA t = Air conditioner tonnage available for cycling k = Temperature adjustment factor a = Constant adjustment factor b = Slope adjustment factor When the temperature in Covina is below 70 degrees, the assumption is that no AC Cycling DR is available and thus no forecast is made. Specific values for a, b, and k are disclosed in a 1986 SCE internal memo for 4 SCE service area weather zones and for the 50% and 100% cycling strategies. 152 Adjustments are made to the algorithm based on air conditioner tonnage available for cycling. This particular algorithm is only valid for event day temperatures between 90 and 116 degrees. As of this draft, the 1985 AC cycling load reduction analysis report has not been provided to ED staff. Consequently ED staff has not been able to examine the specific slope, constant, and temperature adjustment values. SCE used a modification of this algorithm to accommodate the hourly forecasts requested by the CAISO prior to August 28, The modified methodology uses the program load reduction estimates using a temperature input of 100 degrees that is scaled based on actual temperatures below 100 degrees. Towards the end of the summer, the legacy algorithm was built into a system where the temperatures could be applied by hour across the different zones requested by the CAISO. SCE s 7 day report for the Summer Discount Plan is calculated using the AC cycling load reduction algorithm with a temperature input based on actual temperatures in Covina CA. When the temperature in Covina CA is below 70 degrees, the assumption is that no AC Cycling DR is available. Adjustments are made based on enrollment and temperature. SDG&E s 7 day results reports for the AC Saver program are calculated using a one or two day baseline with adjustments based on same day or historical days with the most similar weather conditions to the event day. The 7 day report results provided to the CAISO are hourly but the event day results average results from 1p.m. 6 p.m. for events including those hours and the average results over the event period for events not including all of the hours 1p.m. 6p.m. Peak Time Rebate SCE s daily forecast and 7 day report for the Save Power Day peak time rebate program is calculated by multiplying the population of residential customers actively enrolled in Save Power Day event notification by a forecasted average load drop of kw per participant. SDG&E s methods for developing the daily forecast and 7 day report for the residential peak time rebate program are the same as those described above for the AC Cycling program. DR Contracts SCE s daily forecast and 7 day report for DR Contracts program are calculated as the current month's contract capacity with no adjustments are made for enrollment, temperature, or other factors. 152 See Appendix S. 82

87 Daily Forecast SDG&E s Methodology The daily forecast is calculated in two steps. The first step is the creation of a regression model that predicts the entire load of participating customers. Model input variables include temperature, day of week and month. Temperature inputs utilized in the regression model are the monthly peak temperatures from the prior year. In some instances, the load forecast may be scaled up or down according to the number of currently enrolled participants and their impact on on peak load. In some instances, if large customers leave a program, the load forecast regression is re run with participants that are still enrolled in the program. The second step in the process is to multiply the estimated load of participating customers by a fixed percentage load reduction that is based upon ex post results from the previous year. CAISO s 7 day Report Load reductions detailed in CAISO s 7 day Report are calculated by subtracting an estimated baseline from the measured load during DR event hours. SDG&E utilizes 10 working days prior to an event to calculate an estimated baseline for its CPP, CBP, CPP E, and BIP programs. For its residential programs, SDG&E utilizes 1 to 2 days to calculate its estimated baseline. The exception is that if the PTR event occurs on a Monday, then data from the prior work week (excluding event days) is used. As of this draft, Energy Division staff has not inspected SDG&E s regression model, model inputs, or cases where comparisons and judgment were applied to scale forecasts up or down. Ex Post Results and Settlement Data Ex Post Results Ex post result is the measurement of MW delivered using Regression methods. Regression methods use an entire season s data and data across multiple events to improve on the accuracy of impact estimates. It relies on historical information about customer loads and focuses on understanding the relationship between load, or load impacts, during hours of interest and other predictor variables (i.e., temperature, population characteristics, resource effects, and observed loads in the hours preceding the DR event). Whenever ex ante estimation is required, regression analysis is generally the preferred method because it can incorporate the impact of a wide variety of key drivers of DR. DR load Impact estimates are determined directly from the regression modal. Decision adopts protocols for estimating the impact of DR activities for resource planning. The purpose of the ex post results is to inform DR Resource Planning and Program Design Settlement Data Day matching is the primary approach used to calculate customer settlement for DR options involving large Commercial and Industrial customers. Settlements refer to the methods of paying customers for participating in DR program and it is an important component of DR program design and implementation. Because of the need to produce estimates in a short time frame after an event for prompt payments, this limits the amount of data collected. Forecasting future impacts of DR events is limited because Day 83

88 matching do not collect data on influential variables (i.e., weather conditions, seasonal factors, customer population characteristics) that would cause impacts for vary in the future. SCE Methodology Load impact is calculated as the difference between the reference load (baseline) and the observed load (usage). The purpose of the settlement data is to calculate payment to customers. 84

89 Month Appendix D: SCE 2012 Monthly Average DR Program Load Impact (MW) RA (1) with RA Measurement Hours (1 6 p.m.) 2012 Adjusted RA Enrollment (2) Enrollment & Weather (3) Daily Forecast 7 Day Report Year End Ex Post Monthly Nominated Programs Capacity Bidding Program (Day Ahead) June 1.19 No Events N/A No Events No Events No Events No Events July N/A August 1.27 No Events N/A No Events No Events No Events No Events September 1.23 No Events N/A No Events No Events No Events No Events October N/A Capacity Bidding Program (Day Of) June No Events N/A No Events No Events No Events No Events July N/A August N/A September N/A October N/A Demand Bidding Program June No Events N/A No Events No Events No Events No Events July N/A August N/A September No Events N/A No Events No Events No Events No Events October N/A Demand Response Contracts (Day Ahead & Day Of) June No Events N/A No Events No Events No Events No Events July No Events N/A No Events No Events No Events No Events August N/A September No Events N/A No Events No Events No Events No Events October N/A Other Price Responsive Programs Save Power Days / Peak Time Rebates June No Events N/A No Events No Events No Events No Events July N/A N/A N/A August N/A N/A September N/A October No Events N/A No Events No Events No Events No Events 153 SCE 03, Table 1. 85

90 Month Appendix D: SCE 2012 Monthly Average DR Program Load Impact (MW) (Cont.) with RA Measurement Hours (1 6 p.m.) 2012 RA (1) 2012 Adjusted RA Enrollment (2) Enrollment & Weather (3) Daily Forecast 7 Day Report Year End Ex Post Summer Advantage Incentive Program / Critical Peak Pricing (CPP) June N/A July N/A August N/A September N/A October No Events N/A No Events No Events No Events No Events Summer Discount Plan (Residential) June N/A July N/A August N/A September N/A October 0.00 N/A N/A Emergency Programs Summer Discount Plan (Commercial) June No Events N/A No Events No Events No Events No Events July No Events N/A No Events No Events No Events No Events August N/A September No Events N/A No Events No Events No Events No Events October 0.00 N/A N/A No Events No Events No Events No Events Agriculture Pumping Interruptible June No Events N/A No Events No Events No Events No Events July No Events N/A No Events No Events No Events No Events August N/A September N/A October No Events N/A No Events No Events No Events No Events Base Interruptible Program June No Events N/A No Events No Events No Events No Events July No Events N/A No Events No Events No Events No Events August No Events N/A No Events No Events No Events No Events September N/A

91 Event Date Appendix E: SCE 2012 DR Program Load Impact by Event (MW) Daily Average by Event Hours Daily Forecast 7 Day Report Year End Ex Post Monthly Nominated Programs Capacity Bidding Program (Day Ahead) 7/23/ /24/ /25/ /30/ /31/ /1/ /2/ /3/ /5/ /17/ /18/ /29/ Capacity Bidding Program (Day Of) 7/20/ /7/ /13/ /14/ /14/ /2/ /18/ Demand Bidding Program 7/12/ /8/ /10/ /14/ /16/ /29/ /1/ /17/ Demand Response Contracts (Day Ahead & Day Of) 8/14/ /2/

92 Appendix E: SCE 2012 DR Program Load Impact by Event (MW) (Cont.) Daily Average by Event Hours Event Date Daily Forecast 7 Day Report Year End Ex Post Other Price Responsive Programs Save Power Days / Peak Time Rebates 7/12/2012 N/A /10/2012 N/A /16/2012 N/A /29/2012 N/A /31/2012 N/A /7/ /10/ Summer Advantage Incentive Program / Critical Peak Pricing (CPP) 6/29/ /12/ /23/ /7/ /9/ /13/ /20/ /27/ /29/ /10/ /20/ /28/ Summer Discount Plan (Residential) 6/20/2012 Group /29/2012 Group /29/2012 Group /10/2012 Group /10/2012 Group /10/2012 Group /1/2012 Group /1/2012 Group /1/2012 Group /3/2012 Group /3/2012 Group /3/2012 Group /8/2012 Group /8/2012 Group /8/2012 Group

93 Appendix E: SCE 2012 DR Program Load Impact by Event (MW) (Cont.) Daily Average by Event Hours Event Date Daily Forecast 7 Day Report Year End Ex Post Other Price Responsive Programs Summer Discount Plan (Residential) (cont.) 8/9/2012 Group /9/2012 Group /9/2012 Group /14/2012 Group /14/2012 Reliability /15/2012 Group /15/2012 Group /15/2012 Group /17/2012 Group /17/2012 Group /21/2012 Group /21/2012 Group /21/2012 Group /22/2012 Group /22/2012 Group /22/2012 Group /28/2012 Group /28/2012 Group /28/2012 Group /29/2012 Group /29/2012 Group /29/2012 Group /10/2012 Group /10/2012 Group /10/2012 Group /14/2012 Group 1 9/14/2012 Group /14/2012 Group 3 9/14/2012 Group /14/2012 Group 5 9/14/2012 Group /20/2012 Group 1 9/20/2012 Group /20/2012 Group 3 9/20/2012 Group /20/2012 Group

94 9/20/2012 Group 6 Appendix E: SCE 2012 DR Program Load Impact by Event (MW) (Cont.) Daily Average by Event Hours Event Date Daily Forecast 7 Day Report Year End Ex Post Other Price Responsive Programs Summer Discount Plan (Residential) (cont.) 9/21/2012 Group /21/2012 Group /21/2012 Group /28/2012 Group 1 9/28/2012 Group /28/2012 Group 3 9/28/2012 Group /28/2012 Group 5 9/28/2012 Group /2/2012 Group /2/2012 Group /17/2012 Group /17/2012 Group /17/2012 Group /18/2012 Group N/A 10/18/2012 Group N/A 10/26/2012 Group N/A 10/26/2012 Group N/A 10/26/2012 Group N/A Emergency Programs Summer Discount Plan (Commercial) 8/14/ Agriculture Pumping Interruptible 8/14/ /26/ Base Interruptible Program 9/26/

95 Appendix F: SDG&E 2012 Monthly Average DR Program Load Impact (MW) with RA Measurement Hours (1 6 p.m.) Program Month 2012 RA Enrollment 2012 Adjusted RA Enrollment & Weather Daily Forecast 7 Day Report Ex Post Settlement Emergency Programs BIP A N/A N/A N/A N/A N/A BIP A N/A N/A N/A N/A N/A BIP A N/A N/A N/A N/A N/A BIP A N/A N/A BIP A N/A N/A N/A N/A N/A Monthly Nominated CBP DA N/A N/A N/A N/A N/A CBP DA N/A N/A N/A N/A N/A CBP DA N/A CBP DA N/A CBP DA N/A CBP DO N/A N/A N/A N/A N/A CBP DO N/A N/A N/A N/A N/A CBP DO N/A CBP DO N/A CBP DO N/A Price Responsive ACSAVER N/A N/A N/A N/A N/A ACSAVER N/A N/A N/A N/A N/A ACSAVER N/A N/A ACSAVER N/A N/A ACSAVER N/A N/A CPP N/A N/A N/A N/A N/A CPP N/A N/A N/A N/A N/A CPP N/A N/A CPP N/A N/A CPP N/A N/A DBP 6 N/A N/A N/A N/A N/A N/A N/A DBP 7 N/A N/A N/A N/A N/A N/A N/A DBP 8 N/A N/A N/A DBP 9 N/A N/A N/A DBP 10 N/A N/A N/A PTR Com 6 N/A N/A N/A N/A N/A N/A N/A PTR Com 7 N/A N/A N/A PTR Com 8 N/A N/A N/A PTR Com 9 N/A N/A N/A PTR Com 10 N/A N/A N/A N/A N/A N/A N/A PTR Res N/A N/A N/A N/A N/A PTR Res N/A PTR Res N/A PTR Res N/A PTR Res N/A N/A N/A N/A

96 Appendix G: SDG&E 2012 DR Program Load Impact by Event (MW) Daily Average by Event Hours Program Event Date Daily Forecast 7 Day Report Ex Post Settlement Emergency Programs BIP A 9/14/ N/A CPPE 8/13/ N/A CPPE 9/14/ N/A Monthly Nominated CBP DA 8/9/ CBP DA 8/10/ CBP DA 8/14/ CBP DA 9/14/ CBP DA 9/17/ CBP DA 10/1/ CBP DA 10/2/ CBP DO 8/8/ CBP DO 8/13/ CBP DO 9/13/ CBP DO 9/14/ CBP DO 10/1/ Price Responsive ACSAVER 8/8/ N/A ACSAVER 8/10/ N/A ACSAVER 8/13/ N/A ACSAVER 8/17/ N/A ACSAVER 9/13/ N/A ACSAVER 9/14/ N/A ACSAVER 9/15/ N/A ACSAVER 10/1/ N/A CPP 8/9/ N/A CPP 8/11/ N/A CPP 8/14/ N/A CPP 8/21/ N/A CPP 8/30/ N/A CPP 9/15/ N/A CPP 10/2/ N/A PTR Com 7/20/ PTR Com 8/9/ PTR Com 8/10/ PTR Com 8/11/ PTR Com 8/14/ PTR Com 8/21/ PTR Com 9/15/ PTR Res 7/20/ PTR Res 8/9/ PTR Res 8/10/ PTR Res 8/11/ PTR Res 8/14/ PTR Res 8/21/ PTR Res 9/15/

97 Appendix H: SCE 2012 DR Program Overview Program Type Program Season Available Annual Events/Hours Available Monthly Events/Hours Available Weekly Events/Hours Available Daily Events/Hours # of Events Triggered/ # of Hours Available Remaining Available Trigger Criteria 2012 Trigger Condition Agricultural Pumping Interruptible (API) Day Of Year Round (excluding Holidays) 150 Hours 25 Events 4 Events 1 Event 6 Hours Max 2 Events 7.1 Hours 143 Hours CAISO Stage 1 Alert CAISO Stage 2 Alert SCE Grid Control Center Discretion Measurement & Evaluation System Emergency (San Joaquin Valley) Measurement & Evaluation Base Interruptible Program (BIP) Day Of Year Round (excluding Holidays) 180 Hours 10 Events No Limit 1 Event 6 Hours Max 1 Event 2 Hours 178 Hours CAISO Stage 1 Alert CAISO Stage 2 Alert SCE Grid Control Center Discretion Measurement & Evaluation Measurement & Evaluation Capacity Bidding Program Day Ahead May Oct (excluding Holidays) No Limit 24 Hours Mon Fri 1 Event 8 Hours (11am 7pm) 12 Events July 17 Hrs Oct 22 Hrs May 24 Hrs June 24 Hrs July 7 Hrs Aug 24 Hrs Sep 24 Hrs Oct 2 Hrs High temperature Resource limitations A generating unit outage Transmission constraints CAISO Alert or Warning SCE System Emergency Measurement & Evaluation Heat Rate 93

98 Appendix M (Cont.) SCE 2012 DR Program Overview (Cont.) Program Type Program Season Available Annual Events/Hours Available Monthly Events/Hours Available Weekly Events/Hours Available Daily Events/Hours # of Events Triggered/ # of Hours Available Remaining Available Trigger Criteria 2012 Trigger Condition Capacity Bidding Program Demand Bidding Program DR Contracts Day Of Day Ahead Day Ahead May Oct (excluding Holidays) Year Round (excluding Holidays) Varies DR Contracts Day Of Varies No Limit 24 Hours No Limit No Limit Varies by Contract Varies by Contract No Varies by Contract Varies by Contract No Limit Mon Fri Varies by Contract Varies by Contract 1 Event 4,6, or 8 hour event duration options 1 Event 8 hours Varies by Contract Varies by Contract 7 Events July 3 Hrs Aug 12 Hrs Sept 6 Hrs Oct 10 Hrs 8 Events 64 Hours 1 Event 2 Hours 2 Events 5 Hours May 24 Hrs Jun 24 Hrs Jul 21 Hrs Aug 12 Hrs Sep 18 Hrs Oct 14 Hrs No Limit Varies by Contract Varies by Contract High temperature Resource limitations A generating unit outage Transmission constraints CAISO Alert or Warning SCE System Emergency Measurement & Evaluation CAISO Alert or Warning Day Ahead load and/or Price Forecast Extreme or unusual temperature conditions SCE Procurement needs Measurement & Evaluation Varies by Contract Varies by Contract Heat Rate Heat Rate Peak Load Forecast Energy Prices Peak Load Forecast 94

99 Appendix M (Cont.) SCE 2012 DR Program Overview (cont.) Program Save Power Day Summer Advantage Incentive Summer Discount Plan Residential Summer Discount Plan Commercial Type Day Ahead Day Of Day Of Day Of Program Season Year Round (excluding Holidays) June Sep (excluding Holidays) Year Round (excluding Holidays) Year Round (excluding Holidays) Available Annual Events/Hour s Available Monthly Events/Hour s Available Weekly Events/Hour s No Limit No Limit No Limit 60 Hours Min: 9 Events Max: 15 Events Unlimited Events 180 Hours Base 90 Hours Enhanced Unlimited No Limit No Limit No Limit No Limit Available Daily Events/Hour s 1 Event 4 Hours (2pm 6pm) 1 Event 4 Hours (2pm 6pm) Unlimited Events 6 Hours No Limit No Limit 6 Hours # of Events Triggered/ # of Hours 7 Events 28 Hours 12 Events 48 Hours 23 Events 24 Hours 1 Event 5.6 Hours Available Remaining No Limit 3 Events 156 Hours No Limit Available Trigger Criteria Temperature Temperature CAISO Alert or Warning SCE System Forecast Extreme or unusual temperature conditions Day Ahead load and/or Price Forecast CAISO Alert or Warning CAISO Discretion SCE Grid Control Center Discretion SCE Energy Operations Center Discretion Measurement & Evaluation CAISO Stage 1 Alert CAISO Stage 2 Alert SCE Grid Control Center Discretion Measurement & Evaluation 2012 Trigger Condition Temperature High Temperature Peak Load Forecast Day Ahead load and/or Price Forecast CAISO Emergency Heat Rate Measurement & Evaluation CAISO Emergency 95

100 Program Type Program Season Critical Peak Pricing Default (CPP D) Capacity Bidding Program (CBP) Capacity Bidding Program (CBP) Base Interruptibile Program (BIP) Available Annual Events/Hours Appendix I: SDG&E DR Program Overview Available Monthly Events/Hours Available Weekly Events/Hours Available Daily Events/Hours 1 Event # of Events Triggered Available Remaining Always Day Ahead Year Round 18 Events No Limit No Limit 7 Events 11 Events 7 Hours (11am 6pm) Trigger Criteria Trigger Condition May Oct 1 Event 7 Events Price: Mon Fri Up to 8 Hours Aug: 12 Hours (3 events) Aug: 32 Hours *Mon Friday only *Market Price equal Mitigate potential Day Ahead No Limit 44 Hours No Limit (11am 7pm) Sep: 8 Hours to or greater than price spikes and Sep: 36 Hours (2 events) 15,000 btu/kwh heat load forecast rate above 4000 MW Oct: 8 Hours (2 events) Oct: 36 Hours *Other Statewide or local system conditions May Oct 1 Event 5 Events Price: Day Of Mon Fri Up to 8 Hours Aug:7 Hours (2 events) Aug: 37 Hours *Mon Friday only *Market Price equal No Limit 44 Hours No Limit (11am 7pm) Sep: 8 Hours to or greater than Sep: 36 Hours (2 events) 15,000 btu/kwh heat rate Day Of 30 minute Year Round 120 Hours 10 Events Oct: 4 hours (1 event) 1 Event 1 Event Up to 4 Hours 4 Hours Oct: 40 Hours 116 Hours Temperature and system load *Monday: 86⁰; 3472 MW Met trigger criteria *Tues Fri: 84⁰; 3837 for all 7 events MW *Saturday: 86⁰; 3837 MW *Other Statewide or local system conditions CAISO forecasts a Stage 1 CAISO declares a Stage 2 CAISO calls for interruptible load Extreme weather or system demands or at SDGE discretion. Mitigate potential price spikes and load forecast abolve 4000 MW and/or Real Time Load came in higher than Day Ahead forecast 1 ComplianceTest 2 Met trigger criteria 96

101 Program Type Program Season Available Annual Events/Hours Appendix N: SDG&E DR Program Overview (Cont.) Available Monthly Events/Hours Available Weekly Events/Hours Available Daily Events/Hours # of Events Triggered May Oct 15 Events 1 Event 8 Events Holidays Excluded or Noon to 8 pm Summer Saver Day Of 120 Hours 40 Hours 3 Events Min 2/Max 4 Hours 1 Event Always Aug: 15 Hours (4 events) Sep: 10 Hours (3 events) Oct: 4 Hours (1 events) Available Remaining Aug: 25 Hours Sep: 30 Hours Trigger Criteria Temperature and system load *Monday Friday: 3800 MW *Saturday Sunday Optional Participation Oct: 36 Hours *CAISO Stage 1 or 2 Annual 91 Hours Reduce Your Use Day Ahead Year Round No Limit No Limit No Limit 7 Hours 7 Events No Limit *Local or system emergency Temperature and system load *Monday: 86⁰; 3472 MW *Tues Fri: 84⁰; 3837 MW Trigger Condition Mitigate potential price spikes and load forecast abolve 4000 MW and/or Real Time Load came in higher than Day Ahead forecast Met trigger criteria for all 7 events (11am 6pm) *Saturday: 86⁰; 3837 MW Critical Peak Day Of Pricing Emergency (CPP E) Year Round 80 Hours 40 Hours 4 Events 1 Event Terminates Dec minute Jul Dec 2 Events Aug:1 Event (5 Hours) Sep:1 Event (4 Hours) 3 Events Demand Bidding Day Ahead No Limit No Limit No Limit No Limit N/A 2012 only 14 Hours Flex Alerts in Effect 08/10/13 08/14/13 71 Hours Local utility emergency with intent to avoid any firm load curtailment CAISO calls for CAISO 1,2,or 3 Emergency Transmission or imminent system emergency or as warranted by the utility Conditions warranted by Utility Conditions warranted by Utility 97

102 DR Programs Event Limits Appendix J: SCE Historical DR Event Hours Max Event Duration Average Max Monthly Nominated Capacity Bidding Program Day Ahead (1 4) 24 Hrs./Mo 4 hrs Capacity Bidding Program Day Ahead (2 6) 24 Hrs./Mo 6 hrs Capacity Bidding Program Day Ahead (4 8) 24 Hrs./Mo 8 hrs Capacity Bidding Program Day Of (1 4) 24 Hrs./Mo 4 hrs Capacity Bidding Program Day Of (2 6) 24 Hrs./Mo 6 hrs Capacity Bidding Program Day Of (4 8) 24 Hrs./Mo 8 hrs Demand Bidding Program Unlimited 8 hrs Demand Response Contracts Day Ahead Various 4 hrs Demand Response Contracts Day Of Various 4 hrs Other Price Responsive Save Power Days / Peak Time Rebates Unlimited 4 hrs. 28 Summer Advantage Incentive / Critical Peak Pricing (CPP) 15 Events/Yr. 4 hrs Summer Discount Plan Residential & Commercial Base Summer Discount Plan Residential & Commercial Enhanced Summer Discount Plan Commercial Base Summer Discount Plan Commercial Enhanced 15 Events/ Summer Season Unlimited Events/ Summer Season 15 Events/ Summer Season Unlimited Events/ Summer Season 6 hrs./day hrs./day hrs./day 6 hrs./day 6 Summer Discount Plan Residential 180 Hours/Yr. 6 hrs./day 24 Emergency Agricultural Pumping Interruptible (API) Base Interruptible Program (BIP) 1/Day 4/Wk. 25/Mo. 1/Day 10/Mo. 6 hrs./day 40 hrs./mo 150 hrs./yr. 6 hrs./day 180 hrs./yr

103 DR Programs Event Limits 2012 Appendix K: SCE Historical Number of DR Events Average Max Monthly Nominated Programs Capacity Bidding Program Day Ahead (1 4) 24 Hrs./Mo Capacity Bidding Program Day Ahead (2 6) 24 Hrs./Mo Capacity Bidding Program Day Ahead (4 8) 24 Hrs./Mo Capacity Bidding Program Day Of (1 4) 24 Hrs./Mo Capacity Bidding Program Day Of (2 6) 24 Hrs./Mo Capacity Bidding Program Day Of (4 8) 24 Hrs./Mo Demand Bidding Program Unlimited Demand Response Contracts Day Ahead Various Demand Response Contracts Day Of Various Other Price Responsive Save Power Days / Peak Time Rebates Unlimited 7 Summer Advantage Incentive / Critical Peak 15 Events/Yr. Pricing (CPP) Summer Discount Plan Residential & Commercial Base Summer Discount Plan Residential & Commercial Enhanced Summer Discount Plan Commercial Base Summer Discount Plan Commercial Enhanced 15 Events/ Summer Season Unlimited Events/ Summer Season 15 Events/ Summer Season Unlimited Events/ Summer Season Summer Discount Plan Residential 180 Hours/Yr Emergency Programs Agricultural Pumping Interruptible (API) 1/Day, 4/Wk. 25/Mo Base Interruptible Program (BIP) 1/Day,10/Mo

104 Appendix L: Summary of SCE s Reasons for the 2012 DR Triggers DR Program Category Programs Reasons Monthly Nominated Capacity Bidding Program Demand Bidding Program DR Contracts No nomination or trigger conditions Trigger conditions plus SCE s discretion to optimize performance & minimize participant fatigue Trigger conditions Price responsive Save Power Day (PTR) SCE discretion to optimize performance & minimize participant fatigue Optimal dispatch Emergency Summer Advantage Incentive (CPP) Summer Discount Plan (SDP) Res. Agricultural Interruptible Program Transitioned to price trigger starting June Remaining hours reserved for contingencies. Local transmission contingency Base Interruptible Program No emergency, test event only 100

105 Appendix M: SDG&E Historical DR Event Hours 154 DR Programs Event Limits Average Max Monthly Nominated Programs Capacity Bidding Program Day Ahead 24 Hrs./Mo Capacity Bidding Program Day Of 24 Hrs./Mo Price Responsive Programs Peak Time Rebate Unlimited Critical Peak Pricing Default 98 Hrs. ('06 '07) 126 Hrs. ('08 '12) Demand Bidding Program Unlimited Summer Saver 120 Hrs./Yr Emergency Programs Base Interruptible Program (BIP) 120 Hrs./Yr Critical Peak Pricing Emergency 80 Hrs./Yr Source for the data: SGE 02, Attachment 1, Revised Appendix X, Tables

106 Appendix N: SDG&E Historical Number of DR Events 155 DR Programs Event Limits Average Max Monthly Nominated Programs Capacity Bidding Program Day Ahead Unlimited Capacity Bidding Program Day Of Unlimited Price Responsive Programs Peak Time Rebate Unlimited Critical Peak Pricing Default 12 ('06 '07) 18 ('08 '12) Demand Bidding Program Unlimited Summer Saver 15/Yr Emergency Programs Base Interruptible Program (BIP) 10/Mo Critical Peak Pricing Emergency Unlimited Source for data: SGE 02, Attachment 1, Revised Appendix X, Tables

107 Appendix O: Utilities Peaker Plant Total Permissible vs. Actual Service Hours SCE Owned Peaker Plants Within SONGS Affected Areas Center Barre Grapeland Mira Loma Permissible Service Hours Actual Service Hours: Sept. Dec Jan. Dec Jan. Dec Jan. Dec Jan. Dec Average % of Permitted 11% 14% 9% 16% Jan. Oct % of Permitted 42% 49% 38% 59% % of Avg. 367% 359% 420% 364% SDG&E Owned Peaker Plants Cuyamaca El Cajon Energy Center Miramar Orange Grove Permissible Service Hours N/A Actual Service Hours: Historical Average % of Permitted N/A 17% 34% N/A % of Permitted N/A 39% 96% 34% % of Historical Avg. 302% 223% 280% N/A 103

108 Appendix P: Ex Post Demand Response Load Impact on Flex Alert Days Programs 8/10/12: SCE Ex Post (MW) 3:00 4:00 p.m. 4:00 5:00 p.m. Demand Bidding Program Save Power Day/Peak Time Rebate SDG&E Subtotal Capacity Bidding Program 8 8 Summer Saver/AC Cycling (Res. & Com.) 19 PG&E Subtotal 8 27 Capacity Bidding Program Aggregator Managed Program Peak Day Pricing/Critical Peak Pricing Peak Choice 3 2 SmartAC 65 Base Interruptible Program Subtotal TOTAL /14/12: SCE Capacity Bidding Program Demand Bidding Program Demand Response Contract Summer Discount Plan/AC Cycling Res. & Com Agricultural Pumping Interruptible 14 Subtotal SDG&E Capacity Bidding Program 8 8 Critical Peak Pricing Peak Time Rebate 1 0 Demand Bidding Program 6 5 Subtotal PG&E No Events TOTAL

109 Appendix Q: CAISO Energy Price Spikes SCE Price Spikes Source: SCE 03, SCE s Response to ALJ February 21, 2013 Ruling, Appendix B (Excel Data Tables in Response, Table 9) 105

110 106

111 107

112 SDG&E Price Spikes Source: SGE 02, SDG&E s Response to the ALJ February 4, 2013 Scoping Memo, Attachment

113 109

114 110

115 Appendix R: Utilities Demand Response Reporting Requirements 158 ( ) 1. DR Weekly Forecast The utilities should continue to submit a 7 day (Monday to Sunday) 159 DR forecast (MW) to the CAISO/CPUC_ED/CEC and highlight the DR programs that they anticipate to trigger by noon every Monday. Daily Value For the DR programs that have different hourly forecast, the utilities use slightly different methods to determine the daily value as described below. If an averaging method is used, the daily value may be higher or lower than the MW in a given hour such as the peak hours in the CAISO's demand forecast. Energy Division staff uses an averaging method over the actual event hours for its reports on the historical DR events. Utility Methods for the Daily Value SCE Average over the available event hours in the tariffs, which vary from program to program. SDG&E PROGRAM PERIOD AVERAGED Day Ahead 11 a.m. 6 p.m. Day Of 1 p.m. 6 p.m. (like RA) PG&E PROGRAM PERIOD AVERAGED BIP 1:00 pm 6:00 pm PDP 2:00 pm 6:00 pm (no significant enrollment/load 12 2p) SmartRate 2:00 pm 6:00 pm SmartAC 1:00 pm 6:00 pm For AMP, CBP, DBP, and PeakChoice, the hourly forecast does not vary; therefore, PG&E will continue to submit the same hourly forecast amount for the given month. 2. Daily DR Reporting to the CAISO (by 8 a.m. weekdays & weekends) For the non summer months (January 1 to April 30 and November 1 to December 31), the utilities should submit their Daily DR Reporting to the CAISO/CPUC_ED/CEC only when they intend to trigger a DR program for that day. In the submission , please identify the triggered DR program(s). If there is no DR event, the utilities do not need to submit this report. For the summer months (May 1 to October 31), the utilities should submit their Daily DR Reporting to the CAISO/CPUC_ED/CEC on a daily basis as they did in This report is based on a common template developed by the CAISO and in Excel spreadsheet. In this report, the utilities provide the scheduled as of 8 a.m. and available MW for the day and next day for all of their DR event based programs (including Day Ahead and Day of) on an aggregated basis. SCE also has added the MW by each DR program. SDG&E only added the MW for the DR program(s) triggered for the day or the next day. 158 For SCE and SDG&E. Staff guidance only for PG&E because it is subject to this proceeding (A et al.). However, staff includes the reporting requirements for PG&E as a guidance consistent with what are required for SCE and SDG&E. 159 Change from SCE and PG&E current days from Tuesday Monday to Monday Sunday. 111

116 3. Updated Reporting to the CAISO/CPUC_ED/CEC (by COB weekdays for DR events called after 8 a.m.) PG&E: PG&E continues to send the DR forecast for all of the Day Ahead and Day Of events triggered to the CAISO and CPUC throughout the day as it used to do prior to summer 2012 in Excel spreadsheet. These reports provide the forecasted MW for each DR program. SCE: SCE sends a revised Daily DR Report to include the Day Of events called after 8 a.m. and the forecasted MW by program at the end of the event day. In the submission , please identify the triggered DR program(s). SDG&E: SDG&E also sends a revised Daily DR Report to include the all DR events called after 8 a.m. and the forecasted MW by program at the end of the event day. 4. Reports on DR Results to the CAISO/CPUC_ED/CEC (Seven Days After the Events) All three utilities should continue to provide the DR results in Excel spreadsheet seven days after each DR event (CAISO 7 Day Report). The 7 Day Report should also include the DR results to date in each year. 160 The utilities should submit the DR Weekly DR Forecasts (No.1) to the following s: Entity/Individual Address CAISO John Goodin [email protected] CPUC Bruce Kaneshiro CPUC Scarlett Liang Uejio CPUC Dorris Chow CPUC Paula Gruendling [email protected] scarlett.liang [email protected] [email protected] [email protected] CEC Margaret Sheridan [email protected] The utilities should submit the Daily DR Reports, revisions, and Results (No.2 No.4) to the following s: Entity/Individual Address CAISO Shift Supervisors [email protected] CAISO Market Operations CAISO John Goodin CAISO Glen Perez CAISO Market Monitoring Keith Collins CPUC Scarlett Liang Uejio CPUC Bruce Kaneshiro CPUC Dorris Chow CPUC Paula Gruendling CEC Margaret Sheridan [email protected] [email protected] [email protected] [email protected] scarlett.liang [email protected] [email protected] [email protected] [email protected] [email protected] 160 See SCE s Day Reports as an example. 112

117 Appendix S: Additional Information Provided in separate PDF files 113