2010 Load Impact Evaluation of California Statewide Demand Bidding Programs (DBP) for Non-Residential Customers: Ex Post and Ex Ante Report

Transcription

1 2010 Load Impac Evaluaion of California Saewide Demand Bidding Programs (DBP) for Non-Residenial Cusomers: Ex Pos and Ex Ane Repor CALMAC Sudy ID SCE Seven D. Braihwai Daniel G. Hansen Jess D. Reaser March 29, 2011 Chrisensen Associaes Energy Consuling, LLC 800 Universiy Bay Drive, Suie 400 Madison, WI Voice Fax

2 Table of Conens Absrac... 1 Execuive Summary... 3 ES.1 Resources covered... 3 DBP Program... 3 Enrollmen... 3 Bidding Behavior... 4 ES.2 Evaluaion Mehodology... 5 ES.3 Ex Pos Load Impacs... 5 ES.4 TA/TI and AuoDR Effecs... 6 ES.5 Ex Ane Load Impacs... 7 ES.6 Summary Inroducion and Purpose of he Sudy Descripion of Resources Covered in he Sudy Program Descripions PG&E s DBP Program SCE s DBP Program SDG&E s DBP Program Paricipan Characerisics Developmen of Cusomer Groups Program Paricipans by Type Even Days Sudy Mehodology Overview Descripion of mehods Regression Model Developmen of Uncerainy-Adjused Load Impacs Deailed Sudy Findings PG&E Load Impacs Average Hourly Load Impacs by Indusry Group and LCA Hourly Load Impacs Comparison of PGE's Load Impacs o he 2009 Program Year SCE Load Impacs Average Hourly Load Impacs by Indusry Group and LCA Hourly Load Impacs Comparison of SCE's Load Impacs o he 2009 Program Year Effec of TA/TI and AuoDR on Load Impacs PG&E SCE Ex Ane Load Impac Forecas Ex Ane Load Impac Requiremens Descripion of Mehods Developmen of Cusomer Groups Developmen of Reference Loads and Load Impacs Enrollmen Forecass Reference Loads and Load Impacs i CA Energy Consuling

3 5.4.1 PG&E SCE Validiy Assessmen Recommendaions Appendices ii CA Energy Consuling

4 Tables Table ES.1: 2010 Toal and Incremenal Load Impacs from TA/TI and AuoDR... 7 Table 2.1: DBP Enrollees by Indusry group PG&E Table 2.2: DBP Enrollees by Indusry group SCE Table 2.3: DBP Enrollees by Local Capaciy Area PG&E Table 2.4: DBP Enrollees by Local Capaciy Area SCE Table 2.5: DBP Bidding Behavior PG&E Table 2.6: DBP Bidding Behavior SCE Table 2.7: DBP Evens Table 4.1: 2010 Average Hourly Load Impacs PG&E DBP, by Indusry Group Table 4.2: 2010 Average Hourly Load Impacs PG&E DBP, by LCA Table 4.3: DBP Hourly Load Impacs for Augus 25, 2010 Even Day PG&E Table 4.4: 2010 Average Hourly Load Impacs by Even, SCE Table 4.5: 2010 Average Hourly Bid Realizaion Raes by Even, SCE Table 4.6: 2010 Average Hourly Load Impacs SCE DBP, by Indusry Group Table 4.7: 2010 Average Hourly Load Impacs SCE DBP, by LCA Table 4.8: 2010 DBP Hourly Load Impacs for Average Even Day, SCE Table 4.9: Average Hourly Load Impacs by Even, PG&E TA/TI Table 4.10: Number of Service Accouns and Average Reference Load, PG&E TA/TI Table 4.11: Average Load Impacs in Levels and Percenages, PG&E TA/TI Table 4.12: Incremenal Load Impac Calculaion, PG&E TA/TI Table 4.13: Average Hourly Load Impacs by Even, PG&E AuoDR Table 4.14: Number of Service Accouns and Average Reference Load, PG&E AuoDR Table 4.15: Average Load Impacs in Levels and Percenages, PG&E AuoDR Table 4.16: Incremenal Load Impac Calculaion, PG&E AuoDR Table 4.17: Average Hourly TA/TI Load Impacs by Even, SCE TA/TI Table 4.18: Incremenal TA/TI Load Impacs by Indusry Group, SCE TA/TI Table 4.19: Average Hourly AuoDR Load Impacs by Even, SCE AuoDR Table 4.20: Number of Service Accouns and Average Reference Load, SCE AuoDR Table 4.21: Average Load Impacs in Levels and Percenages, SCE AuoDR Table 4.22: Incremenal Load Impac Calculaion, SCE AuoDR Table 5.1: Hourly Percenage Load Impacs, PG&E Cusomers no dually enrolled in BIP, Summer Monhs Table 5.2: Hourly Percenage Load Impacs, PG&E Cusomers no dually enrolled in BIP, Nonsummer Monhs Table 5.3: Hourly Percenage Load Impacs, PG&E Cusomers dually enrolled in BIP, Summer Monhs Table 5.4: Hourly Percenage Load Impacs, PG&E Cusomers dually enrolled in BIP, Nonsummer Monhs Table 5.5: Hourly Percenage Load Impacs, All SCE DBP Cusomers, Summer Monhs Table 5.6: Hourly Percenage Load Impacs, All SCE DBP Cusomers, Non-summer Monhs.. 46 Table 5.7: Hourly Percenage Load Impacs, SCE DBP Cusomers no in BIP, Summer Monhs Table 5.8: Hourly Percenage Load Impacs, SCE DBP Cusomers no in BIP, Non-summer Monhs iii CA Energy Consuling

5 Figures Figure ES.1 Disribuion of DBP Enrollmen by Indusry Type PG&E... 4 Figure ES.2 Disribuion of DBP Enrollmen by Indusry Type SCE... 4 Figure ES.3: Average Hourly DBP Load Impacs by Even SCE... 6 Figure ES.4: Average 1-in-2 Weaher Year Load Impacs by Year and Scenario, SCE... 8 Figure ES.5: Average PG&E 2011 DBP Hourly Load Impacs by Scenario... 8 Figure 4.1: 2010 DBP Load Impacs PG&E Figure 4.2: 2010 DBP Load Impacs SCE Figure 4.3: 2010 Hourly Load Impacs by Even SCE DBP Figure 4.4: Observed Load and Temperaure, Sep Sep. 30 SCE DBP Figure 5.1: PG&E Hourly Even Day Load Impacs for he Typical Even Day in a 1-in-2 Weaher Year for Augus 2011, Program Level Figure 5.2: PG&E Hourly Even Day Load Impacs for he Typical Even Day in a 1-in-2 Weaher Year for Augus 2011, Porfolio Level Figure 5.3: Share of Load Impacs by LCA for he Augus 2012 Typical Even Day in a 1-in-2 Weaher Year Figure 5.4: Average PG&E 2011 DBP Hourly Load Impacs by Scenario Figure 5.5: SCE Hourly Even Day Load Impacs for he Typical Even Day in a 1-in-2 Weaher Year for Augus , Program Level Figure 5.6: SCE Hourly Even Day Load Impacs for he Typical Even Day in a 1-in-10 Weaher Year for Augus , Program Level Figure 5.7: SCE Hourly Even Day Load Impacs for he Typical Even Day in a 1-in-2 Weaher Year for Augus , Porfolio Level Figure 5.8: Share of SCE DBP Load Impacs by Local Capaciy Area Figure 5.9: SCE Average Even-.Hour Load Impacs by Monhly Sysem Peak Day in a 1-in-2 Weaher Year from iv CA Energy Consuling

6 Absrac This repor documens an ex pos and ex ane load impac evaluaion for he Demand Bidding Program ( DBP ) adminisered by wo of California s large invesor-owned uiliies in The evaluaion firs repors on he esimaion of DBP load impacs ha occurred on he even days called during he 2010 program year a Pacific Gas and Elecric Company ( PG&E ) and Souhern California Edison ( SCE ). Load impac resuls are repored a he program level, by indusry ype, and by local capaciy area. Ex ane forecass of load impacs are hen repored based on enrollmen forecass provided by he uiliies and a characerizaion of he per-cusomer load impacs observed in DBP is a volunary Inerne-based demand response bidding program ha provides enrolled cusomers wih he opporuniy o receive financial incenives in paymen for providing load reducions on even days. Credis are paid based on he difference beween he cusomers acual meered load during an even o a reference load, or baseline, which is calculaed from each cusomer s usage daa prior o he even. Cusomers are noified of evens by 12:00 noon on he previous day. PG&E called one DBP even in 2010, a four-hour es even on Augus 25 h ha lased from 2 p.m. o 6 p.m. SCE called nine DBP evens in 2010, all lasing eigh hours, from noon o 8 p.m. Enrollmen in PG&E s DBP was 1,052 cusomer service accouns in 2010, down slighly from 1,127 in Toal DBP load, represened by he sum of enrolled cusomers individual maximum demands 1, amouned o 1,168 MW. The manufacuring; and offices, hoels, healh care and services indusry groups made up he majoriy of PG&E s DBP enrollmen. SCE s enrollmen in DBP expanded from 1,369 cusomer service accouns in 2009 o 1,421 in These accouned for 1,461 MW of maximum demand. Manufacurers coninued o make up more han half of he enrolled load. As in previous years, only a relaively small percenage of he cusomer accouns enrolled in DBP acually submied bids for mos evens. Fewer han 200 PG&E cusomers, represening approximaely 30 percen of he enrolled load, submied a bid for he es even. A SCE, 470 cusomer accouns, represening 46 percen of he enrolled load, submied a leas one bid during Ex pos load impacs were esimaed from regression analysis of individual cusomerlevel hourly load daa, where he equaions modeled hourly load as a funcion of several variables designed o conrol for facors affecing consumers hourly demand levels. DBP load impacs for each even were obained by summing he esimaed hourly even coefficiens for all cusomers who submied a bid for ha even. The individual cusomer models also allow he developmen of informaion on he disribuion of load impacs across indusry ypes and geographical regions, by aggregaing cusomer load impacs for he relevan indusry group or local capaciy area. 1 Cusomer-level demand is calculaed as he average of he monhly maximum demands during he program monhs. 1 CA Energy Consuling

7 The oal program load impac for PG&E s es even averaged 68.2 MW, or 7.5 percen of enrolled load. Of his, 60 MW came from cusomers enrolled in boh DBP and BIP. These dually enrolled cusomers averaged a 31 percen load reducion during even hours. In conras, cusomers enrolled only in DBP reduced load by an average of 8 MW, or 1 percen of heir load. For SCE, average hourly program load impacs averaged approximaely 61.5 MW across nine evens. The load impacs showed some variaion across even days, wih a low of 41 MW and a high of 99 MW. On average, he load impacs were abou 5.9 percen of he oal reference load. We separaely summarized average even-hour load impacs for cusomers paricipaing in he Technical Assisance and Technology Incenives (TA/TI) program or he Auomaed Demand Response (AuoDR) program. For PG&E, TA/TI service accouns provided 383 kw of load impacs and heir AuoDR service accouns provided 1,658 kw of load impacs. For SCE, TA/TI service accouns provided 6,345 kw of load impacs and heir AuoDR service accouns provided 14,478 kw of load impacs. In he ex ane evaluaion, SCE forecass ha DBP cusomer enrollmen o increase subsanially in 2013, decline slighly in 2014 and remain a ha level hrough During his period, SCE's average even-hour load impac is approximaely 87 MW. Because PG&E has proposed o end is DBP program a he end of 2012, we have only forecas ex ane load impacs hrough ha year. The forecas load impac for Augus 2011 is approximaely 70 MW. For boh uiliies, he porfolio-level load impacs are subsanially less han he program-level load impacs because of he high level of load response provided by cusomers dually enrolled in he Base Inerrupible Program (BIP). For SCE, he porfolio-level load impac is 17.8 MW from For PG&E, he 2011 porfolio-level load impac is 7.7 MW. 2 CA Energy Consuling

8 Execuive Summary This repor documens ex pos and ex ane load impac evaluaions for he saewide Demand Bidding Program ( DBP ) in place a Pacific Gas and Elecric Company ( PG&E ) and Souhern California Edison ( SCE ) in (San Diego Gas and Elecric Company disconinued is program in 2009.) The repor firs provides esimaes of ex pos load impacs ha occurred during evens called in The repor hen documens an ex ane forecas of load impacs for 2011 hrough 2021 (2011 only for PG&E) ha is based on uiliy enrollmen forecass and he ex pos load impacs esimaed for The primary research quesions addressed by his evaluaion are: 1. Wha were he DBP load impacs in 2010? 2. How were he load impacs disribued across indusry groups? 3. How were he load impacs disribued across CAISO local capaciy areas? 4. Wha were he effecs of TA/TI and AuoDR on cusomer-level load impacs? 5. Wha are he ex ane load impacs for 2011 hrough 2021? ES.1 Resources covered DBP Program DBP, which was creaed in 2001, is a volunary Inerne-based demand response bidding program ha provides enrolled cusomers wih he opporuniy o receive financial incenives in paymen for load reducions on even days. Credis are paid based on he difference beween he cusomers acual meered load during an even o a reference load, or baseline, which is calculaed from each cusomer s usage daa prior o he even. Cusomers are noified of evens by 12:00 noon on he previous day. PG&E called one DBP even in 2010, a four-hour es even on Augus 25 h ha lased from 2 p.m. o 6 p.m. SCE called nine DBP evens in 2010, all lasing eigh hours, from noon o 8 p.m. Enrollmen Enrollmen in PG&E s DBP declined slighly from 1,127 cusomer service accouns in 2009 o 1,052 in Toal DBP load, represened by he sum of enrolled cusomers individual maximum demands 2, amouned o 1,168 MW. The manufacuring; and offices, hoels, healh care and services indusry groups made up he majoriy of PG&E s DBP enrollmen. Figure ES.1 illusraes he disribuion of DBP load across he indicaed indusry ypes. 2 Cusomer-level demand is calculaed as he average of he monhly maximum demands during he program monhs. 3 CA Energy Consuling

9 Figure ES.1 Disribuion of DBP Enrollmen by Indusry Type PG&E 10% 6% 2% 26% 40% Ag., Mining, Consr. Manufacuring Whole., Trans., Uil. Reail Offices, Hoels, Healh, Services Schools Ars&En., Oher svcs, Gov. 2% 14% SCE s enrollmen in DBP has expanded from 1,369 cusomer service accouns in 2009 o 1,421 in These accouned for 1,461 MW of maximum demand. Manufacurers coninued o make up more han half of he enrolled load, as shown in Figure ES.2. Figure ES.2 Disribuion of DBP Enrollmen by Indusry Type SCE 13% 3% 6% 13% 51% Ag., Mining, Consr. Manufacuring Whole., Trans., Uil. Reail Offices, Hoels, Healh, Services Schools Ars&En., Oher svcs, Gov. 6% 8% Bidding Behavior As in previous years, only a relaively small percenage of he cusomer accouns enrolled in DBP acually submied bids for mos evens. Fewer han 200 PG&E cusomers, represening approximaely 30 percen of he enrolled load, submied a bid for he es 4 CA Energy Consuling

10 even. A SCE, 470 cusomer accouns, represening 46 percen of he enrolled load, submied a leas one bid during ES.2 Evaluaion Mehodology We esimaed ex pos load impacs using regression analysis of cusomer-level hourly load daa. Individual-cusomer regression equaions modeled hourly load as a funcion of several variables designed o conrol for facors affecing consumers hourly demand levels, including: Seasonal and hourly ime paerns (e.g., year, monh, day-of-week, and hour, plus various hour/day-ype ineracions); Weaher (e.g., cooling degree hours, including hour-specific weaher coefficiens); Even indicaor (dummy) variables. A series of variables was included o accoun for each hour of each even day, allowing us o esimae he load impacs for each hour of each even day. DBP load impacs for each even were obained by summing he esimaed hourly even coefficiens for all cusomers who submied a bid for ha even. The individual cusomer models allow he developmen of informaion on he disribuion of load impacs across indusry ypes and geographical regions, by aggregaing cusomer load impacs for he relevan indusry group or local capaciy area. ES.3 Ex Pos Load Impacs The oal program load impac for PG&E s es even averaged 68.2 MW, or 7.5 percen of enrolled load. Of his, 60 MW came from cusomers enrolled in boh DBP and BIP. These dually enrolled cusomers averaged a 31 percen load reducion during even hours. In conras, cusomers enrolled only in DBP reduced load by an average of 8 MW, or 1 percen of heir load. For SCE, average hourly program load impacs averaged approximaely 61.5 MW across nine evens. Figure ES.3 shows he average hourly load impacs for each even, and for he average even day. The load impacs showed some variaion across even days, wih a low of 41 MW and a high of 99 MW. On average, he load impacs were abou 5.9 percen of he oal reference load. 5 CA Energy Consuling

11 Figure ES.3: Average Hourly DBP Load Impacs by Even SCE Average Even-Hour Load Impac (MW) /16/2010 8/24/2010 8/25/2010 8/26/2010 9/2/2010 9/27/2010 9/28/2010 9/30/ /1/2010 Even Dae On a summary level, he average per-cusomer even-hour load impac was 65 kw for PG&E's program and 46 kw for SCE's program. ES.4 TA/TI and AuoDR Effecs We separaely summarized average even-hour load impacs for cusomers paricipaing in he Technical Assisance and Technology Incenives (TA/TI) program or he Auomaed Demand Response (AuoDR) program. In addiion, we aemped o esimae he incremenal load impacs provided by cusomers paricipaing in TA/TI and AuoDR. The incremenal load impac is he observed load impac on TA/TI or AuoDR less he load impac ha one would expec from he cusomer in he absence of he program. Because of daa limiaions, i can be quie difficul o accuraely esimae incremenal load impacs, as is refleced in he number of wrong-signed resuls ha we esimaed (indicaing ha TA/TI or AuoDR reduced demand responsiveness). Table ES.1 summarizes he oal and incremenal load impacs by uiliy and program. The large wrong-signed incremenal load impac for SCE s TA/TI program is due o one indusry group, in which he non-ta/ti service accouns consisenly provide high percenage load impacs. The larges TA/TI service accoun is capable of providing a similarly high percenage load impac, bu does so in only wo evens. The lack of response during he remaining evens (in which he service accoun also submied a bid) reduces he average percenage load impac significanly, creaing he negaive incremenal load impac. 6 CA Energy Consuling

12 Table ES.1: 2010 Toal and Incremenal Load Impacs from TA/TI and AuoDR Uiliy Program Toal Load Impac (kw) % Toal Load Impac Incremenal Load Impac (kw) TA/TI % 229 PG&E AuoDR 1, % -336 TA/TI 6, % -12,832* SCE AuoDR 14, % 2,472 * This incremenal impac is reduced o -690 kw when one very large indusrial group is excluded from he comparison. ES.5 Ex Ane Load Impacs Scenarios of ex ane load impacs are developed by combining enrollmen forecass wih per-cusomer reference loads and load impacs, which were developed using he daa and resuls of he ex pos load impac evaluaion. Because PG&E is proposing o close is DBP program a he end of 2012, enrollmens are only forecas hrough ha year. The Brale Group forecass enrollmens o be 1,066 cusomers in 2011 and 1,162 in SCE anicipaes enrollmen in DBP of 1,456 cusomers in 2011 and 1,529 cusomers in SCE forecass DBP enrollmens o increase subsanially o 4,069 cusomers in 2013 and hen decline o 3,200 cusomers in 2014, where enrollmen remains for he duraion of he forecas period. Figures ES.4 and ES.5 show he ex ane load impacs for SCE and PG&E, respecively. Boh figures illusrae he large difference beween program-level load impacs (which include all cusomers enrolled in DBP) and porfolio-level load impacs (which exclude cusomers dually enrolled in he Base Inerrupible Program, or BIP). This is because cusomers dually enrolled in BIP end o be larger and more demand responsive han oher DBP cusomers. SCE load impacs increase subsanially in 2013 o mach he increase in enrollmens. 7 CA Energy Consuling

13 Figure ES.4: Average 1-in-2 Weaher Year Load Impacs by Year and Scenario, SCE Program Porfolio Load Impac (MW) Year Figure ES.5: Average PG&E 2011 DBP Hourly Load Impacs by Scenario Load Impac (MW) in-2 Program 1-in-10 Program 1-in-2 Porfolio 1-in-10 Porfolio Scenario 8 CA Energy Consuling

14 ES.6 Summary In 2010, PG&E called one four-hour DBP es even and SCE called 9 evens. PG&E s es even resuled in a 68 MW load reducion, of which 60 MW came from cusomers dually enrolled in DBP and he Base Inerrupible Program (BIP). The remaining DBP cusomers provided 8 MW of load reducion, or jus 1 percen of heir reference load. Ex pos load impacs for SCE s nine evens averaged 61.5 MW, or 5.9 percen of he reference load. In he ex ane evaluaion, SCE forecass ha DBP cusomer enrollmen o increase subsanially in 2013, decline slighly in 2014 and remain a ha level hrough During his period, SCE's average even-hour load impac is approximaely 87 MW. Because PG&E has proposed o end is DBP program a he end of 2012, we have only forecas ex ane load impacs hrough ha year. The forecas load impac for Augus 2011 is approximaely 70 MW. For boh uiliies, he porfolio-level load impacs are subsanially less han he program-level load impacs because of he high level of load response provided by cusomers dually enrolled in he Base Inerrupible Program (BIP). For SCE, he porfolio-level load impac is 17.8 MW from For PG&E, he 2011 porfolio-level load impac is 7.7 MW. 9 CA Energy Consuling

15 1. Inroducion and Purpose of he Sudy This repor documens ex pos and ex ane load impac evaluaions for he saewide Demand Bidding Program ( DBP ) in place a Pacific Gas and Elecric Company ( PG&E ) and Souhern California Edison ( SCE ) in (San Diego Gas and Elecric Company disconinued is program in 2009.) The repor firs provides esimaes of ex pos load impacs ha occurred during evens called in The repor hen documens an ex ane forecas of load impacs for 2011 hrough 2021 (2011 only for PG&E) ha is based on uiliy enrollmen forecass and he ex pos load impacs esimaed for The primary research quesions addressed by his evaluaion are: 1. Wha were he DBP load impacs in 2010? 2. How were he load impacs disribued across indusry groups? 3. How were he load impacs disribued across CAISO local capaciy areas? 4. Wha were he effecs of TA/TI and AuoDR on cusomer-level load impacs? 5. Wha are he ex ane load impacs for 2011 hrough 2021? The repor is organized as follows. Secion 2 conains a descripion of he DBP programs, he enrolled cusomers, and he evens called; Secion 3 describes he mehods used in he sudy; Secion 4 conains he deailed ex pos load impac resuls, including esimaes of he incremenal effec of TA/TI and AuoDR on load impacs; Secion 5 describes he ex ane load impac forecas; Secion 6 conains an assessmen of he validiy of he sudy; and Secion 7 provides recommendaions. 2. Descripion of Resources Covered in he Sudy This secion provides deails on he Demand Bidding Programs, including he credis paid, he characerisics of he paricipans enrolled in he programs, and he evens called in Program Descripions DBP is a volunary bidding program ha offers qualified paricipans he opporuniy o receive bill credis for reducing usage when a DBP even is riggered on a day-ahead basis. Firs approved in CPUC D , modificaions have been made o he program, including changes made for he program cycle a he direcion of he CPUC in D In ha decision, he Join Uiliies were direced o coninue heir DBP programs. The uiliy s DPB programs are designed for non-residenial cusomers, boh bundled service and direc access cusomers. Cusomers mus have inerne access and communicaing inerval meering sysems approved by each of he Join Uiliies. A DBP even may occur any weekday (excluding holidays) beween he hours of noon and 8:00 pm and are riggered on a day-ahead basis. These evens may occur a any ime hroughou he year. Resricions exis for cusomers enrolled in muliple DR programs o avoid muliple paymens for reducion during he same even period. 10 CA Energy Consuling

16 PG&E s DBP Program A PG&E, DBP is available o ime-of-use cusomers wih billed maximum demands of 200 kw or higher (less for aggregaed cusomer service accouns) who commi o reduce load by a minimum of 50 kw in each hour for wo consecuive hours during a DBP even. Eligible cusomers mus have an inerval meer which is paid for by PG&E, excep for direc access cusomers. For aggregaed cusomer service accouns, here mus be a leas one service agreemen wih a maximum demand of 200kW or greaer for a leas one or more of he pas 12 billing monhs wihin each aggregaed group ha will be designaed as he primary service agreemen for he aggregaed group. The DBP program operaes year-round and can be called from 12:00 p.m. o 8:00 p.m. on weekdays, excluding holidays. There is no limi o he number of days on which DBP evens may be called. Noificaion of an even day is provided on a day-ahead basis. 3 Day-ahead evens are riggered wih a California ISO Aler Noice for he following day when he California ISO s day-ahead peak demand forecas is 43,000 MW or greaer, or when PG&E, in is own opinion, forecass ha resources may no be adequae. Day-of evens are riggered when he California ISO issues an energy warning. PG&E may also acivae up o wo DBP Day-Ahead es evens per year in order o simulae an emergency even. When an even day is called, enrolled cusomers may choose o bid a load reducion for he even or no o paricipae for ha even. For evens called a day ahead, he incenive paymen is $0.50 per kwh reduced below a baseline level. Cusomers mus reduce load by a minimum of 50 percen of heir bid amoun o qualify for a credi, and hey are paid for load reducions up o 150 percen of heir bid amoun. The hourly baseline for load reducions is calculaed as he average usage from he previous en qualifying days (non-holiday, non-even weekdays), wih he cusomer having he opion o include a day-of adjusmen based on heir usage in preeven hours. There is no penaly for failing o comply wih he erms of he submied bid. Each bid mus be a minimum of wo consecuive hours during he even. Bids mus mee he hreshold of 50 kw for each hour and cusomers may submi only one bid for each even noificaion. Alhough PG&E cusomers enrolled in DBP may paricipae in oher DR programs (Dayof noice in AMP, CBP, BIP, and OBMC), hey do no receive a day-ahead DBP incenive paymen for hose hours in which a day-of even from anoher DR program in which he cusomer is enrolled occur simulaneously. SCE s DBP Program SCE s DBP program design is similar o PG&E s, wih wo excepions: enrolled cusomers are required o commi o a minimum load reducion of 30 kw (versus 50 kw a PG&E); and bidding cusomers are paid for load reducions up o wice heir bid amoun. DBP paricipans may also paricipae in CPP, BIP, Day-of CBP, or OBMC. 3 On June 24, 2010, PG&E filed Advice Leer 3560-E-B wih he CPUC requesing he eliminaion of he DBP day-of program opion. The Commission approved he advice leer on July 27, 2010 wih a May 1, 2010 effecive dae. 11 CA Energy Consuling

17 However, he cusomer will no receive DBP incenive paymens during overlapping even hours. SDG&E s DBP Program SDG&E disconinued is DBP in Paricipan Characerisics Developmen of Cusomer Groups In order o assess differences in load impacs across cusomer ypes, he program paricipans were caegorized according o eigh indusry ypes. The indusry groups are defined according o heir applicable wo-digi Norh American Indusry Classificaion Sysem (NAICS) codes: 4 1. Agriculure, Mining and Oil and Gas, Consrucion: 11, 21, Manufacuring: Wholesale, Transpor, oher Uiliies: 22, 42, Reail sores: Offices, Hoels, Finance, Services: 51-56, 62, Schools: Enerainmen, Oher services and Governmen: 71, 81, Oher or unknown. In addiion, each uiliy provided informaion regarding he CAISO Local Capaciy Area (LCA) in which he cusomer resides (if any) Program Paricipans by Type The following ses of ables summarize he characerisics of he paricipaing cusomer accouns, including size, indusry ype, and LCA. Table 2.1 shows DBP enrollmen by indusry group for PG&E. Enrollmen in PG&E s DBP declined slighly from 1,127 in 2009 o 1,052 in Enrollmens in previous years were 866 accouns in 2006; 1,063 in 2007; and 1,165 in Toal DBP load, represened by he sum of enrolled cusomers individual maximum demands 6, amouned o 1,168 MW, or 1.1 MW per service accoun. Average hourly usage for enrolled cusomers was 729 MW, or 693 kw 4 SCE provided Sandard Indusrial Classificaion (SIC) codes in place of NAICS codes. The indusry groups were herefore defined according he following SIC codes: 1 = under 2000; 2 = 2000 o 3999; 3 = 4000 o 5199; 4 = 5200 o 5999; 5 = 6000 o 8199; 6 = 8200 o 8299; 7 = 8300 and higher. 5 Local Capaciy Area (or LCA) refers o a CAISO-designaed load pocke or ransmission consrained geographic area for which a uiliy is required o mee a Local Resource Adequacy capaciy requiremen. There are currenly seven LCAs wihin PG&E s service area, 3 in SCE s service erriory, and 1 represening SDG&E s enire service erriory. In addiion, PG&E has many accouns ha are no locaed wihin any specific LCA. 6 Cusomer-level demand is calculaed as he average of he monhly maximum demands during he program monhs. 12 CA Energy Consuling

18 per service accoun. 7 The manufacuring; and offices, hoels, healh care and services indusry groups made up he majoriy of PG&E s DBP enrollmen. Table 2.1: DBP Enrollees by Indusry group PG&E Indusry Type Coun Sum of Max Sum of Mean % of Max Ave. Size kw kwh kw (kw) 1.Ag., Mining, Consr ,506 33, % Manufacuring , , % 1,819 3.Whole., Trans., Uil ,312 81, % 1,014 4.Reail 84 20,009 11, % Offices, Hoels, Healh, Services , , % 1,084 6.Schools 42 27,455 12, % En, Oher svcs, Gov ,569 75, % 1,048 8.Oher % 283 TOTAL 1,052 1,168, ,970 1,111 Table 2.2 shows comparable informaion on DBP enrollmen for SCE. SCE s enrollmen in DBP has expanded slighly from 1,369 service accouns in 2009 o 1,421 in This is a coninuaion of a rend from recen years, which has seen enrollmens increase from 1,079 cusomer service accouns in 2006 o 1,222 in 2007 and 1,244 in These accouned for a oal of 1,461 MW of maximum demand, or 1 MW per service accoun. Manufacurers coninued o make up more han half of he enrolled load. Table 2.2: DBP Enrollees by Indusry group SCE Indusry Type Coun Sum of Max Sum of Mean % of Max Ave. Size kw kwh kw (kw) 1.Ag., Mining, Consr ,507 23,957 3% 1,209 2.Manufacuring , ,614 51% 2,138 3.Whole., Trans., Uil ,706 67,655 8% Reail ,405 49,757 6% Offices, Hoels, Healh, Services , ,423 13% Schools ,759 25,027 6% En, Oher svcs, Gov , ,281 13% 1,665 TOTAL 1,421 1,461, ,714 1,028 Tables 2.3 and 2.4 show DBP enrollmen by local capaciy area for PG&E and SCE respecively. 7 Average hourly usage is calculaed as he sum of usage during he program monhs divided by he number of hours during he program monhs. 13 CA Energy Consuling

19 Table 2.3: DBP Enrollees by Local Capaciy Area PG&E Local Capaciy Sum of Max Sum of Mean % of Max Ave. Size Coun Area kw kwh kw (kw) Greaer Bay Area , , % 1,023 Greaer Fresno 57 53,111 31, % 932 Humbold 12 3,783 2, % 315 Kern 57 41,764 21, % 733 Norhern Coas 74 47,264 25, % 639 No in any LCA , , % 1,700 Sierra 49 18,816 8, % 384 Sockon 25 9,744 4, % 390 TOTAL 1,052 1,168, ,970 1,111 Table 2.4: DBP Enrollees by Local Capaciy Area SCE Local Capaciy Sum of Max Sum of Mean % of Max Ave. Size Coun Area kw kwh kw (kw) LA Basin 1,122 1,014, ,359 69% 913 Ouside LA Basin , ,104 13% 2,839 Venura , ,251 18% 1,116 TOTAL 1,421 1,461, ,714 1,038 Tables 2.5 and 2.6 summarize he characerisics of cusomer accouns ha submied a bid for a leas one 2010 even for PG&E and SCE respecively. For boh uiliies, he manufacuring indusry group had he highes share of enrolled load ha submied a bid. Table 2.5: DBP Bidding Behavior PG&E Indusry Type # Sum of Max % of Enrolled Avg. Hourly Bidders kw Max kw Bid kw 1.Ag., Mining, Consr , % 2,750 2.Manufacuring , % 52,128 3.Whole., Trans., Uil , % 6,772 4.Reail 27 7, % 2,350 5.Offices, Hoels, Healh, 4,050 Services 35 55, % 6.Schools % 0 7. En, Oher svcs, Gov , % 2,133 TOTAL , % 70, CA Energy Consuling

20 Table 2.6: DBP Bidding Behavior SCE Indusry Type # Sum of Max % of Enrolled Avg. Hourly Bidders kw Max kw Bid kw 1.Ag., Mining, Consr ,377 51% 6,797 2.Manufacuring ,439 47% 99,083 3.Whole., Trans., Uil ,681 56% 12,389 4.Reail 34 37,721 46% 5,574 5.Offices, Hoels, Healh, Services 97 83,538 44% 9,313 6.Schools 37 16,543 18% 2, En, Oher svcs, Gov ,919 49% 4,814 TOTAL ,218 46% 140, Even Days Table 2.7 liss DBP even days for he wo uiliies in PG&E called only one even, a four-hour es even on Augus 25 h ha covered hours-ending SCE called 9 evens, all of which were eigh-hour evens from hours-ending 13 o 18. Table 2.7: DBP Evens 2010 Dae Day of Week SCE PG&E 7/16/2010 Friday 1 8/24/2010 Tuesday 2 8/25/2010 Wednesday 3 1 (Tes) 8/26/2010 Thursday 4 9/2/2010 Thursday 5 9/27/2010 Monday 6 9/28/2010 Tuesday 7 9/30/2010 Thursday 8 10/1/2010 Friday 9 3. Sudy Mehodology 3.1 Overview We esimaed ex pos hourly load impacs using regression equaions applied o cusomer-level hourly load daa. The regression equaion models hourly load as a funcion of a se of variables designed o conrol for facors affecing consumers hourly demand levels, such as: Seasonal and hourly ime paerns (e.g., year, monh, day-of-week, and hour, plus various hour/day-ype ineracions); Weaher (e.g., cooling degree hours, including hour-specific weaher coefficiens); Even variables. A series of dummy variables was included o accoun for each hour of each even day, allowing us o esimae he load impacs for all hours across he even days. 15 CA Energy Consuling

21 The models use he level of hourly demand (kw) as he dependen variable and a separae equaion is esimaed for each enrolled cusomer. As a resul, he coefficiens on he even day/hour variables are direc esimaes of he ex pos load impacs. For example, a DBP hour 14 even coefficien of -100 would mean ha he cusomer reduced load by 100 kwh during hour 14 of ha even day relaive o is normal usage in ha hour. Weekends and holidays were excluded from he esimaion daabase Descripion of mehods Regression Model The model shown below was separaely esimaed for each enrolled cusomer. Q = a + 24 i= 1 5 i= 2 24 i= 1 24 i= 2 ( b ( b ( b ( b CDH i E DBP MornLoad ( bi, Ev hi, DBP ) + b MornLoad + Ev= 1 i= 1 i= 1 DTYPE i CDH, S i FRI, S i h i, DTYPE h h i, i, CDH i, ) + ) + i= 2 i= 6 Summer FRI ( b ( b MON i MONTH i Summer CDH ) + h i, MONTH ) + 24 i= 2 24 i= 2 MON ( b ( b h, S i i, MON, S i h i, ) + h 24 i= 2 ) + b i, ( b FRI i Summer h i, Summer ) + e ( b OTH i FRI Summer h i, ) + Summer MON ) OherEv 24 i= 2 ( b h i h i, i, ) ) In his equaion, Q represens he demand in hour for a cusomer enrolled in DBP prior o he las even dae; he b s are esimaed parameers; h i, is a dummy variable for hour i; DBP is an indicaor variable for program even days; CDH is cooling degree hours; 9 E is he number of even days ha occurred during he program year; MornLoad is a variable equal o he average of he day s load in hours 1 hrough 10; OherEv is equal o one in he even hours of oher demand response programs in which he cusomer is enrolled; MON is a dummy variable for Monday; FRI is a dummy variable for Friday; DTYPE i, is a series of dummy variables for each day of he week; MONTH i, is a series of dummy variables for each monh; Summer is a variable indicaing summer monhs (defined as mid-june hrough mid-augus) 10, which is ineraced wih he weaher and 8 Including weekends and holidays would require he addiion of variables o capure he fac ha load levels and paerns on weekends and holidays can differ grealy from hose of non-holiday weekdays. Because even days do no occur on weekends or holidays, he exclusion of hese daa does no affec he model s abiliy o esimae ex pos load impacs. 9 Cooling degree hours (CDH) was defined as MAX[0, Temperaure 50], where Temperaure is he hourly emperaure in degrees Fahrenhei. Cusomer-specific CDH values are calculaed using daa from he mos appropriae weaher saion. 10 This variable was iniially designed o reflec he load changes ha occur when schools are ou of session. We have found he variables o a useful par of he base specificaion, as hey do no appear o harm load impac esimaes even in cases in which he cusomer does no change is usage level or profile during he summer monhs. 16 CA Energy Consuling

22 hourly profile variables; and e is he error erm. The morning load variable was used in lieu of a more formal auoregressive srucure in order o adjus he model o accoun for he level of load on a paricular day. Because of he auoregressive naure of he morning load variable, no furher correcion for serial correlaion was performed in hese models. Separae models were esimaed for each cusomer. The load impacs were aggregaed across cusomer accouns as appropriae o arrive a program-level load impacs, as well as load impacs by indusry group and local capaciy area (LCA). We add load impacs across only cusomers who submied bids for a given even Developmen of Uncerainy-Adjused Load Impacs The Load Impac Proocols require he esimaion of uncerainy-adjused load impacs. In he case of ex pos load impacs, he parameers ha consiue he load impac esimaes are no esimaed wih cerainy. We base he uncerainy-adjused load impacs on he variances associaed wih he esimaed load impac coefficiens. Specifically, we added he variances of he esimaed load impacs across he cusomers who submi a bid for he even in quesion. These aggregaions were performed a eiher he program level, by indusry group, or by LCA, as appropriae. The uncerainyadjused scenarios were hen simulaed under he assumpion ha each hour s load impac is normally disribued wih he mean equal o he sum of he esimaed load impacs and he sandard deviaion equal o he square roo of he sum of he variances of he errors around he esimaes of he load impacs. Resuls for he 10 h, 30 h, 70 h, and 90 h percenile scenarios are generaed from hese disribuions. 4. Deailed Sudy Findings The primary objecive of he ex pos evaluaion is o esimae he aggregae and percusomer DBP even-day load impacs for each uiliy. In his secion we firs summarize he esimaed DBP load impacs for boh uiliies using a meric of esimaed average hourly load impacs by even and for he average even. We also repor average hourly load impacs for he average even by indusry ype and local capaciy area. We hen presen ables of hourly load impacs for an average even (also referred o as a ypical even day ) in he forma required by he Load Impac Proocols adoped by he California Public Uiliies Commission (CPUC) in Decision (D.) ( he Proocols ), including risk-adjused load impacs a differen probabiliy levels, and figures ha illusrae he reference loads, observed loads and esimaed load impacs. The secion concludes wih an assessmen of he effecs of TA/TI and AuoDR. On a summary level, he average even-hour load impac per enrolled cusomer was 65 kw for PG&E's program and 44 kw for SCE's program. 17 CA Energy Consuling

23 4.1 PG&E Load Impacs Average Hourly Load Impacs by Indusry Group and LCA Table 4.1 summarizes average hourly DBP load impacs a he program level and by indusry group for PG&E s es even, which occurred on Augus 25, While DBP load impacs were esimaed from he individual cusomer regressions of only hose enrolled cusomers who submied a bid for he es even, he reference loads and observed loads shown in he able reflec all cusomers enrolled in DBP. Across he four even hours, he average hourly load impac was 68 MW, or 7.5 percen of enrolled load. The Manufacuring indusry group accouned for he larges share of he load impacs. Table 4.2 summarizes load impacs by local capaciy area (LCA), showing ha he highes share of he load impacs came from ouside of he seven LCAs. Table 4.1: 2010 Average Hourly Load Impacs PG&E DBP, by Indusry Group Indusry Group Coun Esimaed Reference Load (MW) Observed Load (MW) Esimaed Load Impac (MW) Agriculure, Mining, & Consrucion % Manufacuring % Wholesale, Transporaion, & Oher Uiliies % Reail Sores % Offices, Hoels, Healh, Services % Schools % Enerainmen, Oher Services, Governmen % Oher or Unknown % Toal 1, % % LI 18 CA Energy Consuling

24 Local Capaciy Area Greaer Bay Area Greaer Table 4.2: 2010 Average Hourly Load Impacs PG&E DBP, by LCA Coun Esimaed Reference Load (MW) Observed Load (MW) Esimaed Load Impac (MW) % LI % % Fresno Humbold % Kern % Norhern % Coas Sierra % Sockon % No in any LCA % Toal 1, % Hourly Load Impacs Table 4.3 presens hourly PG&E DBP load impacs a he program level in he manner required by he Proocols. DBP load impacs were esimaed from he individual cusomer regressions of only hose enrolled cusomers who submied a bid for he es even. However, he reference loads and observed loads in he able reflec all cusomers enrolled in DBP. Hourly load impacs average 68 MW, which represens approximaely 7.5 percen of he oal DBP reference load for enrolled cusomers. PG&E has wo very differen ypes of cusomers in DBP: hose who are dually enrolled in Base Inerrupible Program (BIP) and hose who are no. The cusomers who are enrolled in boh DBP and BIP end o be larger and much more demand responsive han he cusomers who are only enrolled in DBP. For example, 60 MW of he oal 68 MW load impac comes from he DBP/BIP-overlap cusomers, which is a 31 percen load reducion for hese dually enrolled cusomers. In conras, he DBP-only cusomers accoun for only 8 MW of he oal load impac and average a 1 percen load reducion during even hours. 19 CA Energy Consuling

25 Table 4.3: DBP Hourly Load Impacs for Augus 25, 2010 Even Day PG&E Hour Ending Esimaed Reference Load (MWh/hour) Uncerainy Adjused Impac (MWh/hr)- Perceniles 10h%ile 30h%ile 50h%ile 70h%ile 90h%ile Reference Energy Use (MWh) Observed Even Day Load (MWh/hour) Esimaed Even Day Energy Use (MWh) Esimaed Load Impac (MWh/hour) Change in Energy Use (MWh) Weighed Average Temperaure ( o F) Cooling Degree Hours (Base 75 of) Uncerainy Adjused Impac (MWh/hour) - Perceniles 10h 30h 50h 70h 90h Daily 20,152 19, n/a n/a n/a n/a n/a The op porion of Figure 4.1 illusraes he reference load (ne of he BIP load reducion) and observed load for he DBP es even. The lower porion of he figure displays he esimaed DBP load impacs (which are labeled on he righ y-axis). The full se of ables required by he Proocols, including ables for each local capaciy area, are in he Excel file aached as an Appendix o his repor. 20 CA Energy Consuling

26 Figure 4.1: 2010 DBP Load Impacs PG&E 1,200 1,000 Reference Observed Load Impac Loads (MW) Load Impacs (MW) Hours Comparison of PGE's Load Impacs o he 2009 Program Year PGE s 2010 average hourly load reducion of 68.2 MW is 26 percen larger han he 54.1 MW reducion repored for The difference is due o a wo-hour overlap of BIP and DBP evens in For cusomers dually enrolled in BIP, measured load reducions were allocaed o he BIP during he overlapping even hours. In 2009, cusomer responses appear o have exended hrough he wo remaining DBP even hours afer he end of he BIP even, wih load reducions exceeding 100 MW in each hour (10 percen of program load). In 2010, here was no overlap beween DBP and BIP evens. This helps address a quesion we had in he 2009 program year evaluaion: how would he DBP/BIP cusomers respond o a sand-alone DBP even? The 2010 load impac is quie large (68.2 MW) compared o he load impac from he overlapping hours in 2009 (~5 MW), bu lower han he load impac in he non-overlapping hours in 2009 (~100 MW). Thus i appears ha cusomers dually enrolled in BIP provide more demand response o BIP evens han DBP evens. 21 CA Energy Consuling

27 4.2 SCE Load Impacs Average Hourly Load Impacs by Indusry Group and LCA Table 4.4 summarizes average hourly reference loads and load impacs a he program level for each of SCE s nine DBP evens. 11 Across all evens, he average hourly load impac was approximaely 62 MW. The load impacs showed some variaion across even days, wih a low of 41 MW, a high of 99 MW, and a sandard deviaion of 21 MW. On average, he load impacs were 5.9 percen of he oal reference load. Table 4.5 compares he bid quaniies o he esimaed load impacs for each even. Across all evens, he bid amoun averaged approximaely 110 MW, while he esimaed average hourly load impac was 62 MW. The average bid realizaion rae (esimaed load impacs as a percenage of bid amouns) across all even hours was 56 percen. Even Table 4.4: 2010 Average Hourly Load Impacs by Even, SCE Dae Day of Week Esimaed Reference Load (MW) Observed Load (MW) Esimaed Load Impac (MW) 1 7/16/2010 Friday 1, % 2 8/24/2010 Tuesday 1, % 3 8/25/2010 Wednesday 1,062 1, % 4 8/26/2010 Thursday 1, % 5 9/2/2010 Thursday 1, % 6 9/27/2010 Monday 1,056 1, % 7 9/28/2010 Tuesday 1,049 1, % 8 9/30/2010 Thursday 1, % 9 10/1/2010 Friday % Average 1, % Sd. Dev % % LI 11 As for PG&E, he reference loads and observed loads represen all enrolled DBP cusomer accouns, while he esimaed load reducions were esimaed only for he accouns ha submied bids for a given even. 22 CA Energy Consuling

28 Table 4.5: 2010 Average Hourly Bid Realizaion Raes by Even, SCE Even Dae Day of Average Bid Esimaed Load LI as % of Bid Week Quaniy (MW) Impac (MW) Amoun 1 7/16/2010 Friday % 2 8/24/2010 Tuesday % 3 8/25/2010 Wednesday % 4 8/26/2010 Thursday % 5 9/2/2010 Thursday % 6 9/27/2010 Monday % 7 9/28/2010 Tuesday % 8 9/30/2010 Thursday % 9 10/1/2010 Friday % Average % Tables 4.6 and 4.7 summarize average hourly load impacs for he average even by indusry group and LCA. Manufacuring service accouns accouned for he larges shares of he load impacs. By region, he highes share of he average load impac came from he LA Basin. Table 4.6: 2010 Average Hourly Load Impacs SCE DBP, by Indusry Group Indusry Group Coun Esimaed Reference Load (MW) Observed Load (MW) Esimaed Load Impac (MW) Agriculure, Mining, & Consrucion % Manufacuring % Wholesale, Transporaion, & Oher Uiliies % Reail Sores % Offices, Hoels, Healh, Services % Schools % Enerainmen, Oher Services, Governmen % Toal 1,383 1, % % LI Local Capaciy Area Table 4.7: 2010 Average Hourly Load Impacs SCE DBP, by LCA Coun Esimaed Reference Load (MW) Observed Load (MW) Esimaed Load Impac (MW) LA Basin 1, % Ouside LA Basin % Venura % Toal 1,383 1, % % LI 23 CA Energy Consuling

29 4.2.2 Hourly Load Impacs Table 4.8 presens hourly load impacs a he program level for he average DBP even in he manner required by he Proocols. The reference loads and observed loads in he able reflec all cusomers enrolled in DBP. Load impacs reflec only cusomers ha submied bids. Hourly load impacs for he average even range from 54.4 MW o 66.0 MW. These load impacs represen 5.9 percen of he oal enrolled DBP reference load. Table 4.8: 2010 DBP Hourly Load Impacs for Average Even Day, SCE Hour Ending Esimaed Reference Load (MWh/hour) Uncerainy Adjused Impac (MWh/hr)- Perceniles 10h%ile 30h%ile 50h%ile 70h%ile 90h%ile ,021 1, ,050 1, ,080 1, ,089 1, ,089 1, ,095 1, ,090 1, ,066 1, , Reference Energy Use (MWh) Observed Even Day Load (MWh/hour) Esimaed Even Day Energy Use (MWh) Esimaed Load Impac (MWh/hour) Change in Energy Use (MWh) Weighed Average Temperaure ( o F) Cooling Degree Hours (Base 75 of) Uncerainy Adjused Impac (MWh/hour) - Perceniles 10h 30h 50h 70h 90h Daily 23,030 22, n/a n/a n/a n/a n/a The op porion of Figure 4.2 illusraes he hourly reference load and observed load for he average DBP even. The boom porion of Figure 4.2 displays he esimaed hourly load impacs (scale is presened on he righ y-axis) for he average DBP even. Figure 4.3 shows he variabiliy of esimaed load impacs across evens. 24 CA Energy Consuling