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Home My WebLink About20191018IRP Volume II Appendices A-L.pdf7019 Integrated , fe,toafu/frfu 5 I f,I -^ill E A \I I I I r I VOLUME II _APPENDICES A-L ocroBER r8,20r9 I ,) I .......F_- \ I Ii Y a \v Ia I This 2019 Integrated Resource Plan Report is based upon the best available information at lhe time of preparation. The IRP action plan will be implemented as described herein, but is subject to change as new information becomes available or as circamstances change. It is PaciJiCorp's inlenlion to revisir and relresh the lllP action plan no le.ss J-requently lhan annually. Any refreshed IRP action plan will be submitted to the State Commissions for their informalion. For more information, contact: PacifiCorp IRP Resource Planning 825 N.E. Multnomah, Suite 600 Portland, Oregon 97232 (s03) 813-s24s irp@pacificorp.com www.pacificorp.com Cover Photos (Top to Bottom): Marengo Wind Project Transmission Line Iilectric Meter Pavant III Solar Plant PACTICoRP _ 20I9 IRP TABLE OF CONTENTS Taglg op CONTENTS INDEX OF FIGURES x APPENDIX A - LOAD FORECAST DETAILS INTRoDUCTIoN I I 3 3 5 6 6 7 8 8 9 S u M M,4 R y Lo A D I : o R-L.c As r ........................ LoAD FORECAST ASSUIVPTIONS .......... R.EGIONAL EC9NoMY BY JUNSDICI'ION . UTA| t................... OREGqN-.............. WvoMrNG............. WASHINGToN ,,..... IDAHo -.-............... CAt.tFoRNrA ......... WEATHER STATISTICALLY A DJUSTLD E N D. T lS E (,, 5A E'' ).. I N D r vt D UAL C u sro M L R l" o R E cA sr .................. ACTI tAL LjAD L\ATA....................... 10 l0 t3 l3 l) 13 t4 15 t5 15 l5 t6 16 l7 17 /8 l8 SYSTEM LaSSES.. FORECAST METHODOLOGY OVENVIEW CI,ASS 2 DEMAND-SIDE MINAGEMENT RES2URCES IN THE I,o/ID FOREC,IST ... M)DELING ovE Rt't Ew.................... Selps FoRrclsr AT THE CusroMER METER RESIDI:. NI1AL ................ CoMMERCuL............... INDUSTNAL.....,,...... STATE SUMMAPJES OREG)N.................. WASHINGToN .......... CALlFottNrA.. (IT,IH IDAHO WyoMtNc...... INDEX OF TABLES .......... vi PACITIC0RP _ 20 I9 IRP I'AI'I,F] of CON I'I,N|S APPENDIX B - IRP REGULATORY COMPLIANCE 2l INTRODUCTIoN 2t 2t 22 :J 23 23 24 GENERAL CoMPLIANCE CALII,.ORNIA IJTAH WASI NGtoti........... WYoMtNG................. PARTICIPANT LIST 59 59C o MM rssroNs.......... STAKLHOLDERS AND INDUSTRY EXPERIS............................60 PUBLIC.INPUT MEETTNGS 6t 61 64 64 66 G ENER 4 t. MF-EnNas..................... STATE-S P EC IF IC I NP w MEETINGS STAKEHoLDER Covvexrs..... APPENDIX D - DSM RESOURCES 67 INTRODUCTION 67 67 68 70 CoNSERVATToN POTENTHL ASSESSMENT (CPA) FoR 2019-2038 CURRENT DSM PRoCRAM OFFERINGS BY STAT8........ STATE-SPECIFIC DSM PLANNTNG PROCESSES APPENDIX E_ SMART GRID 73 INTRODUCTIoN........73 fR,lN.sMl.5l'IoN J^rsr E M E F F o RTS ..... DIST.RIB (Iuo N SYSTE M E F F.].RTS...... C r tsro M t:R I N Fo RMATrot'i E FF,RTS 73 75 /() FUTURE SMART GRID ...............76 APPENDIX C - PUBLIC INPUT PROCESS ..............59 CoNracr INFoRMATToN. ii PACrrCoRp - 2019 IRP TAI}I.E OT CONTENTS APPENDIX F _ FLEXIBLE RESERVE STUDY....77 INTRODUCTIoN 77 77 79 80 FLEXTBLE RESOURCE REQUIREMENTS C )NTI NG E NC y RES ERVE ........... IIEGULATI2N RESERVE. FR.EQT/I,N(Y RESP2NSEREsEn ...... 80 ......8.1 ......82B 1,,1C K S 1.AR1. REQUI REM ENTS.... ANC ILI,4 Ry SL RI,IC I S O P E RA|IONAL DISTINCTI2NS 82 83REGULATIoN RESERVE DATA INPI,TS Ot,tnr'rcw _ _.... 6 J I,OAD DATA 84 84 85 85 WND,lND S)LAR DA|A N)N-VER l)..1111..... REGULATION RESERVE DATA ANALYSIS AND ADJUSTMENT Ot ERntifi,.........8J .........8JBASE SC I:,DLJLE RAMPING ADJLISI,MENT. DATA CoRRt.:(1 t(),\s............. ..... REGULATIoN RESERVE REQUIREMENT METHoDoLOGY 86 88 OvERL,lt.tv ....88 C OMPO N E N'I'S OI.' O P I: RAU NG IU:S LR''E METHO DO I,OG Y 2 0 1 7 REGU T.AnoN RESERV E FoRrio4si .................... PORTFoLIo DIVERSnY AND EIM DIVERSITY BENEFITS ...,.,.94 .... 100 Po Rt Fo Lto D t t E RS trv B E\;EFrT............... EIM Dt t,rRSn'y B ENEFTT ......................... 100 t01 102 104 106 106 106 t07 ll0 t10 t 10ilt il4 OvERn E w................. REsurrs.................... REGI ]LATI)N RESERI,E (, FLEXBLE RESOURCE NEEDS ASSESSMENT................... Ot ERwEW.......... FO R,LCAST ED RESERVE REQUIREMEI',7|S.. FLE B LE R I:So LI RC E SLl P PLy I,.O RLC AST FLEXLB LE RESoU RC E SUPPLY PI"4NNING 111 FASr-RAMPTNG RESERVE RreurREMENrs ..................... INCREMENTAL REGULATI0N RISERVE REQUIREMENTS PORTFOLIO REcULATION RESERVE REQUIREMENTS PACII.ICORP _ 2II I !) IR? APPENDIX G- PLANT WATER CONSUMPTION l15 APPENDIX H- STOCHASTIC PARAMETERS il9 l19 lt9 120 120 122 t22 OvsRvrsw...... VOLATILITY.... ESTIMATING SHORT-TERM PROCESS PARAMETERS STOcTTaSTIC PROCESS DESCzuPTIoN .. DATA DI t' E Lo pM 8 7.................................. 123 PAkAMETER ESTIMATIoN A UI.oREGRESSIyE MoDEL ELECTRrcrry P Rrct:. Pftocr.s,s............ REGI)NAL LOAD PRoCESS... 126 t28 129 t32 t33 HyDRo G ENERATIoN PRoC I!SS SHORT-TE RM CoRRE UTIO N ESTI MATIqN APPENDIX I- PLANNING RESERVE MARGIN STUDY 137 137 138 . t38 . 139 . t40 . t40 METHODOLoGY.. ( t p t, A I. I I I I A sst t lt I pz( )r\s................. DEr-El-op\tEliT ot' Rt L|ABILtt y METRtcs DEt'ELopMt:tit 01. .5 rsmv V,|RIABLE PItoDUCl toN Cosrs St:Lt:c I IoN oF THE PLANNIN(; llt st R t M/lRGLti............... Rgsulrs l4l . t4l .142 .145 . t46 146 R E SO T,i R (' E P O RTI.- O U OS RELIABIL| ft Mt TRr(-s .... .5 )'.t7t!,r,/ C().tr.s INCREMENTAL ('osl ot.- RtiLr,tR .rIy.. CoNcr-usrol APPENDIX J- WESTERN RESOURCE ADEQUACY EVALUATION ...... 147 INTRODUCTIoN.....147 t47 l5t 152 152 154 NERC 20I8 LoNG TERM RELTABILITY ASSESSMENT.. PACTFIC NORTHWEST RESoURCE ADEQUACY FoRUM'S ADEQUACY ASSESSMENT CUSTOven VERSUS SHAREHoLDER RISK ALLOCATION PACIFICORP,S ENERGY PoSITIoN MARKET PT,]RCHASES IABI,I:OF CONTLNTS INTRODUCTIoN INTRODUCTION DEI,EL)PMENT oI; IIfSoIIRCE PoRTFoLIoS PACIFICORP _ 20 I9 IRP TAI} t-I] o}' CONTEN'I S APPENDIX K- CAPACITY EXPANSION RESULTS DETAIL t57 PoRTFoLIo CASE BUILD TABLES 157 APPENDIX L- STOCHASTIC SIMULATION RESULTS 243 INTRODUCTION 243 INopx or TRer-ps PActrrCoR-P - 2019 tRP TABI,}']OF CONTENI'S TABL[ TABLI, TABLIi TABI,E TABLE TABLL TABLE TABI,E TABLE TABLL TABLE TABI,E TABLE TABLI, TABLE TABLtj TABLTI TABLE TABLT TABLE A.I _ FORJ]CASTED ANNI]AI, LOAD, 20I9.2028, AT GENLRATION, PRE.DSM .......... A.2 - FoR-ECASTED ANNI]AL CoTNCIDENI.PEAK LoAD AT GENI,RATIoN, PRE-DSM A.3 - ANNrrAt. LoAl) CHANGj ... A.4 - ANNU^L CoINCIDEN'I PEAK CIIAN(;E............. A.5 _ WEATTTITR NoRMALIZED JIIRISDICTIoNAL RETAIL SALES 2OOO ,IHRoUGII 2OI 7... A.6 - NoN-CorNCIDI,NT JtJRISDrcroN,ll- PLAK 2000 TrrRouGH 2017 A.7 _ JURISDICTIoNAI- CoNTRIBUTIoN To CoINCDLNT PE^K 2OOO THRoT,GH 20 I7 A.8 - SYSTEM ANNI,AL RI'I.AII, SALITS FORECAST 20I9 THRoUGH 2028, PoST-DSM A.9 - FORTCAS'TEr, R.ETAIL SAI,ES GRowTH hI OREGoN, PoST.DSM ....................... A. l0 - FozuicAsrED RTTAII- SALES GRowrH rN WAsHrNcroN, posr'-DSM ............. A.I I _ FoRECASTED RETAIL SALEs GRowl.H tN CALITORNIA, POST-DSM. 2 3 3 3 A.12 _ FoRECASTED REI'AI SALES GRowTH A. I3 - FoRECASTED RETAIL S,qrrs Gr.owru A.14 - FORTCASTED RETATL SALES GnowTII IN Ul AH, PoST-DSM ........ IN IDAHo. PoST-DSM....... rN WYoMING, Posr-DSM .18 .25 .30 .38 .47 53 56 ll t2 t2 l5 t6 l6 t7 t7 l8 79 79 92 92 92 93 B.I _ IRP STANDARDS AND GIIIDELINES SUMMARY BY STA E 8.2 _HANDLING oF 2OIT IRP ACKNoWLEDGMENT AND OTHER IRP REQUIRI,MENTS ... 8.3 - OREcoN PuBLlc UTrLrry CoMMrssloN IRP STANDARD AND GuEELrNEs............ B.4 _ UTAH PTJBt,IC SERVICE CoMMISSI)N IRP STANDARD ANI) GUIDELINES ............... B.5 _ WASIIINGToN UTU,ITIES AND TRANSPoRTATIoN CoMMISSIoN IRP STANDARD AND CI IIDELINES........., 8.6 _ WYoMING PUBLIC SERVICE CoMMISSIoN GUIDELINES ............ TABI,E D.I_ CTIRRENT DLMAND R.ESPoNSE AND ENERGY EI,I.ICIENCY PRoGRAM SERVTCES AND OFFERINCS By SECTOR AND STA1E........._............... TABLT] D.2 - CTIRRENT wAI.t.SMART OUIRF,ACH ,\ND CoMMTINICATIoNS ACTIVTIIITS TABLI, F. I _ PoRI.FoI,Io RLaUI,ATIoN R.ESERVE RTQTJIREMENTS TABLE F.2 - 2019 FRS FLrrxrBLE R-ES(XrRCE CosTS As CoMPARED To 2017 Cosis .. TABLE F.3 _ CoMBINTiD DryERSIIY ERRoR ExAMPLE TABL[ F.4 _ WIND ERRoR EXAMPLE........... TABLE F.5 _ R-EGRESSIoN INPUTS ExAMPI,E TABLE F.6 - WIND FoRTCAST LEVEL EXAMPLE........... TABLI F.7 _ RESLILTS wITH PACIFICoRP PoRIToLIo DIVERSrrY TAtsLE F.8 _ EIM DIWRSIl.Y BF,NEFII. APPI,ICATIoN EXAMPLE,. TABLL F. l0 - ToiAL REcUL{roN REeutR|MENT, By ScnN,rplo ....... TABLF] F.I I _ PoRTFoI,Io RLGUI,ATIoN RF,QUIRLMINTS, PERCTN oF NAMF]PLAI.E/PEAK CAPACITY......... TABT.E F. l2 - RESERVE RrerJrREMENrs (MW)........ TABLE F.l3 - FLExrBr.E RESoURcE SrJppl-y FoRF.CAST (MW) l0t 102 102 107 t07lu tt2 \,1 70 70 TABLE F.9 - 20I7 REsI]LTS WITTI PORTFoLIo DIVF:RSITY AND EIM DIIV,ERSITY BI]NEFITS ........--,-.,,-.,,,,...-- PACFICORP _ 20 I9 IRP TABLI, O[ CON-I'ENTS TABLE G.I _ PL^NT W^TER TABLL G.2 - PLANT WATER TABI i G.3 - PI,AN,I WATER TABLE G.4 - PT.ANT WATER CoNSUMP'I]oN CoNsrI^4PrloN CoNSUMPTION CoNSLIMPTIoN WITH ACRE.FEET PLR YEAR..... By STATE (ACRE-FF.E1 )............. BY FUEL TYP! (ACRE-FEEI) ..... FOR PLANTS LOCATED IN TIIlJ ll6 tt7 tt7 TABI,E TABLE TAxLE TABLTi TABI,E TABLE TABLE TABLL TABLE TABLL TABI,E TABLE TAI}LE TABI,F TABLE TABLI, TABLE TABLE TABLE K TABLI, K TABI,Ij K Uppl,R Cot.oRADo RtvtrR BASIN (ACRE-IrET). - Selsor.tlL DEFINTTIoNS _ UNCERTAINTY PARAMETERS FoR NATURAI, GAS ................ - UNCERTAINTY PARAMTI.ERS FoR ELECI.RTCITY REGIoNS ... _ UNCI]RTAINTY PARAMF,TFRS FoR LOAD RIGIoNS ............... _ UNCERTAINI.Y PARAMETERS FoR HYDRo GENERATIoN...... - SHoRT-TERM WTN TER CoRRF.LATIoNS................................ - SHoRT-TERM Spn rNc Connpr-.q.TloNS.................. - SrIoRT-TERM SUMMER CoRREL^TrcNs................. H.l H.2 H.3 H.4 H.5 H.6 H.7 H.8 123 128 t29 112 133 134 t35 t35 136 I l8 158 159 159 159 160 160 160 l6l 162 't64 166 t97 207 214 t49 t49 149 t49 150 150 155 .. 157 TABLE H.9 - SHoRI-1rRM FALL CoRRr,-LATroNs............. SUMMER EXPANSIoN RISoURCE ADDITIoNS BY PRM WINTER EXP,.\NSIoN RESOIJRcE ADDITIoNS BY PRM SIMI]LA.I.LD RELIABILITY METRICS BY PRM................... FITTED REI-IABIL|I,Y METRTCS BY PRM ---,,,............ SYS'TEM VARIABI,F,, UP-I)RONT CAPITAL, AND RTN.RATE FIXED COS,IS BY PRM ....... I 2 3 4 5 .. l4l ..142 ..142 ..143 .. 145 TABI-E J.I _ WECC STIBRIGIoN DESCRIPTIoNS .,. TABLE J.2 _ NERC LTRA ANI.ICIPATED RESERVL MARGIN........ TABLL J.3 _NERC LTRA PRoSPECTIVL RESERVE MARGIN.....,,, T^BI,E J.4_NERC LTRA RE!-ERENCE RESLRVE MARGIN..........- TABLE J.5 _ PLAI.{NING RISERVL MARGIN SHoRI.I..ALLS BY St]IIREGIoN wIT]I ANTICIPA [D R.ESoURCES TABLE J.6 - PLANNING RESERVE MARCIN SHORTFALLS BY SUBRI,GIoN WITH PRoSPECTIVE R[SoURCES TABI,F] J.7 _ MAxIMT]M AVAILABLE FRoNI OI.IIICE TRANSACTIoNS BY MARKET HTTB..,,, TABLE K.I INI,TIAL DEVELoPMENI S.I.T]DY REFERENCL GUIDE TABI,L K.2 _ C-CASI. SI'UDY REFERF,NCL GUIDE T^BLE K.3 _ CP-CASI. S't T]DY R-EFERENCE GI]IDE ... TABLE K.4 _ PREFERRED PORII;0LIO RLFERENCI.] GUIDE........,.............,,, TABT,I, K.5 _ FOT RISK ASSESSMENT CASL STLIDY REIILRENCE GIIIDI.. - TABLE K.6 _ GATEWAY & No GAS CIsn Sluuy REFERENCL GTIIDE ...... TABLE K.7 SDtrslTlvtrv C.qsl: S.tur)y REFERENCFT GUIDE K.8 - DSM BUNDLLD CASE STUDY RLI,IR-ENCE G[]ll)E K.9 - P70 CASE STUrry RLI,ERENCE Glrtt)r, ................ K.1O _ EAST StDE RESoURCE NAML AN'D DESCRIPTIoN....,.,,......................... K.l I - WEsr-SIDI R-r.souRCE NAME AND DESCRIPIoN .............,,,,,,--.---,,,,,. K.l2 - INtrL{L CASES, DETATLLD CAPACITY ExpANstoN PoRTFoLIoS ......... TABI,ti K.I3 _ C-CASIjS, DETAILED CAPACI.IY EXPANSI0N PoRTF0LIo --......, I4 _ CP.CAsIis, DI]I.AILED CAPACITY EXPANSION PoRTFoLIo........... I5 - PREFERRED PoRTFoLIo, DETAIT,F,D CAPACITY ExPANSION PoRTFoLIO I6 _ FOT RISK ASSESSMENT CASTS, DETAII,F:I) CAPACTTY ExPANSIoN PoRTI,oLIo ........ 2 l5 v TABLE K.l 7 - CATIiwAy & No GAS CASrs, DETATLED CApACrry ExpANsroN PoRTFoLro TABLE K,I8 - SENSITIVITY CAsEs, DLI.AII,ED CAPACTIY ExPANSIoN PoRT}oI,to ............., TABLE K.I9 _ REBUNDLID DSM CASES, DETAILED CAPACTIY EXPANSION PoRTFoLIo..... .......221 .......227 .......235 TABL[ TABLE TABLE TABLE TABLI: TABI-E TABLE TABLE TABLL TABLE TABLE TABLE TABLE TABLE TABLE TABLE TABLF, TABLE TABLT TABLE TABLE TABLE TABI,E TABLE TABLE TABLE TABLE TABLE TABLE TABI-E TABLE TABLE TABI,E TABLE TABLE TAI]I,E STocltAsflc STocHASTIC STOCHASTIC SToCHAS,IIC STocfiASTtc L L L L L I 2 3 4 5 MEAN MEAN MEAN MEAN MEAN L.26 - STocHASTIC RrsK L.27 _ SToCHASTIC RISK L.28 _ STOCHAS'IIC RISK L.29 _ SToCIIASTIc RISK L.3O _ S'I.oCHASTIC RIsK L.3I _ ST0CHAS,IIC RISK L.32 - SToCIIASTIC RIsK L.33 - CARBoN DtoxtDli L.34 _ CARBoN DIoxIDE L,35 CARB0N DIoXIDL L.36 - CARUoN DIoxrDli L.37 _ CARBoN DIoxIDE L.38 _ CARBoN DIOXIDE L,39 - CARBON DIoXIDI: L.40 - CARBoN DIoxrDri PVRR, INrrrAr. DEvr,LopMENT CAsEs .,,,,..-......................... PVRR By PRICE ScLNARto, INfl rAr. DEVEL0PMENT CASES. PVRR, C C^sLs . PVRR BY PRrcli ScENARro, CP CASES PVR& FOT RrsK ASSLSSMENT CASES ..... -.......................... ADfl.STED PVRR, C CASI.s . ADJUS IED PVRR BY PRICE SCENARI0, CP CASF,S ADJTJSTED PVRR, FOT RISK ASSESSMENl. CAsEs ADJIISTED PVRR, GATEWAY AND No CAs CASES ADJUSTTD PVRR. SENsrrrvrry CASES .................. ADJt]STED PVRR, DSM REBUNDI,F,D CAS8S......... ADJrrsrED PVRR, P70 CAstrs ............................... EMISSIoNS, INITIAL CASI.s.... EMlssroNs By PRICL SCENARIo, INITIAL CASIS .... EMlsstoNS, C CAsF.s..................... EMISSIoNS BY PRICE SCLNARIo. CP CAsEs........... EMISSIONS, FOT RISK ASSESSMINT CASES,....,,.,.. EMIssIoNs. GAI.LwAY AND No GAS CASES........... EMISSIONS, SrNSI fl VtTy CrrSrS............................. EMISSIoNS, DSM REBIINDI,ED CASES ................... ......243 ......244 .,_...244 ......244 ......245 ,,,...245 ......245 ._....246 ......246 TABLE L.6 - STocTTASTIC MLAN PVRR, GArFwAy AND No G,rs Clsr.s.___. L.7 - STocHASTTc MEAN PVRR, SENsrrrvr[y CASES ....................... L.8 _ STOCHASIIC MEAN PVRR, DSM R.LBTNDLED CASE,S................... L.9 - Sroc Asrrc MEAN PVRR. P70 CAsEs............ L. l0 - STou rASTlc RrsK RESULTS, INrrrAL DEvljl-opMENT CAsF.s - MEDIrM CAs. Mr,DruM CO2... . .. . L.I I _ STOCHAS.TIC RISK RtrSTILTS, INI]IAL DEVELoPMENT CASES _ Low GAS, No CO2 ..,.,.... L. I2 _ SToCIIASTIC RIsK RISIILTS, INI'I.IAI, DEVELoPMF,NT CASIs - HIGH GAS, HIGH C02 ..... L. I3 _ SIocHASTIC RISK RESI]LTS, INITIAL DEVI,L(IPurNr. Cnsr,s _ SoCtAI, CoST OF CARBoN L. I4 - SToCHASTIC fuSK RTSUL.I'S, C CASES _ MEDIUM GAs, MEDruM CO2 ....,....................... L. I5 _ STOCHAS.I.IC RISK RESI.]LTS, CP C^SES _ MEDIUM GAS, MEDIIIM CO2 ............ L. I6 _ SToCIIASTIC RISK I(I]SIII,TS, CP CASES _ Low GAS, Low CO2 T^BLE L.I7 _ SI.oCIIASTIC RISK RESULTS, CP C^SES - HIGH G^S, HIGH CO2......,...... TABI-E L.I8 - SToCHASTIC RISK RESUL Ts, CP_ SoCrAI, CosT o[.CARBoN ................... TABLI] L. I 9 _ SToCIIASTIC RISK RESULTS, FOT RIsK ASSI]SsMENT CAsIiS _ MED M CAS, MEDI]M CO2......... .....247 _....248 .....248 .....248 .....249 249 250 250 ..2-51 ..251 L.2O _ STOCHAS-I'IC RISK R.ESI]LTS, GATEWAY AND No GAs CASLS _ MEDTLM GAs, MEDruM CO2.... L.2I - SToCHASTIC RISK RESULTS, SENSITIVIIY CASES _ MEDITM GAs, MEDTLM CO2 .......... L.22 _ STOCHAS,TIC RISK RESTILTS, DSM RTBTNDITD CAsES _ MljDI( ]M GAs MEDIUM CO2.. L.23 _ STocIIASTIC RISK RISI.ILTS, P7O CAsEs _ MTDnJM GAS, MEDIUM C02.... L.24 - SToCHASTIC RIsK ADJUSI.LI) PVRR, INI I'IAI- CASES... L.25 _ SToCTIASIIc RIsK ADJTISTED PVRR BY PRICE SCENARIo. INITIAI, CAsI.s .....252 .....252 .....252 .....253 .....253 ,s1 .....254 .....254 .....254 .....255 .....255 .....255 255 256 256 257 257 257 258 258 258 PAC ITICoRI, _ 20 I9 IRP TAtsLE OI. CONTEN'I S VIII T^BLF L.4I _ CARBoN DIoxDE EMISSIoNS, P7O CASLS TABLE L.42 _ AVERAGE ANNUAI, ENERGY NOT SER!'ED, INTTTAL DEVELOPMENT CASES ............... TABLT L.43 - AvrrRAar ANNUAL ENS By PRtct ScENARlo, lNrrIAL DEvELopMtrNT CAsEs ... ....... TABLE L.44 _ AVERAGE ANNL,AL ENERGY NoT SLRVED, C CASES ........ TABLE L.45 _ AVERAGE ANNUAL ENERGY NOT SERVED BY PRICE SCENARIo, CP CASES ..258 ..259 ..259 ..259 ..260 ..260 ..260 ..261 ..261 ..?61 TABLE TABLE TABLIi TABLE TABLE TABLE TABI-E TABLE TABLE TABLL TABLE TABLE TABI,E TABLE TABLE TABLE TABLE TABLE TABLE TABI-E TABLE L.46 _ AVERAGE AI.INUAL ENURGY NOT SERVLD, FOT RISK ASSESSMENT CAsI]S ......... L.47 _ AVERAGE ANNUAI, ENERaY NoT SER\T,D, CATEWAY AND No GAS CAsEs.................,..... L.48 _ AVERAGT ANNUAL ENERGY NOI. SERVED, SENSIIIVITY CASES ....................... L.49 _ AVERAGE ANNUAL ENERGY NoT SLRVED. DSM RU]LNDLED CASES.................,.............. L.5O _ AVERAGF. AI.INI]AL ENIRcY NOT SF,RVI.D, P7O CASEs.......... L,5 I _ PVRR CoST COMPONENTS I]Y PRICE SCENARIO, INITIAL CASLS, MEDrlrM GAs, Mr.DruM COz......................... L.52 CoNTTNUED- PVRR CoST CoMPoNENI.S BY PRICE SCINARIo, INITIAL CASES, MFDTLM GAs, MEDnTM COz..... L.53 _ PVRR CoST CoMPoNENI.S t]Y PRICE SCENARIo, INITIAL CASLS, Low GAS, NO CO2 ....... L.54 _ PVRR CoST CoMPoNENTS I]Y PRICE SCENARIo, INITIAI, CASLS, HIGH GAs, HIGH CO2 ... L.55 _ PVRR COS,I CoMPONENTS BY PRICI] SCENARIO, INIITAL CASF,S, So( r-AL Cosr oF CensoN............. L.56_PVRRCoSTCoMPoNENI.S,CCASES,MEDIIIMGAS,MEDIT]MCO2......,........ L.57 - PVRR CosT CoMPoNENTS, CP CASES, MF,DIT]M GAS MEDnIM CO2 ................... L.58 PVRR CosI CoMpoNENrs, CP CAstis, Low GAS No CO2,........................ L.59 _ PVRR CoST CoMPoNENl.S, CP CAsF,s, HIaII G^S HIGH C02.. L.60 _ PVRR CoST CoMP0NFNTS, CP CASES, SoCIAL CosT OF CARI]oN............... L.6l - PVRR CosT CoMpoNENrs, FOT CASES, MF.DnrM CAS MEDIITM CO2.......... .... . ............ L.62 _ PVRR CosT CoMPoNENTS, GATEWAY AND NO GAS CASL,S, MEDruM GAS MEDruM CO2 L.63 _ PVRR CosT CoMP0NENTS, SENSIIVITY CAstiS, MEDI]M GAs MEDn]M CO2.. L.64 - PVRR CoST CoMPoNENTS, DSM RTBUNDI,ED CASES, MEDII,M CAS MEDIUM CO2 ........ L.65 PVRR CosT CoMpoNENTs, P70 CAstis, MEDIUM GAS MEDIUM CO2 ............................... L.66 _ I O-YE^R A\,ERAGE INCRj,MLNTAL CIISTOMLR R^TE IMPACI. ..262 263 263 263 T ABL]. L.67 _ 2O.YI,AR AVERAGE INCREMT.]N,I.AL CUSTOMER RA'tL IMPACT ...... T^BI,E L.68 _LosS oF LoAD PRoBABILITY, MAJoR JTILY EVENT, MT]DIUM GAS MEIIIUIT CO2 .......... TABLE L.69 _ SUMMER PEAK, AVF,RACL LOSS OF LOAD PROBABII-ITY, MLDITiM GAS MEDIIiM CO2.. 2& 264 265 265 266 266 ?67 267 268 268 269 269 270 271 272 tx PACIFICORP _ 20I9 IRP T,\3L[ OIj (oNl L]liTS lNoEx op FrcuREs FIGURE A.I _ PACIIICoRP SYSTEM ENERGY LoAD FoRF,CAST CIhNGE, AT GI,NERATIoN, PRE-DSM .............2 FIGURE A.2 _ PACIFICoRP ANNUAI, RETAT- SAI,F,S 2OOO THRo(IGH 20 I 7 AND WESTDRN RrGtoN EMPLoYMENT.... ........................ 4 FIGURL A.3 _ PACII'ICORP AI.{NUAL RESIDENTIAL USU PER CUSTOMTJR 2OO I TTff.OUGH 2OI7 .........................5 FIGURE 4.4 _ IHS CLoBAI. INSIGIIT UTAH HoUS[HoLD AND EMPLoYMENT }oRICAsTs FRoM THE AucusT 2017 LoAD IoRECAST AND THF. SEPTEMBLR 2018 LoAD FoRECAST ....................-........... 6 FIGt,RE A.5 - IHS GLoBAL INSIGHT OREGoN HoUSEHoLD AND EMPLoYMENT FoRECAS,TS FRoM THE AucusT 2017 LoAD FoRECAST ANrr THE ST,PTEMBER 2018 LoAD FoRECAST ..............................,. 6 FIGURE A.6 _ IHS GLoBAI, INSIGHT WYoMTNG HoUSTTIoLD AND EMPLoYMENT I'oRECASTS FRoM THE Aucus'I 2017 LoAD l oRECAsr AND 1HE SEPTEMBIR 2018 LoAD t:oRrcAsr ................................ 7 FIGIIRE A.7 - IHS GI,oB^L INSIGHT WASHINCToN HoUSEHoLD AND EMPLoYMENT FoRECASTS FRoM TIIE AT,GUST 20 I7 LoAD FoRECAST AND THE SEP,TEMBER 20 I8 LoAD FoR.ECAST ........,...........,.........., 7 FIGUR.E A.8 _ IHS GLoBAI, INSIGIIT WASHINGToN HoI,SEHoLD AND EMPLoYMBNT FoREcAsTs FRoM THE AuGLrs'r 2017 LoAD r,oRECAsr AND THE SEPTEMBER 2018 LoAD rroRrcAsr ................................ 8 FTGURE A.9 - IHS GLoBAL INSIGHT CALII,ORNIA HoUSEHoLD AND EMPLoYMFNT FoREcAsTs FRoM nlE AlrcusT 2017 LoAD FoRECAST AND THE SIP'TEMRER 2018 LoAD FoRECAST .........,.....................- 9 FIGURtr A.I O _ CoMPARISoN oF UTA]I 5, I O, AND 20 YDAR AVERAGL PEAK PRoDUctNG TEMPERATURES ... I O FIGURE A. I I _ I.oAD FoRECAST SCENARIoS FoR I -rN-20 WEAI]rcR, HIGH, BASE CASE AND Low, PRE-DSM.............. l9 FIGURE F.I . BASE SCHEDTILL RAMPTNG ADJUSI.MENT...............,. FIGUR-t F.2 - PRoBABtl-lTy oF ExcEEDIN(i ALLoWED DITvtATIoN FIGURT, F.3 - WIND REGULATIoN RESERVE REeTTTREMLN'IS By FoRECAST - PACE ........ FIGT,RE F.4 . WTND REGT]I,ATIoN RESERvE REQIJIREMENTS BY FoRECAST CAPACITY FACTOR-PACW. FIGURE F.5 - Sot.nn Rrct;LnTloN RESERVTT REetIIREMENTS By F0RECAST CApACITy FAC rr)R-PACE. FIGT,RT F.6 - SOLAR RIGIJI,ATION R.ESITRVE REQUIREMI,NTS BY FoRLcAST CAPACITY FACToR-PACW FIGURE F.7 - NoN.VER RIGI]LATIoN RISIRVE REQUIREMEN S BY FoRECAST ScnrrDrir.E FACToR-PACE.......,.,........... FIGIIRF, F.8 _ NoN-VER REGULA,I.nN RESERVE RTQIIIREMEN S BY FoRI,CAST SCHEDLILL FACToR.PACW ..............--... FIGURL F.9 - STAND-ALONr-r LoAD R-EGt[,ATroN RESERvL REetJIREMLNI s-PACE ...... FIaURE F.l0 - STAND-Ar.oNE LoAD REGTTLATToN RrsriRvE REeutRr,MF.NTS-PACW... FIGURE F.I I _ INCREMENTAL WIND CAPACITY FIGURL F. I2 _ INCREMEN'IAI, S(II,AR CAPACITY ,....- FIGURE F. I3 _ INCR.I.ASTNG PEAK LoAD-PACE FIGURE F. I4 - INCRT,ASING PEAK LoAD.PACW ....... FTGIJRE F. I5 _ INCREMENTAL WIND AND SoLAR REGUI,ATIoN RlsERvE CosTs ............. FICUR[ F.I6 . CoMPARISoN oF RF,SERVL Rj.QT]IREMENTS AND RESoLIRCES, EAST BALANCING A(ITHoRTTY AREA ........................ FIGURE F- l7 - CoMpARISoN oF R-tiSER\T REeUIR|MENTS AND R_LSoURCES, WESI BALANCING AL[l()Rrry AREA .......,..........._.. .... 86 ....9l ....94 ....95 ....96 ....96 ...97 98 .........99 .........99 ....... 104 ....... 105 .. 105 .. 106 .. 109 l13 I l3 PACI.ICoR} _ 20 I9 IRP x TABLE OF CON'II]NTS PACIIiCORP 20 I9 IRI)'IAUL[: OF CONTIN] s FIGURE H.l - STocHASTIc PRocEsst s......... FIGIIRF, H.2_ I(ANDoM WAI,K PRIcE PRoCTSS AND MEAN RIVERTING PRoCESs.......... t2t t2l 122 t23 t25 126 t27 129 t30 l3l 133 138 144 t44 l4s t46 150 l5l t52 153 154 156 FICURE FTcURE FIGIIRL FIGt,RE H.3 H.4- H.5 - H.6- LoGNoRMAL DISTRIBUTIoN AND CUMULATIVE LocNoRMAL DISTRIBtr oN............ Dary Cas PRTCES FoR SUMAS BASTN, 2014-2017 ................... DArLy GAS PRICES FOR SUMAS BAsrN wrrH "EXPECTF-D" pRrcES,2014-2017......... GAs PRICE INDEX FOR SUMAS BASIN, 20I4.20I7.. FIGURE H.7 _ RLGRESSIoN I.oR SUMAS GAs BASIN ..- FIGTIRI H.8 - DAII-Y ELECTRICI,I.Y PRICES FoR FoIIR CoRNERS, 20 I4.2O I7 ...... FIGIIRE H.9_ PRoBABII,ITY DISTRIBTII.IoN I.oR PORTI-AND LOAD,2014.2O17 ..................... FIGURE H.I O _ DAILY AVER^GE LoAD FoR POR'I.LAND, 20I4.20I7... FI(iI]RE H.I I _ WLI,KLY AVI,RAGE HYDRO GENF,RAI.IoN TN THE WESI, 20 I3-20I7............. FIGTTRE I.1 _ WoRTpLow TtIR PI,AI.TNIN(; R.ESERVE MARGIN S,IT]DY FIGURE I.2 _ EXPECTED AND FITTED RF,I,ATIoNSIIIP oF EUE 1.o PRM FICiLJRE I.3 _ EXPLCTID AND FITTED RELATIONSHIP OI LOLH TO PRM FIGI]RL I.4 _ SIMUI,ATED RI]I,A-IIONSIIIP oF LoSS oF LoAD EPISoDE TO PRM......... FIGURE I.5 _ INCREMENTAI, CoST oF REI-IAI}ILITY BY PRM.........--....... FIGURL J.l WECC SUBRIi(;roN Rr,st RVE MARCiIN PIRCr]NTAGE SUMMARY ........ FTGURF. J.2 - WECC FoRECASTED Powr.rR SLrppLy MARGTNS, IssLrED 2009 To 2016 (STTMMER)... FrauRE J.3 - SysrEM AI.TNUAL HEAvy L0AD Hul rR PostIoN FI(iI'RL J.4 ,JITI,Y MoN IIILY HLH PoSITION FIGI.RF, J.5 _ S^MPI,E JI.I,Y PFAK DAY Pos[IoN FIGURE J.6 - PACIFICoRP M?TRKET PURCHASES,,,,........... xl PACIFICoRP' 2019 IRP TABLE OF CONI L,NI'S xll PACIFICORP - 20I9 IRP AppENorx A - Loao FoRecasr Dsrarls This appendix reviews the load forecast used in the modeling and analysis of the 2019 Integrated Resource Plan (lRP), including scenario development for case sensitivities. The load forecast used in the IRP is an estimate of the energy sales, and peak demand over a 2O-year period. The 20-year horizon is important to anticipate electricity demand in order to develop a timely response of resources. In the development of its load forecast PacifiCorp employs econometric models that use historical data and inputs such as regional and national economic growth, weather, seasonality, and other customer usage and behavior changes. The forecast is divided into classes that use energy for similar purposes and at comparable retail rates. These separate customer classes include residential, commercial, industrial, irrigation, and lighting customer classes. The classes are modeled separately using variables specific to their usage pattems. For residential customers, typical energy uses include space heating, air conditioning, v/ater heating, lighting, cooking, refrigeration, dish washing, laundry washing, televisions and various other end use appliances. Commercial and industrial customers use energy for production and manufacturing processes, space heating, air conditioning, lighting, computers and other office equipment. Jurisdictional peak load forecass are developed using econometric equations that relate observed monthly peak loads, peak producing weather and the weather-sensitive loads for all classes. The system coincident peak forecast, which is used in portfolio development, is the maximum load required on the system in any hourly period and is extracted from the hourly forecast model. Summary Load Forecast PacifiCorp updated its load forecast in September 2018. The compound annual energy grouh rate for the l0-year period (2019 through 2028) is 0.87 percent. Relative to the load forecast prepared for the 2017 IRP Update, PacifiCorp 2028 energy forecasted energy requirement increased in all jurisdictions other than Wyoming and ldaho, while PacifiCorp system energy requirement increased approximately 3.15 percent. Figure A.l has a comparison of energy forecasts from the 2019 tRP to the 2017 IRP Update. APPENDLa A _ LoAD FoRECASI DE.I.AILS Introduction I Forecasted Annual System Load (GWh) +2017 IRP Update +2019lRP 70,000 60,000 50,000 40,000 30,000 20,000 10,000 o! a.t at o. a.t a.l a.l a.lOat (\ at c-a.t a.t ooa] at \oa] al a..lql N ...l(\ PAcIT.ICoRP - 20I9 IRP APP!,NDD( A - LoAD FoRECAST DETAII-S re A.1 - Pacifi Load Forecast , at Generation, Table A.l and Table A.2 show the annual load and coincident peak load forecast when not reducing load projections to account for new energy efficiency measures (Class 2 DSM).t Table A.3 and Tabte A.4 show the forecast changes relative to the 2Ol7 IRP Update load forecast for loads and coincident system peak, respectively. Table A.l Forecasted Annual Load, 2019 through 2028 (Megawatt-hours), at Generation, DSM I Class 2 deurand-side management (DSM) Ioad reductioos are included as resources in the System Optimizer model. 2 2019 m,555,0r)0 l5,l16,420 4.648,980 888,050 25,$5.,la)10,034,340 3,961,820 2020 61,200,9l)0 15.458,460 4,683,290 894,090 26,240,X1)9,947.800 3.9763m 2021 61,658,220 6,1@;730 4,696,950 26,4m,100 9,8,14,530 3,987,6q)886,220 2022 62,430,120 r6.073.620 4,'124,UO 81i1,300 26,889,210 9,851,r l0 4,008,040 2023 63,189,850 16,226Ato 4,156.440 881,850 2'7,359,26 9,935,1l0 4,030,780 2024 &,099,060 t6.422.5(fr 4,802.810 882,180 2'7 ,8'16,',7fi)10,051r,210 4,056,61r) ,025 64,561.310 16,522,910 4,821.500 87't.420 28,220,371)10,052,750 4.0({,3(fr 2026 ({,235.860 16,66),290 4.855,450 2'1.(41,2m l0. t t 0,510 4,079.860871,460 2027 64,827,020 l6,8ll,0m 4,892.190 867,6(n 2'1,944,390 10,2 r 0.990 4,090,850 ,II'f,J 2019 - 2028 m 0.a1yo 6 IEDS tr)m u ITt;f m m ffnpt l rirgq 2t l m rrlgt IEM Efirr- ulEttTirltutmE lrt+ilIfatEilE ritrtE.tmEtiE tr I il@GM@@IIIIUT Year Total OR WA CA UT WY ID Compound Annud Gmrth Rate PACTFICORP _ 20I9 IRP APPENDD{ A _ LoAI) FORECAST DITAILS Table A.2 - Forecasted Annual Coincident Peak Load watts at re-DSM Table A.3 - Annual Load Change: September 2018 Forecast less Noyember 2017 Forecast att-hou rs at Genera DS}I Table A.4 - Annual Coincident Peak Change: Seplember 2018 Forecast less November 2017 Forecast at Generation,re-DSNI Regional Economy by Jurisdiction The PacifiCorp electric service territory is comprised of six states and within these states the company serves customers in a total of 90 counties. The level of retail sales for each state and county is correlated with economic conditions and population stalistics in each state. PacifiCorp 3 2.4{6 167 tE'i ffi l lItZl2019lq r97 2.44'l 1',l4202 0 t0,279 l,16 4,821 l.l0l 785 2,491 1'.79 t45 4.862 1.291 7882l2tlll'157 2022 10,468 2,526 786 t44 4.928 t.293 191 2023 10,58t 2,543 792 I46 5,m5 l.l{)l 791 2024 10,68?, ({s 788 5,08r{1.124 2,5'79 1( )ll 5,155202510,786 143 1,316 '7U 2026 10,8 t8 2,596 815 1A 5,144 ll,7y) 2,613 t4l 5.186 8002027t0,$5 1,332 2028 ,INEEIIEII [Trq riFEsi WE rq m0 IEI 4EM ITiEqA [f,Fgi l ffi TDIM ,E) -rJlr-rlitE-@rEEln ;Dlr@riElEIrililpil@l@-uwrf@E ,Er-ii.ri-mE (31.6ff)46,8 t0 33,610 40,9102019rff,560 (l l.2m)28, t,1{) 20 20 516.600 286,7({)60,670 2,420 211Ary.:t (81,630)16.920 2021 544,030 76,14\)2,350 2794m (219,250)12.820715,580 2022 978.34t)'757.450 90,500 3,300 389,520 (288,'r0)26,sfl) 803.410 t03,1160 5.1'lo s563m (281,790)19.670to231,2(x;.8t0 2021 1,437,060 851,760 I13,690 6,56t)712,080 (257.650)10,620 xq1 570 t20,010 8,490 842.I70 (307.270)(450)2025 1,556,5,() 2026 I,657,600 947,910 r27,0)0 n,850 m5,310 (lr8,m0)( 12,s70) 2027 1.904,560 l,fix,uto lt]7.810 6.900 1.ffig,810 (287,310)(26.6s0) 2028 r,998,380 t.062;1&152..r00 3.490 t,157930 (332,dX))(45,5m) fitg)t92 50 l0 (0)l0l 2'7 4 2020 24t t{11 l0 0 r23 l8 2021 248 t21 l2 (0)llt l (l) 21t22 278 149 t3 (0)125 (s)(4) t5'7 l5 (0)155 (5)t7\202J :11 2$24 t6l 5 (3)I l,t5 '1 ( l5) t'71 l7 (0)I (l{)( t0)2025 3(,(, t82 19 (D 222 ( l0)(lo2026196 2027 l9l 20 (l)153 (8)(ll) 201 22 (3)( l4)129)2028 149 Ilirt[ Year Total OR WA CA LTT WY ID l.1l 'tt)l 10.985 Compound Annusl Growth Rete Load Forecast Assumptions Ye er Total OR WA CA UT WY ID OR WA CA UT IDYearTotalWY 3.1'l P^CITICoRP - 20 I9 IRP APPENDIX A _ LOAD FoRE]CAST DETAITS uses both economic data, such as employment, and population data, to forecast its retail sales. Looking at historical sales and employment data for PacifiCorp's service territory, 2000 through 2017, in Figure A.2, it is apparent that the company's retail sales are correlated to economic conditions in its service territory, and most recently the 2008-2009 recession. Figure A.2 - PacifiCorp Annual Retail Sales 2000 through 2017 and Western Region Em ment Sources: PacifiCorp and flnited States l)epartrn€nt of tabor, Bureau of [.abor Slatislics The 2019 IRP forecast utilizes the February 2018 release of IHS Markit economic driver forecasU whereas the 2017 IRP Update relies on the February 2017 release from IHS Markit. As discussed below, although both the economic and demographic forecast is relatively unchanged from the 2017 IRP Update, the load forecast has increased. There are two changes which are driving the 2019 IRP load and peak forecast higher. First, higher projected demand from data centers are driving up the commercial forecast; whereas, a higher residential customer forecast is driving a higher residential forecast. Figure A.3 shows the weather normalized average system residential use per customer. As illustrated, residential use per customer has been decreasing since 2010. 4 -System Amual Sales -Westem Region Employment %%%%%%%%%%%%%%%%%% --r7^./ / // --/ 25 58,000 5(r,000 54,000 ,5o.ooo 48,000 46.000 44,000 42,000 52,000 37 35a -11 9 1.re ri 2'1 !tco =(J r! ce! oc !,B 3Iobo(! o 11,0m 10,8m 10,6m 10,4m 10,2m 10,0m 9,800 9,600 9,400 %%"%'%%,%%'-%%%'%'%%%%%4 PACIITICORP _ 2OI9 IRP APPENDD{ A _ LoAD FoRFjCAST DETAII-S re A.3 - PacifiC Annual Residential Use er Customer 2001 throu 2017 Utah PacifiCorp serves 26 of the 29 counties in the state of Utah, with Salt Lake City being the largest metropolitan area served by the company within the state. Utah is expected to experience an annual increase of 1.30 percent in non-farm employment over the next l0 years. Figure A.4 shows the change in population and employrnent forecasts between the 2017 IRP Update relative to the 2019 IRP forecast. This figure illustrates that the population forecast is slightly lower. The employrnent forecast is slightly higher over the 2019 through 2024 timeframe, while it is lower over the 2025 through 2028 timeframe. Relative to the load forecast prepared for the 2017 IRP Update, the Utah 2028 retail load forecast increased approximately 4.95 percent. This increase is attributable to higher projected demand from data centers driving up the commercial forecast and higher residential demand due to higher projected residential customers. 5 Residential use per customer across all six of PacifiCorp's states is changing due to increased energy efficiency driven primarily by lighting efficiency standards resulting from the 2007 Federal Energy legislation. In addition, there has been a shift from single-family and manufactured housing to multi-dwelling units and a trend ofreplacing older electric appliances with more energy efficient appliances. r______ ______-r.T-T----__- 3,900 3,800 3,700 3,600 3,500 1,400 -l3m 1,200 3,100 3,000 2,900 Utah Population Forecasts - Augutt 20 | 7 - Scprenbcr :0 I 8 2 Utah Employment Forecasts -August 2017 -Septembcr 20I8 -q ^s ^\ ,.l1, i5 ^0. ^b ^b A ^$n$- 1sv .vsv .vsv asv asv asv .rsv nqv nsv 5o 7tx) .600 ii{x) .500 350 ,400 .350 .650 .550 PACIIICoRP 20 I9 IRP APPENDD( A _ LoAD IoRECAST DHIAIIS Figure A.4 - IHS Global Insight Utah Household and Employment forecasts from the August 2017 load forecast and the mber 2018 Load Forecast 0regon PacifiCorp serves 25 of the 36 counties in Oregon, but provided only 26.6 percent of ultimate electric retail sales in the state of Oregon in 2017.2 Figure A.5 shows the change in population and employment forecasts for the 2017 IRP Update relative to dre 2019 IRP forecast. This figure illustrates that the Oregon forecast of population and employment have both increased slightly. Relative to the load forecast prepared forthe 2017 IRP Update, the Oregon 2028 retail load forecast has increased approximately 5.73 percent. Figure A.5 - IHS Global Insight Oregon Household and Employment forecasts from the Au 2017 load forecast and the tember 2018 Load Forecast Wyoming PacifiCorp serves 15 of the 23 counties in Wyoming, with Casper being the largest metropolitan area served by the company in the state. Industrial sales make up approximately 74 percent of PacifiCorp's Wyoming sales. Figure .4.6 shows the change in population and employment forecasts for the 2017 IRP Update relative to the 2019 IRP forecast. This figure illustrates that the Wyoming population forecast used in the 2019 IRP forecast has decreased relative to the 2017 IRP Update. Similarly, the employment forecast has also decreased. Relative to the load forecast 2 Sourcc: Oregon Public fltility Commission,20lT Oregon Utility Statistics 6 Oregon Population Forecasts -Augusl2017 -Seprcmber20lS ".s d,t ,&' .u$ di' dF df' "". dC ,s. .200 :60 :40 180 160 140 ,340 .320 ,100 ,280 E a Oregon Employment Forecasts -AuSuxr t0l7 -s€pl.mbcr 2018 t60 t50 540 530 520 5t0 500 490 "., "&" "$ "$ -{D d} ',^6i, "d," ..s d," .q^s.\,.l\,s^E^b^h.]\^$ts- "rsv na' nsv aav tsv 1sv nsv asv asv PACIFICORP _ 2O I9 IRP APPF]NDTX A LoAD FoRICAS]. DEIAII-S prepared for the 2017 IRP Update, the Wyoming 2028 retail load forecast decreased approximately 4.27 percent. Au ust 2017 load forecast end the S mber 2018 Load orecast A risk to the Wyoming forecast is commodity prices, such as oil and natural gas, where volatility in prices and profitability can lead to swings in production and employnent which translates to potential swings in the retail sales forecast. Washington PacifiCorp serves the following counties in Washington State: Benton, Columbia, Cowlitz, Garfield, Walla Walla, and Yakima. Yakima is the most populated county that the company serves in Washington State and has a large concentration of agriculture and food processing businesses. Residential and commercial sales are roughly equal in size each making up approximately 39 percent of PacifiCorp's Washington sales. Figure A.7 shows the change in population and employment forecasts for the 2017 IRP Update relative to the 2019 IRP forecast. This figure illustrates that the population forecast is lower, while the employment forecast has increased. Relative to the load forecast prepared for the 2017 IRP Update, the Washington 2028 retail load forecast increased approximately 1.78 percent. Figure A.7 - IHS Global Insight Washington Household and Employment forecasts from the Au 20t7 load forecast and the ber 2018 Load Forecast Wyoming Population Forecasts - August 2017 -Seplember 2018 280 275 270 265 260 255 250 ,.9 d," "&' d0 d? dF "$ 'u-{," .,"$ ,". Wyoming Employment Forecasts E z -August 20t7 - S€Pr.mbcr 20t8 134 132 130 r28 t26 t24 r22 120 ".9 .ulo .u+' ".,"' d? ',-6| $t d," Sl .u&. z Washington Employment Forecasts -Augusr 2017 -Scptember 2018 r08 to7 106 l0J 104 I03 102 lol 100 .q ^s ^\ ,r'! 3 ^!. ^5 ^b 3 ^$"vs- 1$v asv 1$/ -y(l' -vsv 1sv 1sv {!v as' Washington Population Forecasts -Augusl2017 -Seprcmbcrl0lSlt5 ^ lto E :os : 300 ! ,on E 285 ,$ ,e" -$ Sl dfi ,$ "{t "6'" "$ ,s,' l 80 Figure A,.6 - IHS Global Insight Wyoming Household and Employment forecasts from the 7 PACTFICoRP - 2019 IRP APP}:NDX A _ LOAD FoRECAST DETATLS ldaho PacifiCorp serves 14 ofthe 44 counties in the state of Idaho, with the majority ofthe company's service territory in rural Idaho. lndustrial sales make up approximately 50 percent of the company's Idaho sales. Figure A.8 shows the change in population and employment forecasts for the 2017 IRP Update relative to the 2019 IRP forecast. This figure illustrates that the forecast for population has increased, while the employment forecast has increased over the 2Ol9 to 2023 timeframe and declined over the 2O24 to 2O28 timeframe. Relative to the load forecast prepared for the 2017 IRP Update, the Idaho 2028 retail load forecast decreased approximately 1.32 percent. Figure A.E - IHS Global Insight Washington Household and Employment forecasts from the Au 20l7load forecast and the S mber 2018 Load Forecast California The four northem California counties served by PacifiCorp are largely rural, which include Del Norte, Modoc, Shasta and Siskiyou Counties. Crescent City is the largest metropolitan area served by the company in Califomia. Residential sales make up approximately 50 percent of the company's Califomia sales. Figure A.9 shows the change in population and employment forecasts for the 2017 IRP Update relative to the 20l9IRP forecast. This figure illustrates that the population and employment forecasts have increased. Relative to the load forecast prepared for the 2017 IRP Update, the Califomia 2028 retail load forecast increased 0.40 percent before energy efficiency (and decreased 0.8570 after accounting for energy effrciency savings). 8 200 r95 190 185 180 115 170 165 160 Idaho Population Forecasts -Au8ct 20t7 - Seprcmbcr 2018 "", ,s" Si' d0 "$ "$ dt "{," "$ "{," Idaho Employment Forecasts -Autsusr 2ol7 - Scptemhcr 2018 "", ."' d) dP "69 S dF "6," $ B- e74 2tz 8709E68 -o. (,6 i6l i60 Z z California Population Forecasts -August 2017 -Septcrnher 2018 't8 e74 1t 'to ".9 ,*t "6,' dP "$ ^$F "$ ,6," "$ "-,s,. I 31. 3:glo Aze E27 Ezo i25 2 California Employment Forecasts -Aueust20l7 -Seplemb€r2018 ,d d re'"$ "$ dI ,$ "&" fo d," PAClFICORP-20I9IRP APPTNDIx A _ LoAD FoRICASI ,T.:IAILS Figure A.9 - IHS Global Insight California Household and Employment forecasts from the A 2017 load forecast and the 2018 Load Forecast PacifiCorp's load forecast is based on normal weather defined by the 20-year time period of 1998- 2017. The company updated its temperature spline models to the five-year time period of 2013- 2017. PacifiCorp's spline models are used to model the commercial and residential class temperatue sensitivity at varying temperatures. PacifiCorp has reviewed the appropriateness of using the average weather from a shorter time period as its "normal" peak weather- Figure A.l0 indicates that peak producing weather does not change significantly when comparing five, 10, or 20 year average weather. 9 Weather PACITICoR} _ 2OI9IRP APPENDX A _ LoAD FOR.ECAST DT]|AII-S Figure A.l0 - Comparison of Utah 5, 10, and 20 Year Average Peak Producing Tem eratures Statistically Adjusted End-Use (*SAE") PacifiCorp models sales per customer for the residential class using the SAE model, which combines the end-use modeling concepts with traditional regression analysis techniques. Major drivers of the SAE-based residential model are heating and cooling related variables, equipment shares, saturation levels and efficiency trends, and economic drivers such as household size, income and energy price. PacifiCorp uses ITRON for its load forecasting software and services, as well as SAE. To predict future changes in the efficiency of the various end uses for the residential class, an excel spreadsheet model obtained from ITRON was utilized; the model includes appliance effrciency trends based on appliance life as well as past and futue efficiency standards. The model embeds all currently applicable laws and regulations regarding appliance efficiency, along with life cycle models of each appliance. The life cycle models, based on the decay and replacement rate are necessary to estimate how fast the existing stock of any given appliance tums over, i.e. newer more efficient equipment replacing older less efficient equipment- The underlying efficiency data is based on estimates ofenergy efficiency from the US Department of Energy's Energy Information Administration (EIA). The EIA estimates the effrciency of appliance stocks and the saturation of appliances at the national level and for individual Census Regions, lndividual Customer Forecast Utah Average Peak Produclng Weather (Average Dry Bulb Temperature on Peak Day (Deg F.)) +20 Year Average -o-10 Year Average +5 Year Averrge Jan Feb NIar .{pI May Jun Jul Aug Sep Oct Nov Dec __f__- r00 90 80 70 or@ hso H40 30 20 l0 0 10 PacifiCorp updated its load forecast for a select group oflarge industrial customers, self-generation facilities oflarge industrial customers, and data center forecasts within the respectivejurisdictions. APPI]NI)Ix A_ LOAD TORtsCASI DT,fAU-S Customer forecasts are provided by the customer to PacifiCorp through a regional business manager (RBM). Actual Load Data With the exception of the industrial class, PacifiCorp uses actual load data from January 2000 through February 2018. The historical data period used to develop the industrial monthly sales is from January 2000 through February 2018 in Utah, Wyoming, and Washington, January 2002 tkough February 2018 in Idaho, and January 2003 through February 2018 in California and January 2008 through February 2018 in Oregon. The following tables are the annual actual retail sales, non-coincident peak, and coincident peak by state used in calculating the 2019 IRP retail sales forecast. Table A.5 - Weather Normalized Jurisdictional Retail Sales 2000 th 2017 .System retail sales do not include sales for resale Idaho (Jn:gon Washingk)n Wyoming S vslemYear 2000 716.330 3,$4;742 t4,047,381 18,765,857 4,U],l),269 7,373,138 48,1s6J1t 7'18,256 13.529.960 t8,4q),759 4,020,032 7,680,$3 47 ,487 )Ot)2001 t1,@7,U2 t8,u2.619800.256 4,017,549 47,182,t04 13.071.848 1.47t.9352003819,413 3,243,v9 4,M1,42'.7 41,953,042 3,300,658 13,188.745 I9,880,615 4,101,526 7,808,927 49,r 25,73420 04 3,232,797 l3,ly),t97 49,7 44,69 t20 05 835.878 20 06 859,459 3,348,273 13,9 ,t50 21,I17,90r 4,130,862 8,252,1)36 51,6 20.581 2[[7 3,384,l%14,023,185 21983,',124 4,O769(fi 8,48t,524 52,824,605 3.41_1.508 13,71t,92t 22,69t3N 4,0'71,e72 9,209,482 54,026,8992008 r3, t28,9t2828, 7 2.t)65.022 22.t5',t.812 4,048,793 9,258,055 52J87,581 Mt,47t 1426,21s 13.158.282 22.(fit,3'7t 4.052.934 9,6(14,8(,0 53,805,13J 3.472.522 13,029,055 23,457,892 4.018,0u9 9,765,559 54-r46,57920ll803,,162 3.518,810 t 3,044, 180 23,859,5{'4,M5,8?8 9,475,326 54,7 29,4612012185.6'14 2013 175.ffit 3,549,834 13.081.879 23,ri39,238 4059.5 )9,551,554 54,857,105 7',15,699 13.136.140 24,41ri,898 4,1o5,424 9,587,978 55,568,531 3.,t68.932 11.09.r.(xl4 24.1 17.031 4,102,238 9,37'7.276 54J06J7e747,'798 3.49t,U9 t3, t85,654 9,153,908 54,427,497757,|2 ,fim ,ITI'IITEE [frgt 4m rIEf,gI Eml 'Ef,g| 21.707.r)15 ml Growth m TERgA 2 IKVA 3 JIIJP7. m m IIIIFgI 7tIrilE-reEr@Errrtltlttr rriEilrErrtr']*Ifrm @il@@@@![r@I,EMt ll PACIFICORP _ 2OI9 IRP Svstem Retail Sales - Mesawatt-hours (MWh)* 2 010 4,041,9x)rr23,7<)6,9782016 2015 3,544,3912014 2009 w,625 874,813 8,011,25842 t 1,93320,251,628 u5,263 2002 t9,279,O71 7,405,4853.218.294 2,98'7.39r UrahChIifomia PACTFTCoRP -2019 IRP APPENI)Ix A _ LoAD F-oRECASI. DI-]IAII-S Table A.6 - Non-Coincident Jurisdictional Peak 2000 20t7 *Nontoincident peaks do nol include sales br resale Table A.7- Jurisdictional Contribution to Coincident Peak 2000 th h20t7 .Coincident peaks do not include sales for resale Ycar Orcgon Washington Wyorring S !,s tcm 2000 7ti53,684 1.062 8,995 2 001 3,480 I. t24 8,876 2002 11t I,II3 9,184 2003 7884,0u 1,t26 9,260 2004 2.524 3,8('9J l8 2005 2;721 4.08t M4 1.224 9,8t I 2006 180 8224,314 1,208 t),1)70 2{t07 789 2.856 4.57 t 834 1,230 10.466 2008 t87 759 )o)t 4479 92f 10,609 2009 4,4\A t0,705 2010 176 771 ) is)4,448 10,213 n544.596 1,404 10.486 20t2 159 ? 550 4,732 1,338 10,3 76 2013 I82 2,980 5.(Dl 1.398 I lJSl 201.t l6l 10.831 2015 r57 ) sr)R 5.n6 1,326 10,986 20t6 t55 84lt ?5R4 5.018 819 Ijm rt,724 ,[m flTIIIIIE m IIIITPI trr|m m WM IE EM m IIESI E IE6M,tar% m ffiEilEEre-E-EGEil prrrr r ririr r @ @ @ @ @-JEpt Year (hlitbmia Idaho Oregon WashirRtonLrrah Wyoming Svstcm 2000 523 2.141 3,684 9'79 8..t43 2 001 42t 3 419 t,091 2002 758 t,043 8_5t I 2003 t55 r lso 4,m.1 1,o22 8,887 2004 (,03 ) )r\t 3,831 8,588 li.lt95 I ()7)1.0(,4 9.283 2007 2,6i.j4 4,381 9,730 20 08 2,521 728 t,208 9,456 20 09 153 517 ) 57',t 4,t5t 795 98?q t7< 20t0 t44 2,442521 4,294 75'7 t,208 9)73 201I 2,t8'7 4,5%701 t,2u 9)87 2012 156 2,163 4,171 '749 9,806 2013 156 5,091 1,349 10414 2014 150 630 2.345 5.O24 819 t,294 10,263 2015 t52 805 2,472 5,081 83_l 1,259 t 0.601 2016 139 575 2.462.1.20t 10,135 ffi IIrIgA IIEII96 tru rrn% wn O:EM ,ntn ',TITTE, m m[gi IEgA EEvI m m@-rr-!tcrBlrE @Err@@-rriil@,@GD @ t2 Non-Coincident Pesk - Mesawatts (MW)* E37843 1,3608715,O244598818 EE6814 '797800 2,686770t77201I 1,366893 1,3839t73,121688193 1,339 lE7 2,724723 753189 l,ln0708193 2,45t722169 3;1'732539'7 t3174 7552,739616L6,, L@3686t76 UtahIdahoCalitbmia Coincident Peak - Mesawotts (MW)* Comoound Annud Growth Rate 1,3ffi 8174,9N 7n2407674 549t43 4,1456E2l7l 1,t2975470t160 El62,6U5611562006 1,0817084,015) )la681t7r2005 1,09t'140120 714573 2,138689la 7,8636272,t2tt24 756154 PACIFICORP _ 20I9 IRP APPENDD( A _ LOAD I, oRI-]CAS-I. DETAILS System Losses Line loss factors are derived using the five-year average of the percent difference between the annual system load by jurisdiction and the retail sales by jurisdiction. System line losses were updated to reflect actual losses for the five-year period ending December 31,2017. Class 2 Demand-side Management Resources in the Load Forecast PacifiCorp modeled Class 2 DSM as a resource option to be selected as part of a cost-effective portfolio resource mix using the company's capacity expansion optimization model, System Optimizer. The load forecast used for IRP portfolio development excluded forecasted load reductions fiom Class 2 DSM; System Optimizer then determines the amount of Class 2 DSM- expressed as supply curves that relate incremental DSM quantities with their costs-given the other resource options and inputs included in the model. The use of Class 2 DSM supply curves, along with the economic screening provided by System Optimizer, determines the cost-effective mix of Class 2 DSM for a given scenario. Modeling overview The load forecast is developed by forecasting the monthly sales by customer class for each jurisdiction. The residential sales forecast is developed as a use-per-customer forecast multiplied by the forecast number ofcustomers. The customer forecasts are based on a combination of regression analysis and exponential smoothing techniques using historical data from January 2000 to February 201 8. For the residential class, PacifiCorp forecasts tlte number of customers using IHS Global Insight's forecast of each state's number ofpopulation as the major driver. For the 2019 IRP, PacifiCorp improved its residential customer forecasting methodology by adopting a differenced model approach in the development of the residential customer forecast. Rather than directly forecasting the number of customers as has been done in previous years, the differenced model predicts the monthly change in number of customers. The changes are accumulated and added to the initial number of customers to generate the final customer forecast. PacifiCorp had observed that directly forecasted customers, as done in previous years, consistently produced an under forecast ofresidential customers. PacifiCorp performed a historical comparison of the forecasted results using both methods against actual customer counts and determined the differenced model produced a more accurate customer forecast. As such the model was used to forecast load for the 2019IRP. and resulted in an increase in the overall residential customer projections. For the commercial class, the company forecasts sales using regression analysis techniques with non-manufacturing employment and non-farm employment designated as the major economic l3 Overview PacifiCorp models sales per customer for the residential class using the SAE model discussed above, which combines the end-use modeling concepts with traditional regression analysis techniques. PACHCoRP _ 2OI9 IRP APPENDD( A - II)AD I-oR.EcAsT DEIAILS drivers, in addition to weather-related variables. Monthly sales for the commercial class are forecast directly from historical sales volumes, not as a product ofthe use per customer and number of customers. The development ofthe forecast of monthly commercial sales involves an additional step; to reflect the addition ofa large "lumpy" change in sales such as a new data center, monthly commercial sales are increased based on input from PacifiCorp's RBM's. The treatment of large commercial additions is similar to the methodology for large industrial customer sales, which is discussed below. Monthly sales for irrigation and street lighting are forecast directly from historical sales volumes, not as a product ofthe use per customer and number of customers. The majority of industrial sales are modeled using regression analysis with trend and economic variables. Manufacturing employment is used as the major economic driver in all states with exception ofutah, in which an lndustrial Production Index is used. For a small number ofthe very largest industrial customers, PacifiCorp prepares individual forecasts based on input from the customer and information provided by the RBM's. After PacifiCorp develops the forecasts of monthly energy sales by customer class, a forecast of hourly loads is developed in two steps. First, monthly peak forecasts are developed for each state. The monthly peak model uses historical peak-producing weather for each state, and incorporates the impact of weather on peak loads through several weather variables that drive heating and cooling usage. The weather variables include the average temperature on the peak day and lagged average temperatures from up to two days before the day ofthe forecast. The peak forecast is based on average monthly historical peak-producing weather for the 2O-year period, 1998 through 2017. Second, PacifiCorp develops hourly load forecasts for each state using hourly load models that include state-specific hourly load data, daily weather variables, the 20-year average temperatures as identified above, a t)?ical annual weather pattern, and day-type variables such as weekends and holidays as inputs to the model. The hourly loads are adjusted to match the monthly peaks from the first step above. Hourly loads are then adjusted so the monthly sum of hourly loads equals monthly sales plus line losses. After the hourly load forecasts are developed for each state, hourly loads are aggregated to the total system level. The system coincident peaks can then be identified, as well as the contribution of each jurisdiction to those monthly peaks. This section provides total system and state-level forecasted retail sales summaries measured at the customer meter by customer class including load reduction projections from new energy efficiency measures fiom the Preferred Portfolio. l4 Sales Forecast at the Customer Meter PACIFICORP _ 2OI9 IRP APPENDD( A_ LOAI) FoRICAST DEIAII-S Table A.8 - S Annual Retail Sales Forecast 2019 202 Residential Over the 2019-2028 timeframe, the average annual growth of the residential class sales forecast decreased from -0.28 percent in the 2017 IRP Update to -0.29 percent in the 2019 IRP. The number ofresidential customers across PacifiCorp's system is expected to grow at an annual average rate of 1.33 percent, reaching approximately I .9 million customers in 2028, with Rocky Mountain Power states adding 1.64 percent per year and Pacific Power states adding 0-84 percent per year. Commercial Average annual growth of the commercial class sales forecast increased from 0. I 8 percent annual average growth in the 2017 IRP Update to 0.87 percent expected average annual growth. The number of commercial customers across PacifiCorp's system is expected to grow at an annual average rate of 0.95 percent, reaching approximately 233,000 customers in 2028, with Rocky Mountain Power states adding I .20 percent per year and Pacific Power states adding 0.61 percent per year. lndustrial Average annual gtowth of the industrial class sales forecast decreased from -0.23 percent annual average growth in the 2017 IRP Update to -0.52 percent expected annual gro*th. A portion ofthe company's industrial load is in the extractive industry in Utah and Wyoming; therefore, changes in commodity prices can impact the company's load forecast. Year Rcsidential Industrial Irrigation 'forlrl 18,034,U)O2019t6,2t2,70/.',)t,466,024 133,696 s4,766,743 15,854,942 18,459,331 18,954,765 t,462,2t3 133.807 54,865,059 2021 15,638,202 14,734.741)18.834.645 1,458.187 132,854 54,794,677 18,954,503202215,616,831 |,454,t37 132,066 54,976'{O4 2023 15,631,036 19,o74,719 18.859,3 1..t49.880 r3l.097 55,146,128 t9,209,49t 18,950.5fi)2024 15,7 t3,57 t t,444,465 130,381 s5,448,408 19,230,12015,659,140 18,896,281 t,437,742 55Js2,O98 2026 15,674,375 19,326.3U 17,955.352 I,430. t40 54,513"839 2027 t5.702,419 I9.410,838 1,421,958 t26.313 54,675-5oO o.a7"/" 15 -o.290/0 I l{.(J5.1.,11 3 I Annual Gl -0.52"/o r.413.r2r{ owth Rete -o.400/" 5.l.lt73J0.r o.o2"/o 2{)2A 2019-28 r25,38.3 Svstem Retail Seles - Megawatt-hours (MWh) 4.71o/o I9,.18ti,236 18,0r3,973 127.588 l2tt,8l52025 18.818.871 202lD t8,920,232 Lightinr{Conrrrrcial t5 PACU.rCoRr, * 2019 IRP APPENDD< A_ I,oAD FoRECAS,I DDTAILS Oregon Table A.9 summarizes Oregon state forecasted retail sales grorth by customer class. Table A.9 - Forecasted Retail Sales Growth in ost-DSM Washington Table A.l0 summarizes Washington state forecasted retail sales growth by customer class. Table A.l0 - Forecasted Retail Sales Crowth in Washi DSM Year Residential Comrrrcial Industrial Irrigat io n Lishtins 'lbtal 2019 s 6?'t 551 5,434.085 |,793,918 327,801 39,%3 13,22932o 2020 5 5R5 611 5,629,8(A 1,801,507 127.9?8 40,?70 13,3E5,151 2021 5,556.225 5 ?q{) R{)q I,794,568 327.914 40.180 13,509,716 2022 5,556,(64 5,918, t54 1,786,929 327,933 4\\.220 r3.629,900 2112i 5,560,848 5,91t2.220 I,782,3W 327,944 q.250 r 3,613,66r 2024 5,585,036 5,896,025 I,782,806 327,778 .1O,386 13,632,030 2025 5,5(r2,ti45 5,ta(r5,984 t,778,44 327,419 40.289 13,574,9E3 2026 5,5@,157 s,851,239 l,781.633 327.076 40,3013 13,564,414 2027 5,571,n68 5,840,305 |.7M.666 326.7 t5 40.326 13,563,879 2024 ,TIISEI:'I 5.()5. t9 t -o.1160/0 o.1t20/o 5 -4l.lllo/o It 'En -0.0 5 o/o B 0 -l4o/" 4r).l('o 'f,] mm o.32l)/0 @rriEM-tti!t!!l lIlM trill;r:r Year Residential Comnrrcial Industrial Efltatit Liehtrng Total 2019 1,5v2,7t4 1,578,13 I 7U.573 t58,742 9,629 4,123,749 2020 1,570,%0 t,592,676 151r,600 9,U5 4,1 18,735 2021 1,554,7(A 1,58ri,547 783,t4 t5tt,437 9.592 4,o94486 2022 1,548,303 1,585,273 778.282 158,162 9,546 4,079565 2023 1,545,173 l,-s80,260 773,376 157,836 9,484 4,066,130 2024 I,54u,tt6l 1,578,084 77?,t98 t57,483 9,442 4,066,068 2025 t,540,807 1.s66204 768.629 157.091 9,342 4,042,072 2026 1,53n,798 1,5('0,228 768,325 156,638 9,270 4,033,259 2027 t,537,675 1,.556,561 768,1 I I 15(.l.191 9,t97 4,027 ,7 35 2028 2019-24 -0J5% I -s43 (xD 4.13"/o l E r]]r,I9| 1@ m 15 m $EIM 4.56Yo 9 t54 EE EE 4.23Vo ZIIl{lnlilt-tiiBrn6 -uttgJ-itMJ @ I@ t6 Oregon Re tail Sale s - M e sawatt-hours (MWh) Comnound Annual Growth Rate State Summaries Washinston Retail Sales - Mesawatt-hours (MWh) 786,855 Comnound Annual Growth Rate PACTIJICORP _ 2OI9 IRP APPENDH A_ LoAD FoRECASI DEIAIIS California Table A.l I summarizes California state forecasted sales growth by customer class Table A.ll - Forecasted Retail Sales Growth in California DSM l-Itah Table A.l2 summarizes Utah state forecasted sales growth by customer class. Table A.l2 - Forecasted Retail Sales Growth in Utah, post-DSM Commercial Industrial Inigation Liehtine TotalYear 2019 367,897 235,353 58.162 115,073 t,862 7 48,349 36t,826 233.2t4 67,t27 u,5n 1,862 7 48,625 202r 355,51I 229,650 66,226 84,195 t,tt48 737,430 2?6,8(A 65,636202215) t)l l 83,848 l,ti36 730,214 349,7t7 223,699 64,9.)2 I ,1J20202383,434 723,662 348,835 220.8211 64_28t 82,916 I,80n 718,6672024 2025 345.089 216,362 63212 82.405 t,782 708,850 2026 341,104 2n.43 62,272 8 t,891 1,760 699,651 2027 115 71R 208.827 61,282 81,350 I,738 688,935 33t,tM -l .16l,1 205,(09 -1.490/0 0.43Yo 60 3 -0.90"/" 2028 2019-2a 80,790 4,57Vo 679 724 Year ConnrBrciaI Indus trial Irrigat io n Lighting Total 6,958,632 8.924,202 7,530,762 227,083 68,0502019 23,70a,729 2020 6.722,6q 9,127,823 7,U1,629 226,5 t8 67.n2 23,786,58J 202t 6,585,633 9,?55,377 7,650,5fi)225.U3 67,339 23,784,691 9,355,618 7,689,33120226,586,282 225.172 66,786 23,923,t89 9,503,73 t 7,7 t9,t3020236,610,009 224.47 |66,122 24J23163 6,({4,829 9,652,768 7,763,907 223.747 r.5 57S 2447O,827 7,768,5596,659,41tt 2n.gto 64,592 24,459,6r8 2026 9,887,tt6lt 6,828,384 222,{t92 63,782 23,688,755 10,010,002 6,850,869 221,26 62,9q 23..867,725 txrlqi I m 5re -0.97 Vo 4,33Vo tAn -0.98o/o @ mM68 2079-28 rBE*. | -?dfi B|'it-,Dl@t-7rt#'Jm@1il @ t7 California Retail Soles - Mesawatt-hours (MWh) l.7ltl Comnound Annual Grorvth Rate -l.06Yo Residential 2020 Utah Retail Sales - Mesawatt-houn (MWh) 2024 202s Compound Annual Growth Rate -o,28vo o,t7 vo Residential 6,722,6532027 6,686,629 9,74,139 2028 PACII-ICoRP - 2019 IRP APPENI)Ix A _ LOAD FoRECAS'I. DETAILS Idaho Table A.l 3 summarizes ldaho state forecasted sales growth by customer class. Table A.l3 - Forecasted Retail Sales Growth in Idah ost-DSM Wyoming Table A.l4 summarizes Wyoming state forecasted sales growth by customer class Table A.l4 - Forecrsted Retail Sales Growth in Wyoming, post-DSM Year Residential Connrrrcial Indus trial Irrigation Lighting Total 2019 708,653 507.N5 t,7114,522 642,926 2,590 3,646,095 2020 699,473 517,175 1,784.139 (44',t,292 2,580 3,641,660 2021 695,588 520.13 r 1,781,940 637.6t2 2,548 3,637,819 697,223 524,387 r,780,536 634,963 2,51r,t 3,639,627 699,t)48 3,64rJ082023527,91 t,778,654 632,234 2,481 2024 706,27 t 531,51I 1,777,222 628,727 2,446 3,646,179 2025 706,162 624.315 2,393 3$36,249 2026 709,0m 527,395 1,77 t,600 6r9,091 2,345 3,629,521 2027 710,493 525,432 I,769,234 613,336 2.294 3,620,789 2028 0.02o/"0.390 525 47tl -0,1tvo I 7(t7 66t 4,620/0 607 7 tl 2.249 -1.55o/o TB IA 4.100 BEB|Eftl Year Residential Cornnercial Industnal Imgation Liehtine Total 2019 951,251 I,354,914 6,968,294 24,398 I l,(03 eJ r 0,460 914.41 I 9,r82,30420201,358,57e 6,873,509 24,277 I1,52n 2021 8m,48t 1,350,275 6,758,?66 24,167 I 1.347 9,034,53s 2022 876.329 I .344.207 24.W l I,l6l 8p73,9r36,718,156 2023 865,34r r,336,8t8 6,740,U3 23,962 I0,94t)8977,905 2024 tt59,73tt t,330,275 6,790,086 23,8t4 t0,724 9,014,636 2025 844.820 1,308,045 23,601 10.416 8930J2s6,743,444 2026 834,596 1,287,030 6.743,137 ,1 ?<,)10,123 8,898,239 2027 8?3,992 |,269,711 6,779,8tt 23,1ffl 9,818 8,906,437 2028 2019-28 1 14,676 -1 .71"/"4.54Vo 8 69,57 61,259,257 4.8lYo 763,239 4.330/o 4.72"/" 22,872 -2.16"/" 9 532 t8 Idaho Retail Sales - Mesawatt-hours (MWh) 2022 710.1 t 5 Comoound Annual Growth Rate 2019-28 1,773,991529,386 Wvomins Retail Sales - Megawatt-hours (MWh) Comoound Annual Growth Rate PACIFICORP _ 2OI9 IR-P APPENDIX A _ I,OAI) FORTC ST DETAIIS The purpose of providing altemative load forecast cases is to determine the resource type and timing impacs resulting from a change in tle economy or system peaks as a result ofhigher than normal temperatures. The September 2018 forecast is the baseline scenario. For the high and low load growth scenarios, optimistic and pessimistic economic driver assumptions from IHS Markit were applied to the economic drivers in PacifiCorp's load forecasting models. These growth assumptions were extended for the entire forecast horizon. Further, the high and low load gro*th scenarios also incorporate the standard error bands for the energy and the peak forecast to determine a 95 percent prediction interval around the base IRP forecast. The 95 percent prediction interval is calculated at the system level and then allocated to each state and class based on their contribution to the variability ofthe system level forecast. The standard error bands for the jurisdictional peak forecasts were calculated in a similar manner. The final high load growth scenario includes the optimistic economic forecast plus the monthly energy adder and the monthly peak forecast with the peak adder. The final low load growth scenario includes the pessimistic economic forecast minus the monthly energy adder and monthly peak forecast minus the peak adder. For the l -in-20 year (5 percent probability) extreme weather scenario, PacifiCorp used l-in-20 year peak weather for summer (July) months for each state. The l-in-20 year peak weather is defined as the year for which the peak has the chance of occurring once in 20 years. Figure A.l I shows the comparison ofthe above scenarios relative to thebase case scenario. Figure A.l t - Load Forecast Scenarios for l-in-20 Weather, High, Base Case and Low,re-DSM 6 01 O !t !'! (O F- 0o oli O H N m n 6 rO t \ 6 o oo o o o o o o o o oo <, o o o o o o o - 1 in 20 Weather -Hi8h -8ase Case 14,Ofi) 12,OOO a,ooo 6,OOO 4,OOO 10,ooo 2,OOO + l9 Alternative Load Forecast Scenarios 3EtI E PACI,rCoR] - 2019 IRP APPENDD( A _ I,oAD }-oREcAsT D AILS 20 ApppNoIx B - IRP Rp,CuIaroRy CoUPLIANCE This appendix describes how PacifiCorp's 2019 Integrated Resource Plan (IRP) complies with (l) the various state commission IRP standards and guidelines, (2) specific analytical requirements stemming from acknowledgment orders for the company's 2017 Inte$ated Resource Plan (2017 IRP) and other ongoing IRP acknowledgement order requirements as applicable, and (3) state commission IRP requirements stemming from other regulatory proceedings. o Table B.l - Provides an overview and comparison of the rules in each state for which IRP submission is required. t r Table B.2 - Provides a description of how PacifiCorp addressed the 2017 IRP acknowledgement order requirements and other commission directives.r Table 8.3 - Provides an explanation of how this plan addresses each of the items contained in the Oregon IRP guidelines. o Table B.4 - Provides an explanation of how this plan addresses each of the items contained in the Public Service Commission of Utah IRP Standard and Guidelines issued in June 1992.o Table [}.5 - Provides an explanation ofhow this plan addresses each ofthe items contained in the Washington Utilities and Transportation Commission IRP guidelines issued in January 2006.r Table 8.6 - Provides an explanation ofhow this plan addresses each of the items contained in the Wyoming Public Service Commission IRP guidelines updated in March 2016. PacifiCorp prepares the IRP on a biennial basis and files the IRP with state commissions. The preparation of the IRP is done in an open public process with consultation from all interested parties, including commissioners and commission staff, customers, and other stakeholders. This open process provides parties with a substantial opportunity to contribute information and ideas in the planning process, and also serves to inform all parties on the planning issues and approach. The public input process for this IRP, described in Volume I, Chapter 2 (lntroduction), as well as Volume II, Appendix C (Public Input Process) fully complies with IRP standards and guidelines. The IRP provides a framework and plan for future actions to ensure PacifiCorp continues to provide reliable and least-cost electric service to its customers. The IRP evaluates, over a twenty- year planning period, the future load of PacifiCorp customers and the resources required to meet this load. To fill any gap between changes in loads and existing resources, while taking into consideration potential early retirement of existing coal units as an altemative to investments that achieve I Calitbmia Public tjtilities Code Section 454.5 allows utility with less than 500,000 customers ilr lhe state b rcquest an exemption from liling an IRP. Ilowever, PacifiCorp files its IRP and IRP supplemerts with $c Calilbmia Public Utilities Commission to addrcss the company plan for compliance with the Califomia RPS requirements- 2t PACrI-ICoRP 20l9lR-P App[NDx B - IRP I{ECUL^]oRy CoMpr.IANCI Introduction Included in this appendix are the following tables: P^( rrrCoRP - 20t9 IRP AppENDLx B - IRP RIGULAToRy CoMPLTANCE compliance with environmental regulations, the IRP evaluates a broad range ofavailable resource options, as required by state commission rules. These resource options include supply-side, demand-side, and transmission alternatives. The evaluation of the altematives in the IRP, as detailed in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) and Chapter 8 (Modeling and Portfolio Selection Results) meets this requirement and includes the impact to system costs, system operations, supply and transmission reliability, and the impacts of various risks, uncertainties and extemality costs that could occur. To perform the analysis and evaluation, PacifiCorp employs a suite of models that simulate the complex operation of the PacifiCorp system and its integration within the Westem intercornection. The models allow for a rigorous testing of a reasonably broad range of commercially feasible resource altematives available to PacifiCorp on a consistent and comparable basis. The analyical process, including the risk and uncertainty analysis, fully complies with IRP standards and guidelines, and is described in detail in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach). The IRP analysis is designed to define a resource plan that is least-cost, after consideration ofrisks and uncertainties. To test resource alternatives and identifu a least-cost, risk adjusted plan, portfolio resource options were developed and tested against each other. This testing included examination ofvarious tradeoffs among the portfolios, such as average cost versus rislq reliability, customer rate impacts, and average annual carbon dioxide (CO:) emissions. This portfolio analysis and the results and conclusions drawn from the analysis are described in Volume I, Chapter 8 (Modeling and Portfolio Selection Results). Consistent with the IRP standards and guidelines of Oregon, Utah, and Washington, this IRP includes an Action Plan in Volume I, Chapter 9 (Action Plan). The Action Plan details near-term actions that are necessary to ensure PacifiCorp continues to provide reliable and least-cost electric service after considering risk and uncertainty. The Action Plan also provides a progress report on action items contained in the 2017 IRP and 2017 IRP Update. The 2019 IRP and related Action Plan are filed with each commission with a request for acknowledgment or acceptance, as applicable. Acknowledgment or acceptance means that a commission recognizes the IRP as meeting all regulatory requirements at the time of acknowledgment. [n a case where a commission acknowledges the IRP in part or not at all, PacifiCorp may modifu and seek to re-file an IRP that meets their acknowledgment standards or address any dehciencies in the next plan. State commission acknowledgment orders or letters typically stress that an acknowledgment does not indicate approval or endorsement of IRP conclusions or analysis results. Similarly, an acknowledgment does not imply that favorable ratemaking treatment for resources proposed in the IRP will be given. Califo rnia Public Utilities Code Section 454.52, mandates that the Califomia Public Utilities Commission (CPUC) adopt a process for load serving entities to file an IRP begiruring in 2017. In February 2016, the CPUC opened a rulemaking to adopt an IRP process and address the scope ofthe IRP to be filed with the CPUC (Docket R.16.02.007). Decision (D.) l8-02-018 instructed PacifiCorp to file an alternative IRP consisting of any IRP submitted to another public regulatory entity within the previous calendar year (Alternative Type 22 PACTUCoRI - 2019 IRP AppENDrx B- IRPRECULAToRYCOMPT-TANCE On August I , 2018, PacifiCorp resubmitted its 2017 IRP in compliance with D. I 8-02-018, and the CPUC approved PacifiCorp's resubmission in D.l9-04-040 and deemed it to be in compliance. On September 20,2Ol9 the CPUC issued a ruling in Docket R.16.02.007 setting forth proposed IRP filing requirements; CPUC Staff continues to recommend a nonstandard IRP filing plan for multi-jurisdictional utilities, including PacifiCorp. The company submitted comments in support ofthese filing requirements on October 14, 2019. The Idaho Pubtic Utilities Commrssion's (Idaho PUC) Order No. 22299, issued in January 1989, specifies integrated resource planning requirements. This order mandates that PacifiCorp submit a Resource Management Report (RMR) on a biennial basis. The intent of the RMR is to describe the status of IRP efforts in a concise format, and cover the following areas: Each utility's RMR should discws any Jlexibilities and analyses considered during comprehensive resource planning, such as: (l) examination of ktad forecast unce ainties: (2) effects of hrown or potential changes to existing resources; (3) consideration of demand and supply side resource options; and (4) contingencie.t for upgrading, optioning and acquiring resources at optimum times (considering cost, availability, lead time, reliability, risk, etc.) as .fuure events unfokl. This IRP is submitted to the Idaho PUC as the Resource Management Report for 2019, and fully addresses the above report components. Oregon This IRP is submitted to the Oregon Public Utility Commission (OPUC) in compliance with its plaruring guidelines issued in January 2007 (Order No. 07-002). The Oregon PUC's IRP guidelines consist of substantive requirements (Cuideline l), procedural requirements (Guideline 2), plan filing, review, and updates (Guideline 3), plan components (Guideline 4), transmission (Guideline 5), conservation (Guideline 6), demand response (Guideline 7), environmental costs (Guideline 8, Order No. 08-339), direct access loads (Cuideline 9), multi-state utilities (Guideline l0), reliability (Guideline I l), distributed generation (Guideline l2), resource acquisition (Guideline l3), and flexible resource capacity (Order No. l2-013). Consistent with the earlier guidelines (Order 89- 507), the Oregon PUC notes that acknowledgrnent does not guarantee favorable ratemaking treatment, only that the plan seems reasonable at the time acknowledgment is given. Table B.3 provides detail on how this plan addresses each of the requirements. tltah 2 Publrc Uriliry CoDmi$ioo of Orcto[ Or&r No. l2-01], Delel No. 146l, jdnary l r. 2012 23 2 Load Serving Entity Plan). D. 18-02-018 also instructed PacifiCorp to provide an adequate description of treatment of disadvantaged communities, as well as a description ofhow planned fi.rture procurement is consistent with the 2030 Greenhouse Gas Benchmark. ldaho This IRP is submitted to the Public Serv'ice Commission of Utah in compliance with its 1992 Order on Standards and Guidelines for Integrated Resource Planning (Docket No. 90-2035-01, "Report PACTTTCoRP - 2019lRP AppENDx B - IRP REGTJLAToRY CoMpLLANC[ and Order on Standards and Guidelines"). Table B.4 documents how PacifiCorp complies with each of these standards. Washington This IRP is submitted to the Washington Utilities and Transportation Commission (WUTC) in compliance with its ru[e requiring least cost planning (Washington Administrative Code 480-100- 238) (as amended, January 2006). In addition to a least cost plan, the rule requires provision ofa two-year action plan and a progress report that "relates the new plan to the previously filed plan." The rule requires PacifiCorp to submit a work plan for informal commission review not later than 12 months prior to the due date ofthe plan. The work plan is required to lay out the contents ofthe IRP, the resource assessment method, and timing and extent of public participation. PacifiCorp filed a work plan with the WUTC on March 28, 2018, in Docket UE-180259. Table B.5 provides detail on how this IRP addresses each ofthe rule requirements. Wyoming Wyoming Public Service Commission issued new rules that replaced the previous set of rules on March 21,2016. Chapter 3, Section 33 outlines the requirements on filing IRPs for any utility serving Wyoming customers. The rule, shown below, went into effect in March 2016. Table 8.6 provides detail on how this plan addresses the rule requirements. Section 33. 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PACrr.rcoRP -20l9lRP APPENDX D - IRP REGULAToRY COMPLIANCI Table B.2 - Handlin of 2017 IRP Ackn ent and Other IRP uirements Case No. PAC-E- l7-03, Order No. 34018, p. 14 Expcct the company to consider pubhc input meeting p(xess concems raised in the 20 | 7 IRP as related to the Energy Vision 2020 projects and continue to evaluate all resourcc options and the best interest of customer when dcveloping the 20 I 9 IRP. For the 2019 IRP, PaciliCorp expanded the public-input meeting process tiom seven to l8 public-input mcetings and proiented its pretbrred porttblio and draft action plan al the October 3-4, 20t9 public-input mccting. See Volume II, Appendix C (Public Input Process). Casc No. PAC-E- l7-03, Order No. 34018. p. l4 The company should let its modeling fully assess when a coal plant should be rctired, and provide resource portfolios that are least-cost based on modeling, and not assumed coal plan retircment. Case No. PAC-E- l7-03, Order No. 34018, p. l4 Expcct the company to continue improving its forccasting methodologies by analyzing a brcad and diverse range of measutes to avoid disadvantagmus or unfair Iorecasting treatment oIcertai[ resources over others, includins coal and wind. See Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach). Order No. 14-252, p.3 Beginning in the thtd quarter of20l4, PaciliCorp will appear bclirre the Commission to provide quartcrly updatcs on coal plant compliance requirements, legal proceedings, pollution control investments, and other major capital expenditures on its coal planls or aansmission projects. PacifiCorp may provide a written report and nced not appear ifthere are no significant changcs between the quarterly updatcs. Ordcr No. 1,1288 modilied the requircments, movrng the datc ofthe lirst mecting from the third quarter of2014 to the fourth quarter of20l4. EnvironmentaUcoal and transrnission expendinues quarterly presentations were made at Commissior special public meetings on October 28, 2014 and March 16.2015. Quancrly presenulions via written reports wcre provided on June 30, 2015 and Octobcr l, 2015. Thc 2015 founh quarter prcsentation was made at the Commission special public mccting on Deccmhcr 17. 2015. A biannual DSM update was provided at the Commission public meetings on March [0, 2015 and Decembcr 15, 2015 l)iannual presentations tbr krth EnvironmcntaUcoal and trarsmission 30 Reference IRP Requiremcnt or Recommendrtlon IIow the Requlrement or Recommendstlon is Addressed in the 2019 IRP Idaho Recognizing limitations in modeling regarding endogerlous transmission retirements, Pacifi Corp conducted comprehensive coal studies as part of its 20l9lRP- See Volume I, Chapter fl (Modeling and Portfolio Selection Results) and Volume II, Appendix R (Coal Srudies) in particular lbr more information. Oregon Order No. 16-071 further streaurlined this rcquiremenl by rcquiring lhe company to continue to providc twice yearly updates on the status of dcrnand-side management (DSM) IRP acquisition goals at public meetings and include in these updates inlbrmation on future coal plant and transmission investment decisions, Also include inlbrmation on I t t(d) rule compliancc analysis; P^cFrCoRP - 2019 IRP APPENDH B _IRP REGI]I,AToRY CoMPLIANCE expenditurevl I l(d) and DSM were provided on August 30, 2016 and December 20, 2016. Please see Conunission website lbr public meeting history and Docket RE 163 for presentations and written reports provided. PacitiCorp has included two Regional Haze scenarios in the 2019 IRP. See Volume Il. Appendix M (Case Study Fact Sheets) for discussion on specific Regional Haze assumptiotrs lor muleling purposes PacifiCorp has included incremental transmission costs associated with specific resources. See Volume I, Chapter 6 @esource Options) for discussion ofthesc potential costs. Additional detail is provided on the data discs inclutled with the 2019 IRP filine. Order No. l4-252, p.3 In fluture [RPs. PacifiCorp will provide: o Timelines and key decision points li)r cxpected pollution control options and transmission investments: and o Tables detailing major planned expenditures with estimated costs in each year for each plant or transmission proJect, under dillerent modeled scenarios. The screening tool is no longer used to model competing retirement scenarios. In the 2019 IRP, Pacilicorp conductcd comprehensive coal studies See Volume I, Chapter 8 (Modeling and Portfolio Selection Results) and Volune II, Appcndix R (Coal Studies) in particular for more infonnation. Order No. 14-252, P- 13 In thc acknowledgement order the Commission providcd the tbllowing recommendation: As part ofthe 2015, 2017, and 2019 IRPs, PaciliCorp will pnrvide an updated version of the screening tool spreadsheet model thai was provided io padicipants in the 201I (dockct LC 52) IRP Update. Order No. 14-252, P. 16 In l'uture IRPs, PaciliCorp will provide yearly Demand Rcsponse (Class I ) and F)nergy Efliciency (Class 2) DSM acquisition targcLs in both GWh and MW for each year in the planning perio4 by state. See Volume II, Appendix D (Demand-Side Management Resouces) for the breakdown by state and year for hoth energy and capacity selected for the preferred portfolio. PacifiCorp's 2019 IRP notes that the Clean Power Plan rule is stayed and $at no implementation plans or compliance measures impacted dte 2019 IRP, Order No. l6-071, p.4 1te Commission expects the company to update its Clcan Power Plan nn)deling in its 2015 IRP updatc or its next IRP (depcnding on when Oregon's compliancc plan is known) to correctly rcllcct the linal rule and Oregon's implementation plan. Order No. l6-071, p.5 ln addition to the action itenr 3a irrigation pilot program, the Oregon PtlC dtects Pacificorp to design and present additional pilots. PaciliCorp presented information on potential dcmand respouse pilot opportunities at the Oregon PIIC's August 16. 2016 public input mccting ard explained that thc 20 I 7 IRP would inform whethcr the company would propose additional pikrt progams. PacifiCorp provided updates on the status ofDSM acquisition goals to the Oregon PIIC on October 5, 2018 and August 5, 2019. PaciliCorp did not conduct a sensitivily on accelerated DSM in thc 2019 IRP. Order No. t6{71, Appendix A, p. t (action item 3b) Cotrtinue to provide twicc yearly updates on the status of DSM IRP acquisition goals at public mcctings. Include in these updates information on future coal plant and transmission investment decisions. as a strcamlined continuation o[ Order No. t4-288. 3l Referencc IRP Requirement or Recommendation IIow the Requirement or Recommendation is Addressed in the 2019IRP PAoFTCORP - 2019 IRP A?PENDL\ B - IRP REoriLAr oRy CoMpr.rANCE Also include information on I I I (d) rule compliance analysis; Provide more risk analysis on ponfolios that include accelerated energy efhciency as a resourcc; Include annual incremental summer and winter peak demand capacity (MW) conesponding to 20 I 5 tlrough 2018 Encrgy Efliciency (Class 2) DSM annual energy savings targets; For the 2015 IRP Update, provide model run results ofthe prefcrred portfolio with base case DSM and with accclcrated DSM for comparison PUTPOSeSi Perlbrm stochastic modeling on all portfolios with acceleratcd DSM. See Volumc I, Chapter 8 (Modeling Portfolio Selection Results) tbr the aflnual summer and winter peak demand capacity (MW) lirr l-)nergy Efiicieucy I)SM. Order No. l6-071, Appendix A, p.2 (action itern 5a) and Order No. [6- 071, p. 9. Continue permining Energy Gateway Segments D, E, F', and H until PaciliCorp files its 2017 IRP. The Oregon Pt)C acknowledges this action item only to the extent o[ PaciliCorp's pcrmitting actions. The Orcgou PUC expects to scc updated analysis in the ncxt IRP or belbre the company makes signilicant comrnitments to these tmnsmission lines. See Chapter 4 ('l'ransmission), Chapter 7 (Modeling and Portfolio t)valuation Approach), Chapter 8 (Modeling and Portfolio Selection Results), and Chapter 9 (Action Plan) for updated analysis on the company's Energy Gateway transmission scgments. See also Volumc II, Appendir M (Case Fact Sheets Ovewiew) Ibr additional detail regarding the Hnergy Gateway transmission segmens studied in the 2019 IRP. Order No. l6-071, Appendix A, p.2 (additional actions - modeling) See Volurne I, Chapter 8 (Modeling and Portlolio Selection Resultsl including winter and summer peak load and resource tables. 2. See Volume II, Appendix I (Planning Rcserve Margin Study)- The study concludes with a planning criteria that mects one day itr l0 year plandng targets at the lowest reasonable cosl. The company's Flexible Reserve Sndy (Appcndix H) incorporates thc specific requirements of the BAAL standard (BAL- 001-2). Include morc robust analysis regarding the west BAA winter peak load/rcsource balance and F)rtfolios to meet this peak bad; 2. l'rovide quantitative justilication tbr the planning resewc margin of l3 p€rcent: 3. Utilize the Ualancing Authority's Area Control Enor (ACIj) Limit (BAAL) NERC standard in tbrthcoming wind integration s dies, and confirm and demonsl.ratc that the study is based on implementation of the BAAL standard; 4. Use the samc regional haze assumptions when directly comparing portlblios. 32 Referencc IRP Requirement or Recommendalion How the Requlrem€nt or Recommendrtlon is Addressed in the 2019 IRP 4. Regional haze compliance is embedded in the portfolio-developmelt process.'l'op performing portfolios reflected in PaciliCorp's 2019 IRP rellecl corsistent regional haze compliance rcquirements. PACTFTCoRP - 2019 IRP App[NDrx B IRP R-ucuLA roRy CoMPLTAN( E Paciticorp must: I . Provide an updated ecomrmic analysis with the request tbr acknowlcdgemcnt olthc linal shortlist from the 2017R RFP 2, trpdatc its analysis ofthe Energy Vision 2020 projects as parl ofits 2017 IRP Update. including any changes resulting liom the 2017R RFP or changes to critical assumptions, such as availability of tax credits corporate ta-\ rate, then-curcnt cost- and-perfbrmance data fbr repowered wind rcsources, cost-and-perlbrmance data ftom the 2017R RFP final shortlist, and cost assumptions tbr the transmission projects; and 3. Providc quarterly updatcs to lhe Oregon PUC and StatTas devckrpmcnt ofthe prolects chosen in the 2017R RFP and the transmission projects proceed {through the dalc thc prt)irlcts so into service). l. RFP informatbn was provided in the 20t7 IRP tlpdate, Chapter 7 (Dnergy Vision 2020 Updatc). 2. An update on Energy Vision 2020 was providcd in the 2017 IRP Update, Chapter 7 (Energy Vision 2020 Update). Order No. l8- 138, Appendix A p. 19 Order No. l8-138, Appcndix A p. 20 PaciliCorp must provide the Dave Johnston carly rctirernent iransmission analysis to the Oregon PUC anrl parties in LC 67 once the third-party rcview and validation has becn finalized. Order No. l8-138, Appendix A p. 20 t. PacifiCorp is to repo back in ils 2017 IRP tlpdate as to the currert ard lirrccastcd use of liont oflicc transactions through 2036 and any changcs in assumptions impacting fro[t olfice transaction use froln thc initial liling olLC 67 in April 2017. 2. PaciliCorp should repeat its shrdy of trading hub liquidity and also thc market reliance risk analysis offtont ollicc transactions prior to thc 2019 IRP. 3. For the 2019IRP, ifa geueratingl resource is included in the prefencd porttblio with an associated action itcm, trcn PacifiCorp will rcport on the cost and risk tradeoUi between the prctbned portlblio and altemativcs that do not include a generating resource. l. See 20l7IRP Update Filing. Chapter 5 lModeling and Assumptrons Upda{e). 2. See 2019 IRP, Vulumc , Appendix J (Western Resource Adeqrncy Evaluation) for an updated study. 3. See Volume I, Chapter 8 (Modeling and Portfolio Selection RcsulLs). l. PacifiCorp. in coordination with statland the Energy Trust ofOregon (ETO) will conduct an analysis before the 2019 IRP that identilies and l. PacifiCorp conductcd an analysis in cooperation with Navigant and thc Encrgy Imst of C)regon as part ofthe 2019 IRP analysis. The report with recommendations was prcsentcd at public-input Order No. l8-138. Appendix A p. 2l as modified by Order No. l8-420 33 Referencc IRP Requircmcnt or RecommeIldation Eow the Requirement or Recommendation is Addressed ln the 2019 IRP 3. Pacil-rCorp has provided quarterly updates in tlocket No. l.C-70 starting July I l, 2018. Subsequent updates werc providcd on October 30, 201tt, January 7, 2019, May 7, 2019 and August 2, 2019. See 2017 IRP tJpdatc Filing, Chapter 6 (Portlblio Development). PA(rrrCoRP - 2019 IRP AppEr\'Drx B - IRP R.LGULAToRy CoMPLTANCE compares the otrgoirtg difl'erences between Fl'l O and PacifiCorp's near to long-ienn energy etlciency forecast with ETO's actual achicved savings. PacihCorp will rcpr)rl on $is analysis. including any recommendations to both organizations regarding forecast improvements, in the 2019 IRP, PaciliCorp will present thc analysis as a public input IRP meeting. 2. Early in the public input process frrr the 2019lRP, prior to linalizing energy efficiency supply curves, PaciliCorp will hold a I)SM technical workshop to rcvicw and rcceive input regarding how the company models energy elliciency potential in the IRP and supporling studies such as the Conservation Potential Asscssmcnt- meetings (see below) and is available on PacifiCorp's website. 2. PacifiCorp provided dcmand-side management workshops as part otils 2019 IRP public-input mcctings on June 28-29, 20t8 and July 12, 2019. Order No. I tl-l3tl, Appendix A p. 2l PacitiCorp will perform 25 system optimizer (SO) runs, olte for each coal unit and a base case. PacifiCorp will surrunarize the rcsults providing a table of the difi'erence in the PVRR resulting from the early retirement of each unit. an itemized list ofcoal unit rctirement cost assumptions used itr each SO run. and a list ofcoal units thal would free up transmission along the path from the proposed Wyoming wind projects ifretired. Paci[rCorp is to provide this information by June 30, 2018. Ifthere is a disputq about rnodeling in the meantime, PacifiCorp, stafl'and parties should lirst attempt to rcsolvc it informally, but ifthat fails, statf may report back to thc Oregon PUC at a public meeting before the 20l9lRP is tiled. An Oregon PUC commissioner workshop will likely be scheduled to review this analysis once it is complete. PacifiCorp provided the requested information in a public-input meeting preseutation on Junc 28-29, 2018, and the prcsentation is available on the company's website. PacifiCorp presented an update on its coal srudies at a special mccting at the Oregon PUC on December 18,2018. Order No. l8-138. Appendix A p. 2l PacifiCorp will continue to modcl the assumption that EPA regional haze litigation against the company is succcssl.ul and that PacifiCorp will be required to comply with the cunent requirements of the Slate lmplcmentation Plan (SIP) and Federal Implementation Plan (FIP). PacifiCorp has included two Regional Hazc scenarios in the 2019 IRP. See Volume II, Appcndix M (Case Study Fact Sheets) lbr discussion on specilic Rcgional Haze assumptions Order No. l8-138, Appendix A p. 2l In the IRP Update PaciliCorp will explain thc rc'avrns for thc (somelimes) low conelation in the short-term tbrecast. Scc 2017 IRP Update Filing, Chapter 5 (Modeling and Assumptions tlpdatc). 34 Refcrcnce IRP Requirement or Recommendalion How the Requirement or Recommeodetlon ls Addressed in the 20l9IRP PACTFTCoRI 20l9IRP App[NDIx B - IRP R-TGULATORy CoMPI-TANCE In the IRP Update PacifiCorp will model natural gas alrd storage for meeting flexible reserve study needs. See 2017 IRP Update Filing, Chapter 5 (Modeling and Assumptioos Update). Order No. l8- 138, Appendix A p. 22 Ortlcr No. l8-138. Appendix n p. 22 PaciliCorp will work with stalland partics to advance distributed energy resource lbrecasting and representation in the tRP, and define a proposal for opcning a distribution syslem planning iDvestigation. In the 2019 IRP, PacihCorp discussed distributed energy rcsources at its July 26-27,2019 public- input meeting along with a workshop specilic to cnergy storage. PaciliCorp will work with stall and parties to explore the use of AMI dala in future IRPs. AMI data will furthcr cnhance the granularity of load forecasting and PacifiCorp will cotrtinue to evolve in its IRP process as more AMI data becomes available. PacifiCorp. staffand panies should discuss a potential study of the capacity value ofrcncwing QFs. and statf shall bring this issue to a public mceting hclorc thc 20l7lRP Update PacitiCorp discussed with Stall and parties over conlcrence call and agreed to evaluate its 2019 IRP prefencd porttblio load and resource balance with the assumption ofQF renewal and provide that inlormation subsequent to the filing ofthc 20l9 tRP. Order No. l8-138, Appcndix A p. 22 (hder. Docket No l5-0-15-04. p.l8 If PaciliCorp plans to use the Systcm Benelit Tool type oftransmission analytical tool in future IRPs, PacitiCorp should introduce and vet thc ttxrl in an IRP workshop setting prior to utilizing the tool. The System Benefit Tool is not used in the 2019 IRP, Order, Docket No. l5-035-04. p.l9 Encowage PacifiCorp in future IRP processes, to provide a stronger demonstration of the rcasonableness of the range ofrenewable resource costs analyzed. PacitiCorp discussed irs 20l9IRP supply-side rcsource table and inpuls at the October 9, 2018 public-input meeting.'lhe supply-side resource table was updated based on staksholder f'eedback. Ordet l)<rcket No. l5-035-04, p.20 Direct PacifiCorp to identi$ the amount ofdistributed gsneration in lhe baseload forecast in its load and resourcc table, as it &rcs for existing DSM and cunailrnent. Scc Volume I, Chapter 5 (Load and Resourcc Balancel. which breaks out private generation in the same manner as DSM and intemrptible load curtailment- See Volume tl, Appendix J (Western Resource Aduluacy Evaluation) for an evaluation ofmarkct depth, and also cases studied to assess impacts of higher market prices providul in Volume I, Chapter 8 (Modcling and Portlblio Selection Results). Also refer to acquisition path analysis lbr cootingcrcics ir Volume I, Chapter 9 (Action Plan). Order, Docket No l5-035-(M. p.2l Direct PacifiCorp to continue to evaluatc the depth ofthe westeul wholcsale markct, and to use sensitivity cases and aqquisition path analysis, including dcvclopment of a contingency plan, to monitor the I'casibility of long-tcrm reliance on Front Ollice TraNactions to meet ncar-tcrm load growth. Scc Volume II, Appendix I (Plarming Rescwc Margin Smdy). The stndy concludes with a planning criteria that meets one day in l0 year planning targets at thc lowest reasonable cost. Ordcr. I)ocket No l s-035-04. p.2l Recommend contitrued analysis of the planning reserve margiD tr l'uturc IRPs using rcsults liom both loss olload probability studies and analysis ofthe traJcol'lls bctwecn rehabilrty and cosl. Utah 35 Refcrcnce IRP Requlrement or Recommendatlon IIow the Requirement or Recommendaaion iS Addressed in the 2019 IRP Order No. l8-138, Appcndix A p. 22 PACTFTCoR" - 2019 IR-P Order, Docket No t5-035-04, p.25 Analysis behind Near-'l crm and Inng- Term Resource Acquisition Paths Cl ablc 9.3 in the 2015 IRP) could bc improved in terms ol'idcntilying potential exogenous changes tlut would cause a signilicant changc in acquisitio[ path. Encourage PacifiCorp in firture IRPs to further del'me the critical contingencies it is monitoring and identily the rnagnitude of changes that would be requted to polentially trigger movement to any of thc dill'erent paths listcd in the table. Order, Dockqt No l5-035-04, p.3l Remind PaciliCorp r)f the requirement to future lRPs t() prcscnt lhe Business Plan as a sensitivity case. IfPacilicorp has substantive obicctions to this requirement, PaciliCorp should file a motion lirr Commission action within 90 days ofthis ordcr explaining the obiectiun and requesdns relief. Pleas€ rel'er to the Sensitivity 5-06- prcscnted in Volume I, Chapter 8 (Modeling and Portfolio Seleclion Results) consistcnt with the Order in Docket No. l5-035-04. Order, Dockct No 17-035-16.p.22 Encourage PaciliCorp and stakcholders to review recommendatiols of0rc t)PIJ on process at the start ofthe 2019 IRP process. PaciliCorp mct with Utah stakeholders on August 9, 2018 and discussed recommendations ofthe Division of Public t.ltilities (DPLD. PaciliCorp made best cfForts to implement recommendations for timely materials and also shortened the lunch break and shrted earlier on the secoml day of public-input meetings. Order. Docket No l7-035-16, p.3l Encourage all parties to communicatc in advance ofthe 2()19 IRP about whether a training sessiofl on IRP capacity expansion and stochastic models would be appropriate and helpful. There is a distinction betwccn requiring PacifiCorp to create opportunity for public involvemcnt as rcquired by the Guidclines, and requiring PacifiCorp to corduct analyses on behalf of parties. PacihCorp held a modeling workshop as part of iLs June 28-29, 2018 public-input meeting and providcd information on its Systcm Optimizer model and Planning and Risk model. PacifiCorp providcd details on its models, functiomlity and planning assumptions throughout the public-input mei:ting process. Order. Docket No. l7-035- I6. p.15 To satisfy Guideline 3, any changcs to the DSM modeling assumptions must be circulated during the IRP developmert process. PacifiCorp provided a demand-side management workshop as pan ofa public-input meeting June 28-29, 2018. An additional workshop was held July 12, 2019. PacifiCorp discussed updates related to demand-side managemcnt modeling throughout its 2019 IRP process. Order, Docket No l7-035-16, p.37 PaciliCorp cornmits to conduct a workshop spccilic to c[ergy storage as part of the 2019 IRP public input proccss prior to Iinalizing thc supply- side rcsource table inputs lbr banery and energy storage. PacifiCorp held an energy storage workshop August 30, 2018, and the presentation is available on the company's websitc. Order. Docket No l7-035- 16, p.43 Expect PacifiCorp and stakeholders to review the DPLI's recommendations on transmission modeling at the start ofthc 2019 IRP process. PaciliCorp met with tltah stakeholde$ on August 9, 2018 and discussed recommendations ofthe Division of Public Utilities (DPtl). Pacificorp provided a trarsmission overview artd update as 36 APPENDX B _ IRP REGULAToRY COMPLIANCE Reference IRP Requireme[t or Eow the Requirement or R€commendrtion ir Addrcss€d h the 2019 IRP \(( ir(,lrrr\rlrrnr prrth rrrrrrlr.i. Iirr urrrrlrrrtcrrrics rll VohLurc I. Chnpter 9 (Action Plan). PACr[rCoR] - 2019 IRP AppENDrx Il - tRP REcuLAioRy CoMpLrANc[ part ofa public-input meeting September 27-28, 20r8. uE-140546, Acknowledgement Letter, p.l Fincouragc thc company to continue the practice ol'including data discs with dre filing in future IRP lilings. Data discs have provided as part ofthe 2019 IRP filing. uE-140546. Acknowledgcmeut Letter, p.2 Encourage the company to continue to cvaluate how its method ofdcvcloping capacity valuc ol' renewable resourccs compares to the ellective load carrying capability mcthod on which it was based, to ensure that lhc company's modcl is yielding accuate results. See Volume ll, Appendix N (Capacity Contribution Study), analyzing updated hourly protiles and transmission availability impacts to determine ell'cctiveness in meeting system load.'l'he 2019 IRP includcs winter peak (in addition to summer peak; in ils assumptirrns. allowing enhanced insight into solal penetration concems. uE-140546. Acknowledgement Letter, p.4 The cost inpacts in S-10 in the 2015 IRP were on a system basis and the commission would like to see them on a balancing authority area basis. Rcquests the analysis be redonc in the 20 I 7 IRP and that lhc company use inputs consistent with the stafl'MSP powcr flow data or explain why different itrputs are more appropriate. Rcquest that the company incorporate the balancing arca analysis in all future IRPs. PaciliCorp plans to incorporatc this sensitivity as part oiits 2019 IRI Update. Pacifi Corp incorporated flexible ranrping procuement diversity savings fiom the DIM in its llcxible Reserve Study. Sec Volume II. Appendix F (Ilexible Rcscrve Snrdy). uE-r40546. Acknowledgement Letter, p.8 lxpect examination ofJim Bridger and Cotstrip Units 3 & 4 puriuant to specific questions to be addressed in the 2019 IRP. PacitiCorp plans to incorporate responses lo these questions as part of its 20 I 9 IRP tlpdate pursuant to thc Washitrgton Utrlitres and Transponation Commission's July 3, 201 9 letter. u Fr- 16035 3. Acknowlcdgement Letter Attachment, p.4-6 til-r-160353. Acknowledgcment l-elter Attachment, p.6-7 Balancing Area analysis in all future IRPs that includes a west conrol area and an east control area analysis with a robust desmiption ofthe modeling interaction betwee[ the two discrcte systems. See Volume II, Appendix J (Westem Resouce Adequacy Evaluation). uE-r60353. ncknowledgement Letter Attachment. p,8 Expect the compaly to incorporate principles in thc commission's policy statement on energy storage in the 20l9 tRP. Scc Volume II, Appendix Q (F)nergy Storage Potential Evaluation)- rrE- 160353. Acknowledgement Letter Attachment. p 8-9 Flxpcct the company to provide a market reliancc risk assessment in the i[r-xn*rfl*iux*uil;ti risk that can be folded into thc IRP analytical framcwork. See Volume I[, Appendix J (Westem Resourcc Adcquacy Evaluation), PaciliCorp's 2019 IRP also included analysis ofthe impact ofhigher market priccs on selecl cases (FO I' cases). See Volume I, Chapter 7 (Modeling and Pordblio Evaluation Approach) and Chaptcr 8 (Modeling and Portlblio Selection ResulLs). Washington 37 Reference IRP Requirement or Recommendation How the Requirement or Recommendetion is Addressed in the 2019 IRP Encourage the company to continue to intcgrate the HIM into its IRP model, in partic[lar to devckrp modeling capability to capnre how difi'erent resources with different generation proliles would interact with the EIM, based on the company's expericnce with the market. PA(lr.rCoRP - 20l9IRP ArpLNDrx U - IRP Rr.GLrLAToRy CorlrpLrAN( E Table 8.3 -Public Utili Commission IRP Standard and Guidelines UE-160153. Acknowledgcment Lcttcr Attachment. p.9- l0 In future IRPs, the company should more prominently display the Quick Rel'e rence Guides included in Appendix M of its 2017 IRP. PacitiCorp expanded Volume II, Appendix M (Case Fact Sheets Overview) to include more portft,lio specilic materials that were included in public-input meeting presentations thoughout the course ofthe 20l9lRPprocess. Discussion in Volume I oftre 2019 IRP draws more direct references to Volume Il, Appendix M (Case Fact Sheets Overview) l'or simplified navisation. uE- 160353. Acknowledgement Letter Attachment. p.l0-lI ln funre IRPs, the company should incorporate the cost ofrisk of futurc grcenhouse gas regulation in addition to known regulations in its prefened pordblio. 'fhe cost estimate should come tiom a comprehensive, pccr- reviewed estimatc of the monetary cost of climate change damages. produced by a reputrble organization. WIITC suggests using the lnteragency Working Group on Social Cost of (ireenhouse Gases estimate with a three percent discount rate. The company should also continue to model other higher and lower cost estimates to undeGtand how the resource portlblio changur based or these costs. In the 2019 IRP, PacifiCorp assumed a Cor price starting h 2025 in its base case analysis. I1 also perlirrmed assessments ol'certain top pertbrming F)rttblios under a low gas/no CO2, a high gaVhigh COr, and a social cost ofcarbon pricc-policy sccnario that was developed using estimates by the lnteragency Working (houp on Social Cost of C,reenhouse Gascs. See Volume I, Chapter 8 (Modeling and Pordblio Selection Results). trE- 160353, Acknowled8ement Letter Attachment, P.l I The company should dcvelop a supply curve ofemissions abatcment and include this cost curve in the 2019 IRP.'Ihe analysis should ideutily all programs and technologies reasonably available in the company's service area, then use best available infbrmalion k) estimate the amount of emissions reductions each option might achicvc, and at what cost. PacifiCorp will use inlirrmation from this analysis as part ofits 2019 IRP Updare. The Wyoming Public Scrvice Commission acccpted Rocky Mountain Power's 2017 Ifltegratcd Resource Plan (Docket No. 20000-5 l2-EA- t 7) without flrther action on fte rnafter pursuant to action taken at its open meeting on November 20, 2017 and by Letter Order issued January 29, 2019. I .a.l All resources must bc cvaluated on a consistent and comparablc basis: All kno&n resourccs for meeting the utility's load should bc considered, inctuding supply- sidc options which fr^-us un tie geoeration. purchase and transmission ofpower - or gas purchases, transportation, and stora8e - and PaciliCorp considere'd a wide range ofresources including renewables, demand-side mnuagement, energy storage, powcr purchases. thermal resources, and transmissior. Volume I, Chapter 4 (Transmission Planning), Chapter 6 (Resource Options), and Chapter 7 (Modeling and Portfolio Evaluation Approach) document how PaciliCorp developed these resources Guideline l. Substantive Requircments 38 Referencc IRP Requirement or Rccommendation How the Requirement or Recommendation is Addressed in the 2019 IRP Wyoming No,Requirement IIow the Guideline is Addressed in the 2019 IRP PAcTFICoRP -20l9IRP APPENDH B -IRP R.LGULATORY CoMPLIAN(.E and modeled them in its portltrlio analysis. All these resources wcre established as resource options in the company's capacity expansion optimization model, Systcm Optimizer, and selccted by the model based on load rcqurr..-mcnts. relalive cconomics. rcsource size. availability dates, and othcr lhctors. demand-side options which lbcus on conservation and demand responsc. All portfolios dcveloped with System Optimizer were subjected to Monte Carlo production cost simulation. These portfolios contained a variety ofresource types with diflerent fuel typcs (coal, gas, biomass, nuclear fuel, "no fucl" renewables), lead-timcs (ranging from t'ront ofhce transactions to nuclear plants), in-sewice dates, operational livcs, and locations. See Volumc l. Chapter 7 (Modeting and Portfolio Evaluation Approach), Chapter 8 (Modeling and Portfolio Selection Results), and Volume II, Appendix K (c^apacity Expansion ResulLs l)ctail) atrd Appetrdix L (Stochaslic Simulation Results). I .a.2 All resources must be evaluated on a consistent and comparable basis: Utilities should compare different rcsource fuel types. technologies, lead times. in-servicc dates, durations and locations in portlblio risk modeling. PacifiCorp lirlly conplies with this requirement. The company developed generic supply-side resource atlributes based on a consistent charactcrization methodology. t'or demand-side resourccs, the company used the Applied Energy Group's supply curve data developed for this IRP for reprcsentation of DSM resources. The study was based on a consistently applied methodology for determining tcchnical, market, and achievable DSM potentials. All portfolio rcsources were evaluated using the same sels ofpdce and load forecast inputs. These inputs are documented in Volume I, Chapter 5 (l-oad and Resource Balance), Chaptcr 6 (Resource Altematives), and Chapter 7 (Modeling and Portfolio l.)valuation Approach) as well as Volume U, Appendix D (Demand-Side Management Resources). La.3 All resources must be evaluated on a consistent atrd comparable basis: Consistent assumptions and mcthods should be used for evaluation oiall resourccs. PacifiCorp applied its nomiml after-tax WACC of 6.92 percent to discount all cost stleanrs. 1.a.4 All resources rnust be evaluated on a consistent and comparable basis: The aller-tax marginal weipfrted-aveBge cost of capital (WACC) should be used to discount all future tesource costs. Each ofthe sources ofrisk identihed in this guideline is treated as a stochastic variable in Montc Carlo production cost simulation with the exception ofCO: emission compliance cosls, which are treated as a scenario risk and evaluated as part of a CO2 price assumption and a no COr, a high COr, and a social cost ofcarbol price-policy scenario t'or specilic studies. Sec volume I, Chapter 7 lModeling and Portfolio Flvaluation Approach) and Volume I, Chapter 8 (Mtxleling and Portfolio Selection Results) t.b.l Risk and uncertainty must be considered: At a minimum, utilities should address the following sourccs ol'risk and uncenainty. l. Electric utililies: load requirenreots. hydroelectric gencration, plant fbrced outages, tuel prices, elechicity prices, and costs to comply with any rcgulation ofgreenlouse gas emissions. 1.b.2 Risk and uncenaittty must be considercd: t.ltilitics should idcntify in their plaus any adr.litional sourccs ol' risk anrl unccrtainry. Resource risk mitigation is discussed in Volume I, Chapter 9 (Action Plan). Rcgulatory and tinancial risks associated with resource and transmission investmetrts are higl ighted in several areas in the IRP document, including Volume I, Chapter 3 ( t'he 39 No.Requirement IIow the Guideline is Addressed in the 2019 IRP PA(x,rCoRP-2019IRP APPENDx B IRP REGTTLA,I oRY CoMPI,IANCF, Planning Environment), Chapter 4 (Transmission), Chapter 7 (M<xlcling and Portfolio Flvaluation Approach), and Chapter 8 (Modeling and Portfolio Selection Results), l.c The pdmary goal must be the selection ofa portlblio ofrcsources with the best combination ofexpected costs and associated risks and uncenainties lbr the utiliry and its customers ("bcst cost/risk ponlolio"l. PacifiCorp evaluated cost/risk tradeofli lirr each of the portlblios corsidcred. See Volume I, Chapter 8 (Modeling and Portfolio Selcction Results), Chapter 9 (Action Plan), and Volume II, Appendix K (Capacity Expansion Rcsults Detail) and Appcndix H (Stochastic Paramctcrs) for the company's portfolio costlisk analysis and determination of the prel'crrcd portfolio. l.c.l 'I}lc planning horizon tbr analyzing resource choices should be at least 20 years and account for end cffects. Utilities should consider all costs with a reasonable likelihood ofbeing included in rates over t}c long term, which extcnG beyond the planning horizon and the life ofthe resource. PaciliCorp used a 2O-year study period (2019-203t1) for portfolio modeling, and a real levelized revcnue requiremcnt methodology lbr tleatmerlt ofend et]ects 1.c.2 tltilities should use present value of revenue requirement (PVRR) as the key cosl mel.ric. The plan should include analysis ofcurrent and estirnated tuture costs for all longJived resources such as power plants, gas storage lhcilitics, and pipelines, as well as all short- lived resources such as gas supply and short- team power purchases. Volume I, Chapter 7 (Modcling and Portfolio Evaluation Approach) provides a description ofthe PVRR methodology, 1.c.3.I 'lir address risk, the plan should include, at a mrnlmutrt: l. Two measurcs of PVRR risk: one that measures the variability ofcosts and one that measures the severity of bad outcomes- PaciliCorp uses the standard dcviation ofstochastic produclion costs as thc measure ofcost variability. Ilor the severity ofbad outcomes, the company calculates several measures, including stochastic upper-tail mcan PVRR (mean ofhighest tl[ee Montc Carlo iterations) and the 95'r' percentile stocha,itic production cost PVRR, t.c.3.2 To address risk. the plan should include, at a minimum: 2. Discussion of the proposed use and impact on costs and risks ofphysical and financial hedging. A discussion on hcdging is provided in Volume I, Chapter 9 (Action Plan). 1.c.4 '[ hc utility should explain in its plan how its resource choiccs appropriately balance cost and risk. Volumc I, Chapter 8 (Modeling and Ponfolio Selectiotr Results) summarizes the resulls of PacitiCorp's cost/risk tradeol'l'analysis, and describcs what criteria the company used to determine thc best cost/risk porttblios and the prcfcned portfolio. l.d PacifiCorp considcred both crurent and potential state and t'ederal ererBy/pollutant emission policies in portfolio modeling. Volume I. Chapter 7 (Modelin€i and Portfolio Evaluation Approach) describes the decision process used to dcrive portfolios, which includes consideration ofstate and federal resource policies and regulations that arc summarized in Volumc I, Chapter 3 (The Planning Environment). Volume [, Chaptcr 8 (Modeling and Portfolio Setcction Results) provides the results. Volume [, 40 No.Requirement How the Guideline is Addressed in the 2OI9 IRP The plan must bc consistent with the long-mn public interest as expressed in Oregon and federal energy policies. P^crFrCoRP - 2019 IRP AppENDrx U - IRP RrculAroRy CoMPLTANCE Chapter 9 (Actior Plan) presents an acquisition path analysis that describcs resource strategics based on regulatory trigger events. 2.a 'lhe public, which includes othcr utilities, should be allowed significant involvement in thc preparation ofthe [RP. Lrvolvement includes opportunities to contribute inlirrmation and ideas, as wellas to rcccivc inlormation. Parties must have an opportunrly to make relcvant inquiries ofthe utility fomrulating thc plan. I)isputes about whcther intbnnation requests arc relevant or unrcasonably burdeDsome, or whelher a utility is being propcrly rcsponsive, may be submined to the PtiC tbr resolution. PaciliCorp fully complies with this requirement. Volume I, Chapter 2 ([ntroduction) provides an overview ofthe public process, all public-input meetings held for the 2019 IRP, which are dor;umented in Volumc II, Appendix C (Public Input Process). PacifiCorp also madc use ofa Stakeholdcr Fccdback Form for stakeholders to provide comments arrd offer suggestions. Stakeholder Feedback Forms along with thc public-input mecting presentations arc available on Pacifi(orp's webpaple at: www.paci fi corp.cofi/e[ergy/integmted-resource- lan.html 2019 IRP Votumes I and II provide non-confrdential inlbrmation tsed for portfolio evaluation, as well as other data requested by stakcholders. PacifiCorp also provided stakcholders with non-confi dential inlbmratiort to supp{)a public meeting discussions via ernail ard in response to Stakeholder Feedback Iorms Data discs will be available with public data. Additionally, data discs wiih conlidential data will be provided to appropriate panies through use of protcctive order l8-2 16. 2.b While confidential information must be protected, the utility should make putrlic, in its plan, any non+onfidcntial inlbnnation that is relevant to its resource evaluation atrd actiotr plan. Conlidential infbrmation may be protected tlrrough usc ola protective order, through aggregation or shielding of data, or through any other mechanism approved by the (hegon PUC. 2.c PacifiCorp distributed &aft IRP rnaterials for extemal review throughout the process prior to each ofthe public input meetings and solicitcd/and received l'cedback at vaious times when developing the 20 I 9 IRP. The matcrials shared with stakeholders at thesc meetings, outlincd in Volune I Chapter 2 (lntroduction), is consistert wil.h nraterials presentcd in Volumes I and ll olthe 2019 IRP report. PacifiCorp requestcd and responded to comments from stakeholders when establishing modeling assrunptions and throughout its portfolio-development process and sensitivity dclinitions. Thc utility must provide a draft IRP lor public review and comment prior to filing a final plan with the Oregon PUC. 3.a A utility must file an IRP within two years of its previous IRP acknowledgment order. lf the utility docs not intend to take any significant resource action for at lc&st two years after its ncxt IRP is due. the utility may rcquest an extension of its filitrg datc lrom the Oregon P(rc. 3.b This activity will be conducted subsequent to liling this IRP. 'nre utility must presenl thl: rcsults of its filed plan to thc (hcgon P[ IC at a public mecting prior to the deadline for writtcn public commcDt. Guidelinc 2. Procedural Requiremenls Guideline 3r Plan Filin& Relien, and Updates 41 No.Requirement How the Guideline is Addressed in the 2OI9 IRP 'I1te 2019 IRP complics with this requircment. 3.c Commission staffand parties should complete their comments and recommendatious within six months of IRP liling. This activity will be conducted subsequcnt to filing this IRP. 3.d The Commission will consider comments nnd recomnendations on a utility's plan at a public meeting belbrc issuing an order on acknowledg'ment. The Commission may provide the utility an opportunity to rcvise the IRP belbre issuing an acknowledgment order. 'l'his activity will be conducled subsequent to liling this IRP. 3.e The Commission may provide direction to a utility regarding any additional analyses or actioN that the utihty should undertake in its next lRP. Not applicable. 3.1 (a) Each energy utility must submit an annual update on its most rccently acknowledged IRP. 'l-he update is due on or before the acknowledgm.ent order anniversary date. Once a utility anticipates a significant deviation tiom its acknowledged IRP, it must file an updatc with the Oregon PUC, unless thc utility is within six months of liling its next IRP. 'l'he utility must sunrrrnrize the update at an Oregon PUC public mccting. The utility may request acknowledgnrent of changes in proposed actioru identified in an update. Not applicablc to this tiling; this activiry will be conducted subsequent to liling this IRP. @ 3.9 4.a Nd applicablc to this tiling; this activity will bc conductcd subsequent to liling this IRP. 'I hc purpose of this table is to comply with this guideline. Unless the utility requests acknowledgment of changes in proposed actions, the annual update is an inlbnnational filing that:o Describes what actions the utility has taken lo impleme'nt the plan, o Provides an assessment of what has changed since the acknowled5,ment order that allects the action plan to s€lect best ponfolio ol'resourccs. including changcs in such factors as load, expiration ofresourcc contracts, supply-side and demand-sidc resource acquisitions, resourcc costs, and transmission availability; and. Justifies any deviations from the acknowledged action plan. An explanation ofhow the utility met each of thc substantive and proccdural requirements. 4.t)PacifiCorp dcveloped low, high, and extreme peak temperature (one-in-twcnty probability) krad growth ftrrccasts for scenario analysis using the System Optimizer model. Stochastic variability of loads was also captured in the risk analysis. See Volume I, Chapters 5 (l.oad and Resourcc Balance) and Chapter 7 (Mtxleling and Portfolio Evaluatior Approach), and Volume II, Appendix A (l,oad Forecast Detail) lbr load foreca{ inforrnation. Analysis ofhigh and low load growth scenarios in addition to stochastic load risk analysis with an explanation ol-major assumptions. PACTTTCoRP - 2019 IRP AppENDx B - IRP RECTJLAToRy CoMPLTAN('E 42 No.Requirement How the Guideline is Addressed in the 2019 IRP AppEr..Drx ll - IRP REcuLAroRy C'oMPLTANCE 4.c See Chaptcr 5 (Resource Needs Assessment) for dctails on annual capacity and energy balances. Existing hansmission rights arc rellected in the IRP model topokrgies. Future trarsmission additions usetl in analyzing portfolios are summarized in Volume I, Chapter 4 ('liansmission) and Chapter 7 (Modeling and Ponfolio l'lvaluation Approach). For electric utilities, a determinatior ofthc levels ofpeaking capacity and energy capability expccted lirr each year ofthe plan, given existing resourccs; identification of capacity and energy needed to bridge the gap between expcctcd loads and resources; modeling ofall existing transmissioo rierrts, as well as future trammission additions associated with the resource portlblios testcd. Not applicable.4.d For gas utilities only Volume I, Chapter 6 (Rcsource Options) idcntifies drc resources included in this IRP, and provides their detailed cost and perlbrrnance attributes. Additional information on energy clliciency resource characteristics is available in Volume II, Appendix I) (Dernand-Sidc Management Resources) ref erencing additional inlbrmation on PaciliCorp's IRP website see lbotnotc 3 oithis Appendix B. 4.e ldcntitication and estimated costs ofall supply-sidc and dcmand side resource options. taking into account anticipated advances in technology. In addition to incorporating a 13 percent planning rcserve margin for all portfolios evaluated, as supported by an updatcd Stochastic Loss o ,{,ad Sndy in Volumc II, Appendix L (Stochastic Simulation Results), thc company used sevcral measurcs to evaluate relativc porttblio supply rcliability. These merLsures (Energy Not Scrved and Loss ofLoad Probability) are described in Volume [, Chapter 7 (Modeting and Portfolio Evaluation Approach). 4.1 Analysis ol'mcasurcs thc utility intends k) take to provide reliable service, including cost-risk tradeofti. ldentification ofkey assumptions about the future (e.g., trel prices and environmental compliancc coss) and allcmalive scenarios considered. Volume I, Chapter 7 (Modeling and Portlirlio Evaluation Approach) dcscribcs the key assumptions and altemativc scerarios used in this lRP. Volume II, Appendir M (Case Study Fact Sheets) includcs summaries of assumptions uscd fbr each case delinition analyzed in the 2019 lRP. 4.h Construction ofa reprcscntative set ofrcsourcc portlblios to test various operating characteristics, resourcc types, fuels and sources. technologies. lead timcs, tn-servtce dates, durations and gcncral locations - systeru-wide or deliverd to a spccilic portion of the system. This IRP documcnts the development and results of portfolios designed to determinc resource selection under a variety ofinput assurDptioDs in Volume I, Chapters 7 (Modeling and Portfblio Evaluation Approach) and Chapter 8 (Modeling and Porttblio Selection Results). 4.i Evaluation of the perlirrmance of the candidatc portlolios over the range ofidentified risks and ulrcertainties. Volume I, Chapter 8 (Modeling and Portlblio Selection Results) presents thc stochastic portfolio modeling results, and describes portfolio attributes that explain relative dil'l'ercnces in cost and risk pertbnnance. Volume I, Chapter 8 (Modeling and Porttblio sclection Results) provides tables and charts with perfomrancc measure results, including rank ordering 4.i Rcsults ol'tcsting and rank ordering ofthc porttblios by cost and risk mctric, and interyretation ol' tho*- results. 4.k Analysis ofthe uncertainties associated with each portfolio evaluated. Sec rcsponses to l.b.l and I.b.2 atxtve 43 PA( rrrCoRP - 2019 IRP No.Requirement How the Guideline is Addressed in the 2019 IRP 4.1 Selection ofa portfolio that rcpresents the best combination ofcost and risk lbr the utility and its customers. See l.c above 4.rn Identification and explanation of any inconsistencies of the selected portfolio with any state and federal encryy policies that may aflect a utility's plan and any bariers te implemer(ation. This IRP is designed to avoid inconsistencies with state and federal energy policies therefore none are currently identified. @ E@ 4.n 6.a 5 An action plan with resouce activitics the utility htends to undertake ovcr the next two lo four yea$ to acquirc the identitied rcsources. rcgardless ol'whether thc activiry was acknowledged in a previous [RP, with the key attributes of each resource specilied as in portfolio testing. Portfolio analysis should include costs to the utility for the t'uel transportation and electric transmission required tbr each resource being considered. In addition, utilities should consider fuel transportation and electric transmission facilities as resourcc options. taking into account their value lbr making additional purchases and sales, accessing less costly resources in rcmote locations. acquirinB alternative fuel supplies, aud improving reliability. Each utility should ensure that a cons€rvation potetrtial study is conducted periodically for its entirc service tenitory. Volume I Chapter 9 (Action Plan) presents the 2019 IRP action plan. PacifiCorp evaluated four sensitivities on Energy Gateway lransmission project configurations on a consistent and comparable basis with respect to other resources. Where new resources would require additional tmnsmission t'acilities the associatcd costs were factoretl into fte analysis. Fuel transponation costs were factored into resource costs. A multi-statc demand-side mana8ement potential study was cornpleted in 2018, and those rcsults were incorporated into this plar. 6.t)'Ii) thc extent that a utility controls the level of funding for conservation programs in its scwice territory, the utility should include in its action plan all best cosVrisk portfolio comervati(D resources lbr meeting projected resotrce neeG. specifying annual savrngs targets. PacifiCorp's energy elficiency supply curves incorporate (hegon resource potential. Oregon polsntial estimatas were provided by the Energy Trust oI Oregon. Scc the denr,and-sidc rrsource section in Volume I, Chapter 6 (Resource Options), the results in Volume I, Chapter 8 (Modeling and Ponfolio Selection Results), the targeted amounts in Volume I, Chapter 9 (Action Plan) and the implemsrtatiol steps outlined in Volume II. Appendix D @SM Resources). 6.c 'lo the extent that an outside party administcrs conscrvatron pro€(ams in a ulility's service territory at a level of lunding that is beyond the utility's control, the utility should: l. I)ctcrmine the amount ol'conservation resources in the best cost/risk portfolio without regard to any limits on funding of conservation progmlns; and 2. Identify thc preferred pontblio and action plan consistent with thc outside party's projection of conservation acquisilion. See the responsc for 6.b above PACTFTCoRP - 2019 IR-P AppENDx B - IRP RTGULAToRy CoMpLTANcE No.Requirement How the Guideline is Addressed in the 2OI9 IRP 44 @ 8.a '7 Plans should evaluate dcmand response resources, including voluntary ratc programs, on par with other options for meeting energy, capacity, and transmis-sion needs (for electric utilities) or gas supply and transprtation needs (for nanral gas utilities). Basc casc and other compliance scenarios: The ulility should construcl a base-case scenario to rcflect what it considers to be the most likely regulatory compliance future for carbon dioxide (COz), nitrogen oxides, sulfi.u oxides, and mcrcury emissions. 't}re utility should devclop scveral compliancc scenarios ranging from the present CO2 regulatory level to the uppcr reaches ofcrcriiblc proposals by govcming entities. [ach compliancc scenario should include a timc prolile ofCO2 compliance requirements. 'fhe utility should identify whether the basis ofthose requirements, or "costs," would be COz taxes, a ban otr certain types ofresources, or COz caps (with or without llexibility mechanisns such as an allowance for credit trading as a safety valve). The analysis should recognize srgnificant and important upstream emissions that would likely have a significant impact on resource decisrons. Each compliance scenario should maintain logical consistency, to the extent practicable, between the COz regulatory r€quirements and other key inputs. PacifiCorp evaluated demand reslxrnse resources (Class I DSM) o[ a consistent basis with other resources. In the 2019 IRP, PaciliCorp modeled a price on COz starting in 2025. Volume ll, Appendix L (Stochastic Simulation Results) provides thc stochastic mean PVRR versus upp,cr tail mean less stochastic mcan PVRR scatter plot diapgaIlr5 that lbr a broad range ofportfolios dcvcloped with a range ofcompliancc scenarios as summarized in 8.a above. The company considers end-effects in its use otReal Levelized Revenuc Requirement Analysis, as summarized in Volume I, Chapter 7 (Modeling and Portlblio Evaluation Approach) and uses a 2O-year planning horizon. Eady retircment and gas convenion altematives to coal unit environmental investments were considered in the development ofall resource porrfolios. ll.b Testing altemative portfolios against the compliauce scenarios: The utility should cstimate, under each ol'the compliance scenarios, the present value revenue requirement (PVRR) costs and risk measures, over at lcast 20 years, li)r a sct olreasonable altemative pordolios from which thc prcl'erred portfolio is sclected. lhc utility should incorporate end-eftbct considerations in the analyscs to allow for comparisons ofponfblios containing resources with economic or physical lives that cxtend bcyond the planning period. 'l he utility should also modifu projectcd lil'etimes as ncccssary to hr' consisteut with the compliauce scenario undcr analysis. ln addition, the utility should include, ifnraterial. sensitivity analyses on a range of rcamnably possible rcgulatory funues tbr nitrogen oxides, sullirr oxides. and mercury to funhcr intbrm the prel'crrcd portlblio selection. 8.c See Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) fbr a description of initial Triggcr Jnint analysis: 'lhe utility should identify at least oDe CO2 compliancc "tuming PACrrrCoR-P - 2019 IRP AppENDrx B IRP R-EGULAToRy CoMpr.rAN( [ 45 No.Requirement How the Guideline is Addressed in the 2OT9 IRP Guideline 7r Demand Responsc Sec Volume I, Chapter 7 (Modeling and Portlbtio l.lvaluation Approach). PACTFTCoRI - 20l9lR-P A.ppENDx B - IRP REGULA[oRy CoMPLTANCF. point" scenario, which, ifanticipated now, would lcad to, or "trigger" the selection oia portlblio ofresources that is substantially difl'ercnt from the prel'ened portlblio. 'lhc utiliry should develop a substitute ponfolio appropriate for this trigger-point scenario and comparc the substitute porttblio's cxpected cost and risk perlbnnance to that of the pret'errcd portlblio - under the base casc and cach ol'thc above (Ot compliancc sccnarios. The utility should providc ils assessment of whether a CO2 regulatory fun[e that is equally or morc stringent tha( thc rdentrfied lriggcr will be mandated. ponfolio-development definitions. Comparative analysis of thcss case results is includcd in Volume I, Chapter 8 (Modeling and Portfolio Selection Results) 8.d Orcgon conpliance ponlblio: Ifuone ofthe above portfolios is consistent with Oregon encrgy policies (including state goals lirr reducing greenhouse gas emissions) as those policies are applied to the utility, the utility should coNtruct the best cosl/risk portfolio lhat achreves that consistcncy, prcseDt its cosl and risk parameters, and compare it to those in the preferred and altemative portfolios. Several portfolios yield system emissions aligned with statc goals for reducing greenhousc gas emissions. These cases are summarized in Volume l, Chapter 8 (Modeling and Portlblio Selection Rcsults). t)An electric utility's load-resource balancc should exclude custr)mer loads that are ellbctively committed to service by an altemative electricity supplier, Oregon Docket UE 267 established a long-term opt out rption for eligible PacifiCorp customers. Going forward PacifiCorp will cease planning tbr customc$ who clcct direct-access servicc on a long-term basis (i.e. five-year opt out customers). l0 Multi-state utilities should plan their generation and transmission systems, or gas supply and delivery, on an inteBrated system basis that achieves a best cost/risk portfolio for all their retail customen. The 2019 IRP conforms to the multi-state planning approach as stated in Volume I, Chapter 2 under thc scction "The Role ofPaciliCorp's Integrated Resource Planning". The company notes the challenges in complying with multi-state integrated planning given differiug state energy policies and resource prel'erenccs- ll Electric utilities should analyze reliability within the risk modeling of the acnul portfolios being considered. Loss of load probabilily. exp€cled planning rescwc margin. and expecterl and wolsl-case unserued energy should be determined by year for top- performing porttblios. Natural gas utililies should analyze, on an integated basis, gas supply, transportation, and storage, along with demand-side resources, to reliably meet peak, swing, and baseJoad systcm requirements. Electric and natur,rl gas utility plans should demonstrate that the utility's chosen portfolio achieves its stated rcliability, cost and risk objectivcs. See the response to I .c.3. I above. Volume I, Chaptcr 8 (Modeling and Portfolio Selection Results) walk through the role ofreliability, cost, and risk measurcs in determining thc preferred ponfolio. Scatter plots of portfolio cost versus risk at different CO: cost levels were used to inform the cost/risk tradeolf analysis. Cuitlcline 9: Dircct Across Loads 46 No.Requirement How the Guideline is Addressed in the 2OI9 IRP Guideline l0: IIulti-state Utiliticr Guidcline I l: Reliahilitr PACTFTCoRP -20l9lRP AppENDIx B -IRP REGrrr-AToRy CoMPLIAN( E t2 Electric utilities should cvaluate distributed generation technologics on par with other supply-side resources and should consider. and quantily where grssihlc, the additional benefi ts of distributed gencration. PacitiCorp contractcd with Navigant to provide cstimates of expecled privale generation peDetration. The study was incorporated in thc analysis as a deduction to load. Scnsitivities looked at both high and low pe'netration rates for private generation, The study is included in Volume II, Appendix O (Private Gencration Study). l3.a An electric utility should, in its IRP: l. tdcntily its proposed acquisition suategy f'(x each resource in its action plan. 2. Assess the advantages and disadvantagcs of owning a resource instead ofpurchasing power from anolher party. 3. ldentify any Benchmark Resources it plans to consider in compctitive bidding. Chapter 9 (Action Plan) outlines thc procurement approaches for resources identified in the pret'erred portlblio. A discussion ofthe advantages and disadvantagcs of owning a resource instead ofpurchasing it is included in Chapter 9 (Action Plan). PacitiCorp has not at this time identified any specific benchmark resources it plans to consider in the competitive bidding process summarized in the 2019 IRP action plan. l3.b For utilities only l'orecast the Demard tbr Flexible Capacity: The elcctric utilities shall tbrecast the balancing rescrves needcd at diffcrcnt time intervals (e.g- ramping needed withtr 5 minutes) to respond to variation in load and intennittent renewable genemtion over the ?0- year planning period. See Volume II, Appendix F (Flexible Rcserve Study) 2 Forecast the Supply of Flexible Capacity: Itre electric utilities shall forecasi the balancing rcserves available at dillerent time intervals (e.g. ramping availablc within 5 mirutes) from existing generating resources over the 2o.y{)ar plar:ning pcrirxl. See Volurne Il, Appcndix F (Flexible Rescrve Study) 3 Evaluate Flexible Resources on a Consistent and Comparable Basis: In plarming to lill any gap between the d€mand and supply ol llexible capacity, the electric utilities shall €valuate all resouce options, hcluding the use ofEVs, ou a consistcnt and comparable basis. Sce Volume II, Apperdix f' (Flexible Reserve Study). Guidelinc l2; Distributcd Gcncration Guideline lJ: Resource Acquisition Flcrible Capaci(r' Rcsourccs Table 8.4 - Utah Public Service Commission IRP Standard and Guidelines I The Commission has the legal authority to promulgatc Standards and (iuidelines lbr integrated resouce planning. Not addrcssed; this is a Public Service Commission of tJtah responsibility- Procedural Issucs 47 No.Requirement How the Guideline is Addressed in the 2OT9 IRP Not applicable. I No, How the Standards and Guidelines are Addressed in the 2019 IRPRequirement APPENDD< B- IRP R.ECULAToRY CoMPLIANCD 2 lnlbrmation l,xchange is thc most reasonable method for developing and implementing integratcd resouce planning in t.ltah. Information exchange has been conducted thrcughout the IRP process. 3 Prudence reviews ofncw resource acquisitions will occur during ratemaking proceedings. Not an IRP requirement as the Commission ackrowledges that prudence reviews will occur during ratemaking proceedings, outside of the IRP process. 4 PaciflCorp's integrated resowce plandng proccss will be open to the public at all stages. The Commission, is staff. the Division, the Committee, appropriale Utah state agercies, and other interestcd parties can participate. The Commission will pursue a more active-directive role ifdeemed necessary, after formal review of the planning process. PacifiCorp's public process is described in Volume I, Chapter 2 (lntoduction). A description ofpublic- input mcctings is provided in Volume II, Appendix C ( Public Inpur Proccss). Public-input mecting materials can also be found on PaciliCorp's website at: www.pacifi corp.mr/energy/integrated-resource- plan/public-inpulprmess.html 5 Consideration of environmental extemalities and attendant costs must be included in the integrated resource planning analysis. PacifiCorp used a scenario analysis approach along with extcmality cost adders to model environnental extemalify costs. See Volume I, Chapter 7 (Modeling and Portlblio Evaluaion Approach) lbr a description ofthe methodology employed, including how Coi cost uncertainty is lhctored into the determination of relativc portfolio performancc through a base case plarming assumption and other price-policy sccnarios. 6 The integratcd resource plan must cvaluate supply-side and demand-side resources on a consistent and comparablc basis. Supply, transmission, and demand-side resources were evaluated on a comparable basis using PaciliCorp's capacity expansion optimization model. Also see the reqxrnse to number 4.b.ii below. 7 Consistent with Lltah rules, PacitiCorp detcrmination ofavoidcd coss in Utah will be handled in a manner consistent with the IRP, with the caveat that the costs may be updated ifbetler informalt)n becomes availablc. 8 'Ihe planning standards and guidelines must meet the needs of the Utah service area. but since coordrnation with other jurisdictions is important. must not ignorc the rules governing the planning process already in place in othcr jurisdictions. This IRP was developed in consultation with parties from all state jurisdictions, and meets all forrnal state IRP guidelines. 9 I 'Ihc company's Strategic Business Plan must be directly rclated to its lnte[fated Resource Plan. Detlrition: Integrated resource planning is a utility planning process which cvaluates all known resources on a consistent and comparable basis, in order to meet cunent and luture customer electric energy services needs at the lowest total cost to the utility and its customcrs, Volumc I, Chapter 9 (Action Plan) describes the linkage betwe'en the 2019 IRP prefcned portlblio and December 2018 business plan rcsources. Signiticant resource differences are highlighted. The business plan portlblio was run consislent with requirements outlined in the Order issued by the Utah Public Service Commission on September 16, 2016, Docket No. l5-035{4. Volume I, Chaptcr T (Modeling and Portfolio Evaluation Approach) outlines thc portfolio perforurance evaluation and preferred porttblio selection process, while Chaptcr {l (Modeling and Portfolio Selection Results) chronicles the modcling and pref'erred portlblio selection process. 'l his IRP 48 PACTFTCORP - 2019 II{P No.Requirement How the Standards and Guidelines are Addressed in the 2019 IRP Avoided cost should be detennined in a manncr consistent with the company's Integratcd Resource Plan. Standards and Guide lines PACIICoRP - 2019 IRP AppENDLx B - IRP REGTJI-AToRY CoMPLLA.N(E also addresses concems expressed by Utah stakeholders and the I ltah commission conceming comprehensiveless of resources considered, consistency in applying input assumptions for portfolio modeling, and explanation of Pacifi Corp's dccision process for selecting top-performing porttblios and the pret'ened portfolio. and in a manner consistetrt with the long-run public interest. 'I'hc pro,cess should rcsult in the selection ol the oplimal sel of resources given the expected combination ofcosts, risk and uncertainty. The company submined its last IRP on Apil4,2ol7, and liled this IRP on Ocbber 18, 2019 meeting the requirement. PacihCorp rcqucsted and was granted an extension of time to lile the 2019 IRP in Dockct No. 19435-02. 2 3 PaciliCorp's public process is described in Volume I, Chapter 2 (Introduction), A record ofpublic meetings is provided in Volume II, Appcndix C iPublic lnput Process). IRP will be developed in mnsultation with the Commission, its staff, the Division of t\blic Utilities, the Commiftee ofConsumer Scrviccs, appropriate Utah state agencies and interested parties. PacifiCorp will provide ample oppornmiry for public input and information cxchange during the development ol its Plal. PaciliCorp implemented a load forecast rangc for both capacity expansion optrmizalion scenarios as well as lix stochastic variability. covering hrth capacity and energy. I)etails conceming the load forecasts used in the 2019 IRP are provided in Volumc l, Chapter 5 (Resource Needs Assessment) and Vohune II, Appendix A (Load Forecast Details) 4.a PacifiCorp's integrated resource plans will include: a range ofestimates or forecasts ofload growth, including both capacity (kW) ard energy (kWh) requircmcnts. 4.a. i Load forecasts are diffcrcntiated byjurisdiction and difi'erentiate energy and capacity rcquirements. See Volume I, Chapter 5 (Resource Needs Asscssmcnt) and Volume II, Appendix A (Load Forecast Details) Non-firm ofl'-system sales are not incorporatcd into the load forecast. Off-systcm sales markets are included in IRP modeling and are used tbr systen balancing purposcs. Thc forccasts will be made by jurisdiction and by geueral class and will differentiate energy and capacity requirements. The company will iuclude in ils forecasts all on-system loads and those oll- system loads which they have a contactual obligation to fullill. Nor-firm off-system sales are uncertain and should not be explicitly incorporated into thc load forecast thal the utility then plans to meet. However, the Plan must have some analysis ofthe otl'-system sales market to assess the impacts such markes will havc on risks associated with dillerent acquisition strategies. Volume Il, Appendix A ([,oad Forecast Details) d(ruments how demographic and price factors are used in PacihCorp's load forccasting methodology 4.a.ii Analyses ofhow various economic and demopgaphic factors, including the prices of elecrricity and altemative energy sourccs, will alIect the consumption of electric energy services, and how changes in the numbcr, type and efliciency of end-uses will affect future krads. Resources were evaluatcd on a consistent and comparable basis usi g 0le System optimizcr model ald Planning and Risk production cost model using both supply side and demand side alternativcs. Sec explanatitn in Volume I, Chapter 7 (Modeling and Porttblio Evaluation Approach) and the rcsults in Volumc [, Chapter 8 (Modeling and Portfolio 4.b An evaluation ofall prescnt and future resources, iucluding future market opportunities (both dcmand-sidc and supply-sidc). on a consistent and comparable basis. 49 No.Requirement How the Standards and Guidelines are Addressed in the 2019 IRP The company will submit its lntegrated Resource Plan biennially. PAflFTCoRP - 2019 IRP AppFrNDLX B - IRP R-ECLTLAToRY CoNtpt.rAN('E Selection Results). Resource options arc summarized in Volume I, Chapter 6 (Resource Options). 4.b.i An assessment ofall technically lbasible and cost-effective improvements in the efficient use ofclectricity, including load managemcnt and conservation. PacifiCorp included supply cuwes for Demand Response (Class I ) DSM (dispatchable/schedulablc load control) and Energy Ellicicncy (Class 2) DSM in its capacity expansion model. Details are provided in Vohrme I, Chapler 6 (Resource Options). 4.b.ii An assessment ofall technically lcasible generating technologies including: renewable resources, cogeneration, power purchases liom other sources, and the construction o l' thcrmal resources. PacitiCorp considered a wide range ofresources including rcnewables, cogenemtion (combined heat and grwer), power purchases, thermal resourccs, energy storage. and l-;ncrBy Cateway transmission contigurations. Volume I, Chapters 6 (Resourcc Options) and 7 (Modeling and Portfolio Flvaluation Approach) contain assumptions and describe the process under which PacifiCorp developed and asscsscd these technologies and resources. 4.b.iii The resource asscssments should include: lit'e cxpectancy of the resowces, the recognition oI whether the resourcc is replacing/adding capacity or cncrgy, dispatchability. lead-time rcquircments, flexibility, ell'iciency ol'thc resouce and oplx)rtunities for customer participation- PacifiCorp captures and models thesc rcsource atfibutes in its IRP models. Rcsources are defined as providing capacity, energy, or both. The DSM supply cuwcs used for portfolio modeling explicitly incorporate estimated rates of program and event participation. The private generation study, modeled as a reduction to load. also considsred rates of participation. Replaccmcnt capacity is considered in thc casc ofearly coal unit rctiremcnts as evaluated in this IRP as an altemative to coal unit environmcntal invcstments, l)ispatchability is accormted tbr in both IRP models used; however. the Planning and fusk model provides a morc detailed representation ofunit dispatch than System Optimizer, and includes modeling ofunit conmitment and reserves. 4.c An analysis of thc rolc ofcompetitive bidding Iirr demand-side and supply-side resourcc acquisitions A description of the role of competitive bidding and other procurement methods is provided in Volume I, Chapter 9 (Action Plan). 4.d This IRP uses a 2O-ycar study horizon (20t9-2038)A 20-year plaruring horizon. An action plaIr outlining the specific rcsource decisions intended to implement the integrated resource plan in a manner consistent with the compaoy's strategic husiness plan. The action plan will span a four-year horizon and will describe specilic actions to bc taken in the first two ycars and outline actions anticipated in the last two years. The action plan will includc a status report ofthc spccilic actions contained in the preYious actio[ plan. ln Volume I, Chapter 9 (Action Plan) l ablc 9.I identilies actions anticipatcd in the next two years and in the next forrr years. 4.t A plan of di [Icrcnt resource acquisition paths lbr different economic circumstances with a decision mechanism to select among artd modify thcsc paths as the fi.rhlre unfolds. Volumc l, Chapter 9 (Action Plan) includes an acquisition path analysis that presents broad resource stratcgics baserl on regulatory trigger evenLs, change in krad gro*th, extension of l'ederal rcncwable resource tax incentives and procurement delays. 50 No.Requirement How the Standards and Guidelines are Addressed in the 2019 IRP The IRP action plan is provided in Volume [, Chapter 9 (Acti('n Plan). A status report oIthe actions outlined in the previous action plan (2017 IRP Update) is provided in Volume I, Chapter 9 (n ction Plan). PA('rFrCoRP 20l9lRI AppENDrx B - IRP REGUr-AToRY CoMPLTANCE 4.9 An evaluation of the cost-elfectivencss of the resource options from the perspectives of the utility and the difl-erent classes of raicpayers. In addition, a description ofhow social conccms might afl'ect cost etl'ectiveness estimates of resource options. PacifiCorp provides resource-specific utility and total resoutce cost information in Volume I, Chapter 6 (Resource Options). 'l'he IRP docurnent addrcsscs the impact ofsocial concems on rcsorrrce cost-eflectiveness in thc lbllowing ways:. 'l'op performing ponfolios were evaluated using a rangc ofCOl pricc-policy scenarios.r A discussion ofenvironmental policy status and impacts on utility resource planning is provided in Volume l. Chaptcr j {The Planning Environment).o State and proposed federal public policy prelbrences for clean encrgy are considered for development ofthe preferrcd portlblio. which is documented in Volurne l, Chapter 8 (Modeling and Portfolio Selcction Results).r Volurne II, Appendix G (Plant Water Consumptio[) repons historical water consumption for PacifiCorp's thermal plants. 4.h An evaluation ofthe financial, competitivc, reliability, and operational risks associated with various resource options and how the action plan addresses these risks in the context ofboth the Business Plan and the 2O-year Integrated Resource Plan. The company will identi! who should bear such risk, the ratepayer or the stockholder. The handling of resourcc risks is discussed in Volumc I, Chapter 9 (Actiou Plan), and covcrs managing environrncntal risk tbr existing plants, risk management afld hedging and treatment ofcustomer and investmcnt risk. 'l'ransmission expansion risks are discussed in Chapter 4 ('l ransmission). Resource capital cost uncertainty and techtological risk is addressed h Volume l, Chapter 6 (Resouce Options). For rcliability risks, the stochastic simulation model incorporates stochastic volatility of lbrced outages for new thcrmal plants and hydro availability. 'lhcsc risks are factored into the comparative evaluation of grrtlblios and the selection ofthc prcferred portfolio upon which the action plan is based. Identilicatior ofthe classes ofrisk and how thesc risks are allocaled lo ratepaycrs and Investors is discusrcd in Volume I, Chapter 9 (Action Plan). 4.i Considerations pennitting flexibility in ihe plaming process so that the compatry can takc advantage ofopportunities and can prevent the prcmahrre fbreclosure of options. 4.i An analysis oftradeoffsl for example, bctwcen such conditions ofservice as reliability and dispatchability and the acquisition oflowcst cost TCSOUTG€S. PacifiCorp exarnined thc trade-off between portfolio cost and risk. taking into consideration a broad range ofresource alternativcs dclined with varying levels of dispatchability. This trade-off analysis is documented in Volumc I, Chapter I (Modeling aud Portfolio SclL'ction Resrdts)- 4.k A range, rather than attempts at precise quantification, of cstimatcd cxtcrnal costs which PaciliCorp incorporatcd cnvironmental extenlality costs lbr COl and costs fbr courplying with currcnt 5t No.Requirement How the Standards and Guidelines 8re Addressed in the 2019 IRP Flexibility in the planning and procwemant processes is highlighted in Volume [, Chapter 9 (Action Plal), specifically, Tabte 9.1. PA('rFrCoRP - 20l9IRP A?pENDx B - IRP R.tcuLAToRy CoMpr-TANCE may hc intangible, in order to show how explicit consideratio[ of orem might afl'ect selection of resourcc options- The company will attempt to quantily the magnitude olthc cxtcmalities, fbr example. in terms ol'thc amount ol emissions relcascd and dollar estimates olthc costs ofsuch cxternalities. and proposcd U.S. EPA regulatory requirements. For CO, externality costs, thc company used scenarios with various compliance requiremenls to capture a reasonable range ofcosl impacts. -fhese modeling assumptions are describcd in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach). 4.1 A narrative describing how current rate design is consislent with the company's integrated resource planning goals and how changes in ratc design might thcilitate irtegrated resource planning objectives. See Volumc I, Chapter 3 (The Planning l'lnvironment). The rolc ol'Class 3 DSM (price response programs) at PacihCorp and how thesc resourccs are modeled in the IRP are described in Volume I, Chapter 6 (Rcsource Options). 5 PacifiCorp distributed draft IRP materials for extemal review throughout the process prior to each of the public-input mcctings and solicited/and reccived feedback at various times when developing the 2019 IRP. The materials shared with stakeholders at these meetings, outlined in Volume I Chapter 2 (Introduction), is consistent wilh materials presented in Vohunes I and tl of the 2019 IRP report. Public- input mcctings materials can be locatcd on PacifiCorp's website at: www.pacilicorp. corn/energy/inte grated-rcsource- plaD/public-input-process.htr PaciliCorp requested and responded to comments from stakeholders in throughout its 2019 IRP process The company also considered commcnts received via Stakeholder Feedback Fonns that can be krcated on PacifiCorp's website at: www.pacifi corp.conr,/energy/integrated-resource- plan/commcnts.htrnl A total of 133 Stakcholder Fcedback Forms were received and responded to duritrg thc 2019 IRP public-input pr<rcss. PaciliCorp will submit its IRP lbr public comment, review and acknowledgnent. 6 The public, state agencies and other interestcd partics will have the opportunity to rnake fonnal comment to the Cornmission on the adequacy ol- the Plan. The Commission will rcvicw the Plan tbr adherence to the principles stated herein, and willjudge the merit and applicability ofthe public conunent. Il'thc Plan needs funher work the Commission will return it to the company with comments and suggcstions lbr change. This process should lead more quickly to the Commission's acknowledgmeDt ol' an acceptable Integrated Rcsourcc Plan. The cornpany will givc an oral presentation ofits report k) the Commission and all inlerestcd puhlic parlies. Firrmal hcarings on the acknowledg'ment of the Inkttratcd Resource PIan rnrght hc appropriate but are not required. Not addressed; this is a post-tiling activity 7 Acknowledgment ofan acceptable Plan will not guarantee favorablc ratemaking treatm€ot of fu ture resource acquisitions- Not addressed; this is not a PacifiCory activity 52 No.Requirement How the Standards and Guidelines are Addressed in the 2019 IRP PA( rnCoRP - 2019IRP APPENDX B - IRP RfGULAToRY CoMPLIANCE Table 8.5 - Washington Utilities and Transportation Commission IRP Standard and Guidelines CW 19.280.030 and WAC 480-100-238 8 Not addressed; this rcl'crs k) a post-liling activity (4)Work plan filcd no latcr than l2 months befine ncxt IRP due date PacitiCorp liled the 2019 IRP work plan on July I 7, 2019 in Docket No. tlF)- l t10259, given an anticipated IRP filing date of Octobcr I tl, 2019. PacifiCorp was granted approval iu Docket No. tIE-180259 on July 26,2019 to file the IRP October ltl, 20t9. (4)Work plan outlines content of IRP See pages l-2 ofthe Work Plan document lbr a surnmarization of anticipaled IRP contents- (4)Work plan outlines method tbr assessing Jxrtential rcsources- (See LRC analvsis below) See pages 3-5 ofthe Work Plan document tbr a summarization of anticipated resource analysis. (5)Work plan outlines timing aud extent of public participation. See pages 5-6 olthe Work Ptan. Table I, page 6, document for thc anticipated IRP schedule. PaciliCorp was granted approval in Docket No. UE-t80259 on July 26, 2019 to file the 2019 IRP on October ltt,2019. (4)Integratcd rcsourcc plan submitted within two years ofprevious plan. thc Wtl'tC issued an Order on Decembcr I l. 2008, undcr l)ocket No- tIFi-0701 17, granting the company permission to file its IRP on March 3l ofeach odd numbered year. PaciliCorp filed the 2017 IRP on April 4, 2017. PacifiCorp was granted approval in Dockct No. UE-180259 on July 26, 2019 to lile the IRP October 18, 2019. (5)This obligation is not applicable to the company; this is a WUTC obligation. WUTC issues notice of public hearing after company files plan for revtew. lhis obligation is not applicable to the companyl this is a WUl C Volume I, Chapter 5 (Resource Nccds Asscssment) describes the mix ofexisti[g resources, while Volurne l, Chapter 8 (Modcling and Portlirlb Sclcction Results) describes the 2019 IRP prelbrred portlblio. o (5) (2)(a) WIITC holds public hearing. Plan describes the mix ofenergy supply rcsuurces. (2)(a)Plan describes conservation supply.See Volune I, Chapter 6 (Resourcc ()ptions) fbr a description of how conservation supplies are represented and modelcd, and Volume l, Chapter 8 (Modeling and Portlblio Selection Results) lbr conscrvation supply in the pr€fened portfolio. Additional information on energy el'liciency rcsource characteristics is availablc on PaciliCorp's IRP website. (2)(a)Plan addrcsscs supply in terms of current and tilture ueeds at the lowest reasonablc cost to the utility and its ratepayers. 'l hc 2019 IRP pret'ened portfolio was based on a resource needs assessmcnl that accounted for Ibrecasted load growth. expiration of cxisting power puchase contracts, rcsources under construction, con[act, or rellectcd in the company's capital budget, as well as a capacity planning resewe margin. Details on PaciliCorp's findings ofresowce nced arc described in Volume I. Chapter 5 (Resource Needs Assessment). (2Xb)Plan uses lowest reasonable cost (LRC) analysis to select the mix of resoufces. Pacificorp uses porlfolio performance measures based on the Prescnt Value of Revenue Requirements (PVRR) methodology. See the section on portfolio pertbrmance measures in Volume I, Chapter Rcquirements prior to IRP Filing Requiremcnts spccific to IRP filing 53 No.Requirement How the Standards and Guidelines are Addressed in the 2019 IRP The Integrated Rcsource Plan will be used in rate cases to evaluate the performance ofthe utility and to review avoided cost calculations. No.Reouirement How the Standards and Guidelines are Addressed in the 2019 IRP PACTFTCoRP -20l9lRP AIPENDD( B _ IRP RIGULAToRY CoMPLIANCE 7 (Modeling and Pontblio Evaluation Approach) and Volume I Chapter 8 (Modeling and Portfolio Selection Results). (2Xb)LRC analysis considers resource costs. Volume I, Chaptcr 6 (Resource Options), provides delailed inlbrmation on costs and other att butcs firr all resources analyzed for the IRP. (2Xb)LRC analysis considers market- volatility risks. PacihCorp employs Monte Carlo pnxluction cost simulation with a stochastic model to characterize rnarket price and gas price volatility. Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach) provides a summary ofthc modeling aDDroach. (2Xb)LRC analysis considers denrand side resowce uncertainties. PacifiCorp capturcd demand-side resource urcertainties through the development ofnumerous portfolios based on different sets of input assumptions. (2Xb)LRC analysis considers resource d ispatchabil ity. PacifiCorp uses two IRP models that simulate the dispatch of existing and future resources based on such attributes as heat rate, availability, fuel cost, and variable O&M cost. The clronological production cost simulation model also incorporates unit commitrnent logic tbr handling start-up, shutdown, ramp ratcs, minimum up/dou,n times, and run up ratcs, and reserve holding characteristics of individual generalors. (2Xb)[,RC analysis considers resource efl'ect on system op,cratt)n- PacifiCorp's IRP models simulate the operation of its entire system, refl ecting dispatch./unit commitment, forced/unlbrced outagcs, access to markets, and system reliability and transmission constsaints. (2Xb)LRC analysis considers risks imposed on ratepayers. PacifiCorp explicitly models risk associatcd with uncertain CO: rcgulatory regirnes, wholesale electricity and mtural gas price csualation and volatility. load growth unccrtainty. rcsourcc reliability, renewablc portfolio standard requirement unccrtainty, plant construction cost escalation. and resource aflordability. These risks and uncenaintics arc handled through stochastic modcling and scenarios dcpicting alternative tirnres. In addition to risk modeling, the IRP discusses a number of resowce risk topics not addressed in the IRP systcm simulation models. For example, Volume [, Chapter 9 (Action Plan) covers the lbllowing topics: (l ) managing carbon risk for cxisting plants, (2) assessment ofowning vs. purchasing power, (3) purpose ofhedging, (4) procurcment delays and (5) treatment ofcustomsr and investor risks. Volume I, Chaptcr 4 (Transmission) covers similar risks associatcd with transmission system expansion. (2Xb)LRC analysis considcrs public policies regarding rcsourcc prcfcrcncc adopted by Washington state or Icdcral govemment. Iu Volume I, Chapter 7 (Modeling and Portfolio Evaluation) thc IRP modeling incorporates resource expansion constraints tied to renewable portlblio standards (RPS) cunently in place fbr Washington. [-937 conservation requirements are explicitly accounted for in developing Washington conservation resourcc costs. (2Xb)Ll{C analysis considcrs cost ofrisks as\ocialed wilh e viro||tncnlal cfl '.'cls including emissions ol' cartxrn dioxidc. (2)(c)Plan dcfincs conscrvation as any rcduction in electric power consumption that results l'rcm increases in the etlicieucy ofenergy ruse, production, or distribution. A description ofhow PacifiCorp classifies and delines energy conservation is provided in Volume I, Chapter 6 (Resource Options). 54 No.Reouirement How the Standards and Guidelines are Addressed in the 2019 IRP See (2)(b) above. PAClrrCoR" 20l9lRP APPENDIX B _ IRP RIGULA,I ORY CoMPT,IANCE (3)(a)PacifiCorp implemented a load li)rccast range. Details concerning thc load lbrecasts used in thc 2017 IRP (high, low, and cxtrcmc pcak tcmperature) are provided in Volume II. Appendix A (i.oad Forecast Details). Plan includes a range of tbrecasts of funrre derrand. (3)(a)PacifiCorp's load lbrecast methodokrgy employs econometric forecasting techniques that include such economic variables as household income, employment, and population. See Volume II, Appendix A (load Forecast Details) for a dcscription of the load tbrecasting methodology. Plan develops lbrecasts using metho<Ls that cxamine thc cl'fect of cconomic forces on the consumption ofelcctricity. (3)(a)Plan dcvclops lbrecasts using methods that address changes in the number, type and elliciency of electrical end-uses. Residential sector load forecasls use a statistically-adjusted end-use model thst accounts for equipment san[ation rates and cfficiency. Sec Volume II, Appendix A (Load Forecast Details), for a description ofthe rcsidetrtial sector load forecasting methodology. (3Xb)Pacificorp updated the system-wide demand-side management potential study in the 2019 IRP, which served as the basis lbr devcloping DSM resouce supply curves lbr resource portlblio modeling. The supply curves account for technical and achievablc (market) potential, while the IRP capacity expansion model identilles a cost-ell'ective mix of DSM resources based on these limits and othcr modet inputs. The DSM potential study is included on the data disc, ard available on PacihCorp's IRP website at: www.pacifi corp.com/energv/inteqrated-resourcc-plar/suppon.htr . Plan includes an assessment of commercially available conscrvation, including load management. A dcscription ofthe current status of DSM proppams and on-going activities to implement cunent and ncw programs is provided in Vohtme I, Chaptcr 5 (Resource Needs Assessmcn(). (3xb)Plan includes an assessment of currc'ntly employed and ncw policies and programs needed to obtain thc conscrvation improvements. (3Xc)PacitiCorp considered a wide range ofresources including renewables, cogcneration (combired heat and F)wer), customer standby generatiol, power purchases, thermal resourccs, encrgy storags, and transmission. Volumc [, Chapters 6 (Resource Options) and Chapter 7 (Mtxlcling and Portfolio Evaluation Approach) drrcument how PacifiCorp dovcloped and assessed these technologies. Plan includes an assessment ofa wide range of conventional and commercially available nonconventional generating technologies. (3xd)PacifiCorp modcled transmissiol system capability to serve its load obligations, factoring in updates to the representation ofmajor load and gcneration centers, regional transmission congestion impacts, imporVexport availability, extemal ma*et dynamics, and signiticant transmission expanstrn plans explained in Volume I, Chapter 4 ( l'ransmissior) and ChaptL'r 7 (Modeling and Portlblio livaluation Approach). System rcliability given transmission capability was analyzed using stochastic production cost simulation and measures ol'insufiicient energy and capacity lirr a load area ([ncrgy Not Served and Unmet Capacity, respectively). Plan includcs an asscssmcnt of transrnission system capability and rcliability; to the extent such infonnation can be providcd consistent wift applicable laws. (3Xe)Plan includes a comparative evaluation of eDergy supply rcsources (including transmission and distdbution) and improvemelts in conservalion using LRC. Pacifi Corp's capaciry expansion oplimization model (System Optimizer) is dcsigned to conpare alternative rcsources-including tmtrsmission cxpansion options-for the least-cost resource mix. System Optimizer was used to develop numerous resourcc portlblios for comparative evaluation on the basis ofcost, risk. reliability, and othcr pcrformance aftributes. Potenlial ene'rgy savings associated with conservation voltage r€duction are discussed in Volumc l, Chapter 5 (Resowce Needs Assessmcnt). (3Xr)Plan includcs integration of the demand forecasts and resource cvaluations into a loDg range integrated resource plan describing PacifiCorp intcgrates demand tbrecasts, resources, and system operations in the conlqxt ofa system modeling framework described in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach). The porifolio evaluation covers a 20-ycar period (2019- 55 No.Requirement How the Standards and Guidelines are Addressed in the 2019 IRP P^cIHCoRP -20l9lRP APPENDL\ B - IRP REcrir.AloRy CoMPLTANCE Table 8.6 - W ln Public Service Commission Guidelines Electric IRP the mix ofresources that is designated to mcct current and project t'uture needs at the lowest reasonable cost to the utility a[d ils ratepayers. 2038). PacitiCorp developed its prefencd portfolio ofresources judged to be leasccost after considering load requiremenLs, risk, uncertainty, supply adequacy/reliability, and govemment resource policies in accordance with this rule. (3)(c)ltlan includes a two-year action plan that implements the long range plan. See Table 9.1 in Volume I, Chapter 9 (Action Plan), for PacifiCom's 2019 IRP action plan. (3Xh)Plan includes a progrcss reporl on the implementation of the prcviously filed plan. See Table 9.2 lbr a status report on action plan implementation liom the 2017 IRP and 2017 IRP tlpdate in Volume I, Chapter 9 (Action Plan). Requirements from RCW 19.280.030 not discusscd above An assessmcnt of methods. commercially available technologies, or facilities lbr integrating renewable resources, and addressing overgeneration events, il'applicable to the utility's resourcc portlbliot See Volume I, Chapter 6 (Reource Options) fbr discussion of resource options in the 2019IRP. Also sec Volume II, Appendix P (Renewablc Resources Assessment)- (t)(e) (rx,)'[he integration of the demand fbrecasts and resource evaluations into a long-range assessment desoibing the mix of supply side gencrating resources and conservation and efhciency resources that will meet curent and projectcd needs, including mitigating overgeneration events, at the lowest reasonable cost and risk to the utility and its ratepayers; See Volume II, Appcndix A (Load Forecast l)ctails) lor a discussion of the load lbrecasts, supply-side and dc'mand-side resources are discusscd in Volume I, Chapter 6 (Resource Options) Also included is a discnssion of DSM in Vohme II, Appendix D (DSM Resources) are included in Volume I, Chapter 7 (Modeling and Pontblio Evaluation Approach) aud Chapter 8 (Modeling and Portlblio Sclection Results) discuss the modeling methodokrgy and selection ofthe prel'encd portfolio using least cosVleast risk metrics. 'ltc public cornment process employed as part of the lirrmulation of the utility's IRP, including a description, timing and weight givetr to the public process; PacifiCorp's public process is described in Volumc [, Chapter ? (lntroduction) and in Vohrme II, Appendix C (Public Input Process). B 'Illc utility's strategic goals and resource planning goals and prcfcrred resource porttblio: Volume I, Chapter 8 (Modclirg and Portfolio Selcction Results) documenls the preferred resource Jxrrtfolio and rationale l.or selection. Volume I, Chapter 9 (Action Plan) constitutes the IRP action plan ard the descriptions ofrcsource stategies and risk management. c 'I'he utility's illustration ot' resource need over the ncar-term and long-term plarurinp horizons, See Volume I, Chapter 5 (Resource Needs Asscssment) D A study dctailing the types of rcsources considered; Volume, t Chapter 6 (Resource (htions), presents the resoruce options used lbr resourcc portfolio modeling trx this IRP. I Changes in cxpected resource acquisitions and load growth fiom that presentcd in the utility's previous IRP; A comparison ofresource chargcs relative to the 2017 IRP Update is presented in Volume I, Chapter 9 (Action Plan). A chart comparing the pcak krad forecasts tbr the 2017 IRP, 2017 IRP tlpdatc, and 2019 IRP is included in Volumc ll, Appendix A (Load lorccast Details). G 'lhc cnvirunmental impacts considered: Rrrtfolio comparisons tbr CO: and a broad range ol'environmental impacts are considercd, including prospectivc carly retirement and gas conversions ofexisting coal units as altematives to environmental investments. See Volumc [, Chapter 7 (Modeling and Portlblio Evaluation Approach) and Chapter tt (Modeling and Portfbltr 56 No.Requirement How the Standards and Guideling are Addressed in the 2019IRP No.Requirement How the Guideline is Addressed in the 2019 IRP PAcTFTCoRP - 20[9lRP APPENDIX B_IRPRtrGULAI.ORY COMPI,IANCE Selection) as well as Volume II, Appendix L (Stochastic Simulation Results). II Market purchases evaluationl Modeling of lirm rnorket purchases (liont oflice transactions) and sDot market balancing transactions is included in thc 20t9IRP. PacifiCorp's planning reserve margin snrdy, which docurnens sele'ction ofa capacity planning resewe margin is in Volume I, Appendix I (Planning Reserve Maqio Study). I Rcservc Margin analysis; and J Demand-side management and conservation options; See Volume I, Chapter 6 (Resourcc Options) for a detailed discussion on DSM and energy elliciency resourcc options. Additional inlbrmation on e[ergy cfliciency resource characteristics is available on the company's website. 57 No.Reduirement How the Guideline is Addrcssetl in the 2019 IRP P^( rlrC0RP 2019lRP AppENDrx B - IRP Rlcrl.AToRy CoMPLLTTNCE 58 P^crHCoR.P - 20l9 lRP APPENDTX C - PuBLrc INPUr PRocEss AppsNorx C - Pueltc lNpur Pnocsss A critical element of this lntegrated Resource Plan (IRP) is the public-input process. PacifiCorp has pursued an open and collaborative approach involving the commissions, customers and other stakeholders in PacifiCorp's IRP prior to making resource planning decisions. Since these decisions can have significant economic and environmental consequences, conducting the IRP with transparency and full participation from interested and affected parties is essential. Stakeholders have been involved in the development of the 2019 IRP from the beginning. The public-input meetings held beginning in June 2018 were the comerstone ofthe direct public-input process. There were a total of l8 public-input meetings, with eight lasting two days, the remainder being single days. Meetings were held jointly in both Salt Lake City, Utah and Portland, Oregon via video conference, with expanded video conference locations in Denver, Colorado and Cheyenne, Wyoming. Tfuee meetings were held via phone conference. For all meetings, attendees off-site were able to conference in via phone. The IRP public-input process also included state-specific stakeholder dialogue sessions held in June and August of20l8. The goal ofthese sessions was to capture key IRP issues ofmost concern to each state, as well as discuss how to tackle these from a system planning perspective. PacifiCorp wanted to ensure stakeholders understood IRP planning principles. These meetings continued to enhance interaction with stakeholders in the planning cycle and provided a forum to directly address stakeholder concems regarding equitable representation of state interests during public- input meetings. PacifiCorp solicited agenda item recommendations from stakeholders in advance of the state meetings. There was additional open time to ensure participants had adequate opporhmity for dialogue. PacifiCorp's integrated resource plan website housed feedback form discussed earlier in Chapter 2 - Introduction. This standardized form allowed stakeholders opportunities to provide comments, questions, and suggestions. PacifiCorp also posted its response to the feedback forms at the same location. Feedback forms and PacifiCorp's responses can be found via the following link: (www.pacifi corp. com/energy/integrated-resource-plan/comments.html ). PacifiCorp's 20t9 IRP was a robust process involving input from many parties throughout. Organizations actively participated in the development of material, modeling process, and public meetings. Participants included commissions, stakeholders, and indusfy experts. Among the organizations that were represented and actively involved in this collaborative effort were: Commissions o Idaho Public Utilities Commission o Oregon Public Utilities Commission o Public Service Commission of Utah. Washington Utilities and Transportation Commission 59 List P^( rFrCoRP - 2019 IRP APPI NDrx C-PUBLI INPIT PRoctss Wyoming Public Service Commission Stakeholders and Industry Experts r Alliance of Western Energy Consumers . Applied Energy Groupo Avangrido Black & Veatche Breathe Utah. Bums & McDonnell Engineering Company. Cascade Natural Gas o City of Kemmerer Wyomingo Clarke Investrnents, LLCo Enel Creen Power . Energy Trust of Oregono First Solaro Gardner Energyr Glenrock Energyo Heal Utaho Holladay United Church ofchristo Idaho Conservation Leagueo Idaho Power Companyo Idaho Public Utility Commission Staffo Individual Customersr Industrial Customers of Northwest Utilitieso lntermountain Windo Lincoln County Commission o Magnum Development o National Grid Ventureso Natural Resources Defense Councilo Navigant Consulting, Inc.o Northwest Pipeline GPo Oregon Departrnent ofEnergyo Oregon Department of Justiceo Oregon Public Utitity Commission Staffo Portland General Electricr Power Quipo Renewables Northwest o Sierra Clubo Utah Clean Energye Utah Division of Public Utilitieso Utah Offrce of Consumer Serviceso Utah Office of Energy Developmento Washington Offrce of Attorney General, Public Council Unit. Westem Resource Advocates o Weshnoreland 60 . Wyoming Coalition of Local Govemments & Lincoln County. Wyoming Department of Workforce Services. Wyoming House Distnct l8 r Wyoming Infrastnrcture Authorityo Wyoming Liberty Group . Wyoming Office Of Consumer Advocate PacifiCorp extends its gratitude for the time and energy participants have given to the IRP process. Their participation has contributed significantly to the quality of this plan and their continued participation will help PacifiCorp as it strives to improve its planning efforts going forward. As mentioned above, PacifiCorp hosted l8 public-input meetings, as well as six state meetings during the public-input process. During the 2019 IRP public-input process presentations and discussions covered various issues regarding inputs, assumptions, risks, modeling techniques, and analytical results. Below are the agendas Iiom the public-input meetingst the presentations cab be located at: www.pacifi corp.com/energy/integrated-resource-plan.html. General Meetings June 28-29, 2018 - General Public Meeting Day One (Confidential Discussion) o Introductionso Model Overview (System Optimizer / Planning and Risk)r Unit-by-Unit Coal Study Results Day Two (Public Discussion). 2ol7 IRP Update Highlights / 20l9lRP Topics and Timeline. Demand-Side Management Workshop Jrlly 2G27,2018 - General Public Meeting Day One. Energy Storage Workshop. Renewable Resource Schedules and Load Forecasto Distribution System Planningo Supply-Side Resource Study Efforts Day Two o Environmental Policyr Renewable Portfolio Standards. 2019 IRP Modeling Assumptions and Study Updates. Intra-Hour Dispatch Credit. Stochastic Parameters Update. Overview ofPlanning Reserve Margin and Capacity Contribution Studies PACTTCORP - 2019 IRP AppENDrx C PutsLrc INprir llR.oa Ess 6l August 30-31,2018 - General Public Meeting Day Oneo Private Generation Studyo Conservation Potential Assessment and Energy Efficiency Creditsr Portfolio Development Process / Initial Sensitivity Studies o Flexible Reserve Studyo Process Improvement / Next Steps Day 2o Market Reliance Assessment o Planning Reserve Margin Study / Capacity Contribution Snrdy September 26-27, 2018 - General Public Meeting Day Oneo Draft Supply-Side Resource Tabler Intra-Hour Flexible Resource Credit o Environmental Policy / Price-Policy Scenarios. Transmission Ovewiew and Updates. Stakeholder Feedback Form Recap Day Two. Flexible Reserve Study Cost Resultso Planning Reserve Margin / Capacity Contribution Results. Portfolios Discussion / Coa[ Studies Next Stepso Demand-Side Management Transmission and Distribution Credit / Conservation Potential Assessment October 9, 2018 - General Public Meeting (Conference Call Only). Supply-Side Resource Table Levelized Costso Intra-Hour Flexible Resource Credits. Updated CO: Assumption November 1, 2018 - General Public Meeting . Supply-Side Resource Tableo Modeling Improvements and Updateso Update on Coal Analysis . Stakeholder Feedback Form Recap December 3-4, 2018 - General Public Meeting Day One. Coal Studies Discussion Day Two. Coal Studies Discussion (continued) o Stakeholder Feedback Form Recap APPTNDIX C -PUBLI( INPIrrlh(x-tss 62 PA( IHCORP - 20l9 lRP PA('rFrCoRP - 2019 IRP APPFNDTx ('- PUBLI('INPrrr l\(x rss January 24, 2019 - General Public Meeting. Capacity-Contribution Values for Energy-Limited Resources . Coal Studies Discussion . Stakeholder Feedback Form Recap February 21, 2019 - General Public Meeting (Conference Call Only)o General Updateso Summary of Oregon Energy Efficiency Analysis Results . Stakeholder Feedback Form Recap March 21, 2019 - General Public Meetingo Coal Studies Modeling Improvements and Updates o Modeling Next Steps o Stakeholder Feedback Form Recap April 25, 2019 - General Public Meetinge Coal Studies Discussion. Stakeholder Feedback Form Recap May 20-21, 2019 - General Public Meeting Day Oneo Conservation Potential Assessment Cost Correction o DSM Bundling Ponfolio Methodology . Updated Portfolio Matrix o Portfolio Analysis Results Discussion Day Twoo Po(folio Analysis Results Discussion (continued) . Stakeholder Feedback Form Recap June 20-21, 2019 - General Public Meeting Day One. Modeling Updateso Portfolio Analysis Results Day Two. Portfolio Analysis Results. Stakeholder Feedback Form Recap July 12, 2019 - DSM Workshop . ConservationPotentialAssessmento Demand-Side Management Portfolio Methodology July 18, 2019 - General Public Meeting (Conference Call Only)o General Updateso Stakeholder Feedback Form Recap b, September 5, 2019 - General Public Meetingo Portfolio Analysis Results o Stakeholder Feedback Form Recap October 3-4, 2019 - General Public Meeting Day One o Preferred Portfolio and Action Plan o Portfolio Development and Selection Day Two. Portfolio Development and Selection. Sensitivitieso Stakeholder Feedback Form Recap State-Specific I nput Meetings June I l, 201 8 - Oregon State Stakeholder Meeting June 12, 201 8 - Washington State Stakeholder Meeting June 18, 2018 - Idaho State Stakeholder Meetrng June 19, 2018 - Wyoming State Stakeholder Meeting June 20, 2018 - Utah State Stakeholder Meeting August 9, 2018 - Utah State Stakeholder Meeting For the 2019 IRP, PacifiCorp offered a Stakeholder Feedback Form which provided stakeholders a direct opportunity to provide comments, questlons, and suggestions outside opporhrnities for discussion at public-input meetings. PacifiCorp recognizes the importance ofstakeholder feedback to the IRP public-input process. A blank form, as well as those submitted by stakeholders and PacifiCorp's response, can be located on the PacifiCorp website at the IRP commen6 webpage at: www-pacifi corp. com/energy/integrated-resource-plan/comments. html. During the 20l9IRP development process, PacifiCorp received 132 Stakeholder Feedback Forms with a combined 564 questions. The Stakeholder Feedback Form allowed the company to review and summarize issues by topic as well as identifl, specific recommendations that were provided. Information collected was used to inform the 2019 IRP development process, including feedback related to process improvements and input assumptions, as well as responding directly to stakeholder questions. Stakeholder Feedback Forms were received from the following stakeholders: . City of Kemmerer, Wyoming. Energy Strategies, LLCo First Solaro Gridflex Energy, LLC PACIFTCoR! - 2019 IRP ApprNDx C Pt,Bl.rc INPUr PRocESs 61 November 12, 2019 - General Public Meeting (PIanned) o Stakeholder Q&Ao Transmission Modeling Workshop Stakeholder Comments e Idaho Conservation League o Idaho Public Utility Commission Staff. IndividualStakeholders . Interwest Energy Alliance . Key Capture Energy. Lawrence Berkeley National Laboratory o Lincoln County School District o National Grid Ventures. Northwest Energy Coalition o Northwest Power and Conservation Councilo Oregon Citizens' Utility Boardo Oregon Public Utility Commission Staff o Oyster Ridge BOCESo Powder River Basin Resource Council. Renewable Northwest o Sierra Clubr Sound Geothermal Corporationo South Lincoln EMS o South Lincoln Medical Center. Southwest Energy Efficiency Project. Utah Association of Energy Usersr Utah Clean Energy e Washington Utilities and Transportation Commission Staff. Westem Resource Advocates o Wyoming Business Councilo Wyoming Coalition of Local Governments & Lincoln Countyo Wyoming House District 18. Wyoming Office of Consumer Advocate Some topics ofnote addressed in the lorms include: . Capacity Factorsc Coal Analysiso Coal Combustion Residuals. Coal Studies. Conservation Credito ConservationPotentialAssessment o Consultant Reports . Demand Responseo Demand-SideManagement. Demand-Side Management Modelingo Distribution System Planning . Energy Efficiencyo Energy Storageo Environmental Policyo Flexible Reserve Study PACTFTCoRT - 2019 IRP APPr\Drx C -PrrBr.rc [NPr I PRu }ss 65 PA0[rCoRP - 20l9lRP APPfNDIx C- PUBL|( INPUrPRCTESS . General Commentsr Inflation Assumptiono Initial Sensitivity Studiese Intra-hour Dispatch Creditsr IRP Filing Dateo IRP Public-Input Meeting Processo Legislationr Levelized Cost Curveso Load Forecasting o Market Purchaseso Market Reliance Assessmento Modeling Assumptions o Modelinglmprovementsr Planning Resewe Margin o Portfolio Analysiso Private Generation Study. ReliabilityAssessment. Renewable Energy Resources o Sensitivity Studies. Supply-side Resource Costs. Supply-side Resource Tableo Transmission. Unit Specific Questions PacifiCorp's IRP website: www.pacificorp.com/energy/integrated-resource-plan.html. PacifiCorp requests any informal request be sent to the following address or email. PacifiCorp IRP Resource Planning Department 825 N.E. Multnomah, Suite 600 Po(land, Orcgon 97232 Email Address: IRP@PacifiCorp.com Phone Number: (503) 813-s24s 66 Contact Information ApppNorx D - DenaRNn-Sros MaNacSMENT RssouRces This appendix reviews the studies and reports used to support the demand-side management (DSM) resource information used in the modeling and analysis of the 20l9lntegrated Resource Plan (IRP). ln addition, it provides information on the economic DSM selections in the 2019 IRP's Preferred Portfolio, a summary ofexisting DSM program services and offerings, and an overview of the DSM planning process in each ofPacifiCorp's service areas. Since 1989, PacifiCorp has developed biennial IRPs to identifli an optimal mix of resources that balance considerations of cost, risk, uncertainty, supply reliability/deliverability, and long-run public policy goals. The optimization process accounts for capital, energy, and ongoing operation costs as well as the risk profiles ofvarious resource alternatives, including: traditional generation and market purchases, renewable generation, and DSM resources such as energy efficiency, and demand response or capacity-focused resources. Since the 2008 IRP, DSM resources have competed directly against supply-side options, allowing the IRP model to guide decisions regarding resource mixes, based on cost and risk. The Conservation Potential Assessment (CPA) for 2019-2038,r conducted by Applied Energy Croup (AEG) on behalf of PacifiCorp, primarily seeks to develop reliable estimates of the magnitude, timing, and costs of DSM resources likely available to PacifiCorp over the IRP's 20- year planning horizon. The study focuses on resources realistically achievable during the planning horizon, given normal market dynamics that may hinder resource acquisition. Study results were incorporated into PacifiCorp's 2019 IRP and will be used to inform subsequent DSM planning and program design efforts. This study serves as an update of similar studies completed since 2007. For resource planning purposes, PacifiCorp classifies DSM resources into four classifications, differentiated by two primary characteristics: reliability and customer choice. These resources classifications can be defined as: demand response (Class I DSM) (e.g., a firm, capacity focused resource such as a load control), energy effrciency (Class 2 DSM) (e.g., a firm energy intensity resource such as conservation), Class 3 DSM (e.g., a non-firm, capacity focused such as pricing response or load shifting), and Class 4 DSM (e.g., a behavioral-based resource such as education and information). From a system-planning perspective, demand response resources can be considered the most reliable, as they can be dispatched by the utility. In contrast, Class 4 DSM resources are the least reliable due to the resource's dependence on voluntary behavioral changes. With respect to customer choice, demand response and energy efficiency resources should be considered involuntary in that, once equipment and systems have been put in place, savings can be expected I PacihCorp's Demand-Side Resource Potential Assessment for 20t7-2036, complcied by AEG, can be found at: www.pacificorp. corr/energy/integrated-resource-plar/support. html. 67 PACIFICORP _ 2OI9 IRP APPENDX D _ DEMAND.SIDE MANAGtrMENT RtSoURCEs lntroduction Conservation Potential Assessment (CPA) for 2019-2038 PACITICoRP _ 2OI9 IRP to occur over a certain period of time. Class 3 and Class 4 DSM activities involve greater customer choice and control. This assessment estimates potential from demand response, energy efficiency, and Class 3 DSM. The CPA excludes an assessment ofOregon's energy efliciency resource potential, as this work is performed by the Energy Trust of Oregon, which provides energy effrciency potential in Oregon to PacifiCorp for resource planning purposes. Currently, PacifiCorp offers a robust portfolio of DSM programs and initiatives, most of which are offered in multiple states, depending on size of the oppornrnity and the need. Programs are reassessed on a regular bases. PacifiCorp has the most up-to-date programs on its website.2 Demand response and energy effrciency program services and offerings are available by state and sector. Energy efficiency services listed for Oregon, except for low income weatherization services, are provided in collaboration with the Energy Trust of Oregon.r Table D.l provides an overview of the breadth ofdemand response and energy efficiency program services and offerings available by Sector and State. PacifiCorp has numerous Class 3 DSM offerings currently available- They include metered time- of-day and time-of-use pricing plans (in all states, availability varies by customer class), residential seasonal inverted block rates (Idaho and Utah) and residential year-round inverted block rates (Califomia, Oregon, Washington, and Wyoming). System-wide, approximately 17,500 customers were participating in metered time-of-day and time-of-use programs as of December 3l ,2017 . All of PacifiCorp's residential customers not opting for Class 3 DSM time-of-use rates are currently subject to seasonal or year-round inverted block rate plans. Savings associated with these resources are captured within the company's load forecast and are thus captured in the integrated resource planning framework. PacifiCorp continues to evaluate Class 3 DSM programs for applicability to long-term resource planning. PacifiCorp provides Class 4 DSM offerings. Educating customers regarding energy efficiency and load management opporhrnities is an important component of PacifiCorp's long-term resource acquisition plan. A variety of channels are used to educate customers including television, radio, newspapers, bill inserts and messages, newsletters, school education programs, and personal contact. Load reductions due to Class 4 DSM activity will show up in demand response and energy effrciency program results and non-program reductions in the load forecast over time, Table D.2 provides an overview of DSM related rprrrsmart Outreach and Communication activities (Class 4 DSM activities) by state. 2 Programs for Rocky Mountain Power can be found at www.rockymountainpower.net/savings-energy- choices.htrnland programs for Pacihc Power can be lbund at www.pacificorp.com/environment/demand-side- managcment.html. I Funds for low-income weathcrization services are forwarded to Oregon llousing and Community Scrvices. 68 AppENDLx D- DEM,\ND-SIDE MAN GENTENT llEsouR( Es Current DSM Program Offerings by State PACIFICORP 20I9IRP AppENDIx D - DEMAND-SDE MANACEMENT RtsotiRCEs Table D.l- Current Demand Response and Energy Elficiency Program Services and s Sector and State Residenliq.l Seclor N on- Res idenlia I S eclo t Air Cbnditioler Direct Load Control Inigation l-oad Control Standard Incentives Euergy l')ngineering Services Billing Credit Incentive (offset to DSM charge) Energy Managemcnt l)nergy Prohler Onlinc Business Solutions Toolkit Tradc Ally Outreach Small Business Liqhting l,ighting Instant lncentives Small to Mid-Sized Business Facilitstion DSM Projcct Managers Parlner With Customer Account Managers Table D.2 - Current wattsmart Outreach and Communications Activities ldrho UlBh Wyoming Air Conditioner Direct Load Conffol Lighting Incentivcs New Appliance Incentives Heating And Cooling Incentives Weathcrization Incentives - Windows. Insulation. Duct Sealing, etc, Nerv Ilornes Low-lncomc Wcatherization Hqme l-,nergy Repolts School Cttrriculum Energy Saving Kits F'inancing Options With On-Uill Palrncnts Trade Ally Outreach Advcnising SErnsorships lvrllsmart Ouarcach & Communirati0ns (incremcntal t0 program spccific ad!crtising)E -69 Program Scniccs & Offerings by Scctor ard Statc California Oregon 1\ ashinglon Program Sen'iccs & Offerings br Sector and Statc California Oregon Washington klaho Utah Wvoming FI-.rlffifl--T_-i--T_--T__-l-l--f-.r--f--T- ,1., 1l-T_rr-r-l-T-rT-l-l-rrl lT, [a I ''/ "/ "/t"/l ./tl-ri-r-r[-]-,T-T-]tl-ri--r--T__ll./1"/l { Il./1"/l ./ |l./l"il ./ I---i--T_--T__-.]l-_r_-T- H ffiFI California Oregon Washington ldaho Utah Wyoming fl Tr-I Social Media Public Relations Business Advocacy (awards at customer meetings, sponsorships, chamber parmership, university psrtnershiD) Wattsrnart Workshops and Community Outrcach Be wattsmart, Begin at Home - in school encrqy education lvattrmart Outrcach & Communirationr (incrcmrntal to program sperilic a(lr crtising) { ldaho Utah Wyoming PACIIJICORP_ 20I9 IRP APPENDD( D _ DEMAND.SIDE MANAGEMENT RESoURCES Utah, Wyoming and Idaho The company's biennial IRP and associated action plan provides the foundation for DSM acquisition targets in each state. Where appropriate, the company maintains and uses external stakeholder groups and vendors to advise on a range of issues including annual goals for conservation programs, development ofconservation potential assessments, development of multi- year DSM plans, program marketing, incentive levels, budgets, adaptive management and the development of new and pilot progams. Washington The company is one of three investor-owned utilities required to comply with the Energy Independence Act (also referred to as I-937) approved in November 2006. The Act requires utilities to pursue all conservation that is cost-effective, reliable, and feasible. Every two years, each utility must identiff its l0-year conservation potential and two-year acquisition target based on is IRP and using methodologies that are consistent with those used by the Northwest Power and Conservation Council. Each utility must maintain and use an external conservation stakeholder $oup that advises on a wide range of issues including conservation progr,rms, development of conservation potential assessments, program marketing, incentive levels, budgets, adaptive management and the development of new and pilot programs. PacifiCorp works with the conservation stakeholder group annually on its energy efficiency progam design and planning. Oregon Energy efficiency programs for Oregon customers are planned for and delivered by the Energy Trust of Oregon in collaboration with PacifiCorp. The Energy Trust's planning process is 70 California Oregon Washin$on State-Specific DSM Plannins Processes A summary ofthe DSM planning process in each state is provided below. California On September 15,2017, PacifiCorp filed Application 17-09-010 requesting authorization to continue offering its energy efficiency programs (through 2020). The Commission issued Decision l8- l t-033 on December 6, 2018, approving the company's application to continue administering its programs through 2020. PacifiCorp expects to submit an application for the continuation of energy effrciency programs beyond 2020. PACIFICORP _ 20 t9 IRP AppENDIx t) - DEMAND-SrDL. MANAGEMENT Ri,souRCES comparable to PacifiCorp's other states, including establishing resource acquisition targets based on resource assessment and integrated resource planning, developing programs based on local market conditions, and coordinating with stakeholders and regulators to ensure efficient and cost- effective delivery of energy efficiency resources. 7t 72 PACITICORT _ 2OI9 IRP APPENDIX D_ I)EMAND-SIDEMANAGEMENT RfsOURCES The smart grid is the application ofadvanced communications and controls to the electric power system. Areas ofinstallation include generation, transmission, distribution, and customer facilities. A wide array of applications can be defined under the smart grid umbrella. Smart grid includes technologies such as dynamic line rating, phasor measurement ulits (synchrophasors), energy storage, power line sensors, distribution automation, integrated volt/var optimization, advanced metering infrastmcture, automated demand response, and smart renewable and,ior distributed generation controls (e.g., smart inverters). PacifiCorp regularly evaluates integrating smart grid technologies and implements those that show a positive net benefit for its customers. PacifiCorp has tested or implemented smart grid devices and firnctions such as dynamic line rating, synchrophasors, and communicating faulted circuit indicators. Advanced metering infrastructure, distribution automation, and distributed energy resource systems (including electric vehicles) are also underway or under consideration. PacifiCorp will leverage sman grid technologies to align investments with the least-cost/least-risk goals ofthe Integrated Resource Plan (IRP). This will optimize the electncal grid when and where it is economically feasible, operationally beneficial, and in the best interest of customers. PacifiCorp is committed to consistently evaluating the value of emerging technologies and recommend them for demonstration or integration ifthey are found to be appropriate investments. PacifiCorp is working with state commissions to improve reliability, energy efficiency, customer service, and integration of renewable resources by analyzing the total cost of ownership, performing thorough cost-benefit analyses, and reaching out to customers concerning smart grid applications and technologies. As technology advances and development continues, PacifiCorp is able to improve estimates of the costs and benefits of smart grid technologies. Progressing large- scale deployments and demonstration projects will reveal the effect of large-scale rollouts and assist PacifiCorp in identifuing the best suited technologies for implementation. Transmission System Efforts Dynamic Line Rating Dynamic line rating is the application of sensors to transmission lines to indicate the real-time current-carrying capacity of the lines in relation to thermal restrictions. Transmission line ratings are typically based on line loading calculations given a set ofworst-case weather assumptions such as high ambient temperatures and very low wind speeds. Dynamic line rating allows an increase in current-carrying capacity when more favorable weather conditions are present and the 73 PACTFICoRP - 20l9lRP APPENDD(E_SMARTGRD AppsNorxE-StunnrGnto Introduction PacifiCorp has reviewed relevant sman grid technologies for transmission, substation, and distribution systems. When considering smart grid technologies, the communications network is often the most critical infrastructure decision. This network must have high speed, reliability, and security. It must be interoperable for many device types, manufacturers, and generations of technology and must be scalable in order to support PacifiCorp's entire service territory. PAcrrrcoRP - 2019 IRP APPTNDx E- SM^Rr (;RrD transmission path is not constrained by other operating elements. Two dynamic line rating projects were implemented in 2014, Miners-Platte and West-of-Populus. The Miners-Platte project uses a dynamic line rating system to determine the resulting cooling effect of the wind on the line. The current carrying capacity is then updated to a new weather dependent line rating. The Miners-Platte 230 kV transmission line was one of the limitations of the TOT4A transmission path with wind farms significantly impacting the loading of the [ine. As a result of this project, the TOT4A Westem Electricity Coordinating Council (WECC) non- simultaneous path rating was increased. The West-of-Populus project was the second dynamic line rating project in 2014. The dynamic line rating enabled lines experienced low line loading due to peak loads between Pacific Power and Rocky Mountain Power coinciding over time. As a result ol this low loading, the thermal reading of the lines is dependent upon ambient weather conditions without being greatly affected by line loading. Until higher line loading is experienced from high flow scenarios or outages, conclusions concerning the dynamic line rating project in West-of-Populus are difficult to ascertain. PacifiCorp will continue to collect and analyze future data as high line loading is experienced. Dynamic line rating will be considered for all future transmission needs as a means for increasing capacity in relation to traditional construction methods. Dynamic line rating is only applicable for thermal constraints and only provides additional site-dependent capacity during finite time periods. lt may or may not align with the expected transmission need of future projects. PacifiCorp will continue to look for opportunities to cost-effectively employ dynamic line rating systems. Thermal Replicating Relays PacifiCorp extensively considered a project to install thermal replicating relays to adhere to protection and control compliance standards in the Soda Springs area ofldaho. Thermal replicating relays utilize dynamic line rating to monitor the thermal properties of the line, then send a trip signal if the thermal limit has been exceeded. These relays may only be used where line tripping will not cause cascading outages. A remedial action scheme (RAS) was also analyzed as an altemative to thermal replicating relays for the Soda Springs area. In this particular case, because the remedial action scheme was deemed more cost-effective, the thermal replicating relay project altemative will not be employed. Synchrophasors Synchrophasors, also called phasor measurement units, can lead to a more reliable transmission network by comparing phase angles of certain network elements with a base element meursurement. Phasor measurement units can also be used to increase reliability by relaying line condition data through the communication netrvork quickly. Phasor measurement unit implementation may enable transmission operators to integrate variable resources and energy storage more effectively while minimizing service disruptions. 74 PAcrrrCoRP - 20l9IRP PacifiCorp participated in the Weslem Interconnection Synchrophasor Project (WISP). The project resulted in eight phasor measurement units installed in eight PacifiCorp substations. These devices are currently collecting data and will support PacifiCorp's and Peak Reliability'sr goal of maintaining power system stability. The system of synchrophasors will be used to identifu and analyze system rulnerabilities and disturbances. It will also assist in preventing system blackouts and provide historical data for the analysis ofany future power system failure. Peak Reliability is continuing to develop data access for utility participants. PacifiCorp has discontinued sending data to Peak Reliability as part of their WISP program since they currently do not operationally utilize the data. Once Peak Reliability has their advanced application firnctionality enabled, which is expected in 201 7, PacifiCorp expects to reinitiate data flow to Peak Reliability. Phasor measurement units will also be used to satisry the validation requirements in North American Elecric Reliability Corporation (NERC)-MOD-033, a reliability standard proposed to improve accurate data collection and planning models. Planning models analyzing the transmission system reliability are required to compare model results to real-world values in order to meet model validation requirements. Distribution System Efforts Distribution Automation Distribution automation (DA) is a wide field of smart grid technology and applications, which focuses on using sensors and data collection on the distribution system, as well as automatically adjusting the system to optimize performance. It can also provide operational efficiency, peak load management, equipment failure prediction, and decreased restoration times after failure. PacifiCorp is working on several distribution automation initiatives. In Oregon, PacifiCorp has identified 40 circuits on which a DA cost benefit analysis will be performed. These 40 circuits were selected based on a set of criteria intended to minimize the cost of implementation and maximize the reliability benefit. The feasibility of utilizing an advanced metering infrastructure network for the communications of the distribution automation system will also be addressed. PacifiCorp has installed FusesaverrNl devices and electronic reclosers with the capability ofenabling communications through a retrofit in the future. A pilot project in Walla Walla, Washington is underway to demonstrate the feasibility and effectiveness ofdistribution automation, including a lault location isolation and restoration application. A feasibility study to determine the cost and benefit of retrofitting an existing source/transfer scheme to a distribution automation scheme is underway in Salt Lake City, Utah. PacifiCorp installed communicating faulted circuit indicators on five circuits in eastern Utah in March 2014. These devices have proven capable of improving reliability by reducing the time required to report and locate a fault. PacifiCorp is still evaluating the cost and leasibility ofintegrating these devices in its outage management system before further deployment. I Peak Reliabiliry (Peak) is a company wholly independent of WI:CC that pcrfomE the Reliability CNrdimtor (RC) frmctioo in its RC AJea in the Western Interconnectior. 75 APPENDIX H_SMATTGRD Customer Information Efforts Advanced Metering Infrastructure A key effort for PacifiCorp in 2016 was the development of a detailed business case for advanced metering infrastructure in Oregon. Advanced metering infrastructure is an integrated system of smart meters, communications networks, and data management systems with two-way communication. PacifiCorp's objectives were to identiry a solution and strategy that would deliver tangible projected benefits to our customers and deliver economically-driven financial results while minimizing the impact on consumer rates. A request for information followed by a request for proposals was solicited to further evaluate the economics and impacts ofan advanced metering infrastructure rollout in Oregon. The financial analysis of proposals indicated a positive business case due to decreasing costs of advance metering technology and increasing operations and maintenance costs. As a result, Pacific Power committed to proceed with deployment of an advanced metering infrastructure system in Oregon. The advanced metering infrastructure program in Oregon will replace 590,000 existing customer meters with smart meters and install an advanced metering system to remotely read and operate customer meters. The project will provide a web portal for customers, capture hourly meter data, perform on demand meter reads, remotely connect and disconnect power, verifo outage inquiries, remotely reprogram meters, and collect data on power quality and tampering. This advanced metering infrastructue project will provide a network and metering infrastnrcture to improve customer service and enable future smart grid applications. Project benefits include reduced operations and maintenance costs, a platform for future smart grid applications, increased worker safety, reduced emissions, and increased data for efficient management of the network. Meter installations began in 2017 and the project completion date is scheduled for the end of 2019. PacifiCorp is continuing to evaluate smart grid technologies and piloted projects that might benefit customers. PacifiCorp regularly develops smart grid reports to examine the quantifiable costs and benefits of individual components of the smart grrd. While the net present value of implementing a comprehensive smart gdd system throughout PacifiCorp is negative at this time, PacifiCorp has implemented specific projects and programs that have positive benefits for customers, and continues to explore pilot projects in other areas ofinterest. ln order to reduce risk to the company, grid, customers, and supporting systems, it is essential to identifo affordable leading technologies and implement industry best practices. 76 PA( rFrCoRP-2019IRP APPENDIXE_SMARfGRD Future Smart Grid AppENnrx F - Fr-Exrsr-E RpsEnvp Sruoy This 2019 Flexible Reserve Study (FRS) estimates the regulation reserve required to maintain PacifiCorp's system reliability and comply with North American Electric Reliability Corporation (NERC) reliability standards as well as tlle incremental cost ofthis regulation reserve. The FRS also compares PacifiCorp's overall operating reserve requirements, including both regulation reserve and contingency reserve, to its flexible resource supply over t}te Integrated Resource Plan (IRP) study period. PacifiCorp operates two Balancing Authority Areas (BAAs) in the Westem Electricity Coordinating Council (WECC) NERC region, PacifiCorp East (PACE) and PacifiCorp West (PACW). The PACE and PACW BAAs are interconnected by a limited amount of transmission across a third-party transmission system and the two BAAS are each required to comply with NERC standards. PacifiCorp must provide sufficient regulation reserve to remain within NERC's balancing authority area control enor (ACE) limit in compliance with BAL-001-2,r as well as the amount of contingency reserve required in order to comply with NERC standard BAL-002- WECC-2.2 BAL-001-2 is a regulation reserve standard that became effective Juty l,2016, and BAL-002-WECC-2a is a contingency reserve standard that became effective January 24,2017. Regulation reserve and contingency reserve ure components of operating reserve, which NERC defines as "the capability above firm system demand required to provide for regulation, load forecasting enor, equipment forced and scheduled outages and local area protection.''r Apart from disturbance events that are addressed through contingency reserve, regulation reserve is necessary to compensate for changes in load demand and generation output, so as to maintain ACE within mandatory parameters established by the BAL-001-2 standard. The FRS estimates the amount of regulation reserve required to manage variations in load, variable energy resourcesa (VERs), and resources that are not VERs ("Non-VERs") in each of PacifiCorp's BAAs. Load, wind, solar, and Non-VERs were each studied because PacifiCorp's data indicates that these components or customer classes place different regulation reserve burdens on PacifiCorp's system due to differences in the magnitude, frequency, and timing of their variations from forecasted levels. The FRS is based on PacifiCorp operational data recorded from January 2017 tkough December 2017 for load, wind, solar, and Non-VERs. PacifiCorp's primary analysis, focuses on the I NERC Standard tsAL-001-2, www.nerc.con/files/BAl-001-2.pdf, which became ellective July l,2016. ACE is the difference between a BAA's scheduled and actual interchange, and reflects the difference berween electrical generation and Load within that BAA. '? NERC Standard tsAL-002-WECC-2a, www.nerc.com/lileVBAI--002-WECC-2a.pdf, which became effective January 24,2011. BAL-002-WECC-2a clarilied that non-traditional resources can qualifo as spinning reserves if they meet technical and performance requirements. r NERC Glossary ofTerms: www.nerc.corn/files/glossary_of_terms.pdf, updated May 13, 2019. a VERs are resources that rcsources that: (l ) are renewable; (2) cannot be stored by the fhcility owner or opclator; and (3) have variabifity that is beyond the oontrol ofthe facility owner or operator. Integralion of Varidble Enetgt Resor.nce.r, Order No. 764, 139 FERC !l 61,246 aa P 281 (2012) ("Order No. 7(4"); order on reh'g, Order No. 764- A, l4l }'ERC fl 6l,232 (2012) ("Order No.764-A"); order on reh'g and clarirtcation, Order No. 764-8, 144 FIRC \61,222 atP 2lO (2013) ("Order No. 764-8"). 77 PACTTICoRP _ 2O I9 IRP APPENDL\ F - l'ulxrBr.E RTSERVE sTLrDy Introduction PACIIICoRP - 20I9 IRP APP}-NI)Ix F _ I]I.F,XIRI,I: RIsI.]RVE STI ]DY variability of load, wind, solar, and Non-VERs during 2017. A supplemental analysis discusses how the total variability ofthe PacifiCorp system changes with varying levels of [oad, wind and solar capacity. The estimated regulation reserve amounts determined in this study represent the incremental capacity needed to ensure compliance with BAL-001-2 for a particular operating hour. The regulation reserve requirement covers variations in load, wind, solar, and Non-VERs, while implicitly accounting for the diversity berween the different classes. An explicit adjustment is also made to account for diversity benefits realized as a result of PacifiCorp's participation in the Energy Imbalance Market (EIM) operated by the Califomia lndependent System Operator Corporation (CAISO). The methodology in the FRS is similar to that employed in PacifiCorp's previous regulation reserve requirement analysis in the 2017 IRP, but has been enhanced in some key ways.s First, regulation reserve requirements are co-optimized in a quantile regression model. Second, actual hourly load schedules are employed as compared to the proxy schedules developed in the previous study. Third, the FRS uses actual solar schedules reflecting the widespread penetration of utility scale solar facilities that has occurred since tle previous study. Fourth, the FRS reflects updated data based on actual operational experience, including the data and benefits from PacifiCorp's participation in the EIM.6 The FRS results produce an hourly forecast of the regulation reserve requirements for each of PacifiCorp's BAAs that is sufficient to ensure the reliability of the transmission system and compliance with NERC and WECC standards. This regulation reserve forecast covers the combined deviations ofthe load, wind, solar and Non-VERs on PacifiCorp's system and varies as a function of the wind and solar capacity on PacifiCorp's system, as well as forecasted levels of wind, solar and load. Ove rview The FRS first estimates the regulation reserve necessary to maintain compliance with NERC Standard BAL-001-2 given a specified portfolio of wind and solar resources. The FRS next calculates the cost ofholding regulation resene for incremental wind and solar resources. Finally, the FRS compares PacifiCorp's overall operating reserve requirements over the IRP study period, including both regulation reserve and contingency reserve, to its flexible resource supply. 5 2017 l.lexible Reserve Study, Appcndix F in Volume II trfPacifiCorp's 2017 IRP report: www. pacificorp.com/conlent/dam/pacificorp/doc/Energy_Sources/lntcerated,Resource_Plan/201 7_lRP/201 7_lRP Volumell_20 I 7_IRP_Final.pdf 6 PaciliCorp presented thc IRS tbr the 2019 [RP to the 'l cchnical Review Committee (TRC) that reviewed the FRS for the 2017 lRP. In light of the robusl rnethodology developcd for the 2017 lRP, and the relativcly limited modifications for the 2019 IRP, TRC nlembers indicated thal continuing thc lbrmal review proccss was uonecessary, 78 The regulation reserve requirement methodologies produced by the FRS was applied in the Planning and Risk (PaR) production cost model to determine the cost of the reserv'e requirements associated with incremental wind and solar capacity. These integration costs are applied to potential wind and solar resource options in the System Optimizer (SO) model portfolio expansion model, which does not otherwise account for regulation reserve requirements. When a portfolio is studied in the PaR model, the regulation reserve requirements specific to that portfolio are calculated and included in the study inputs, such that the production cost of the requirements is incorporated in the reported results, so it is not necessary to add integration costs to the PaR results. PACITICORP _ 2OI9 IRP APPINI)IX F _ FLEXIBLE IItrSERVE SIlJI)Y The FRS estimates regulation reserve based on the specific requirements of NERC Standard BAL- 001-2. It also incorporates the curent timeline for EIM market processes, as well as EIM resource deviations and diversity benefits based on actual results. The FRS also includes adjustments to regulation reserve requirements to account for the changing portfolio ofsolar and wind resources on PacifiCorp's system and accounts for the diversity of using a single portfolio of regulation reserve resources to cover variations in load, wind, solar, and Non-VERs. A comparison of the results ofthe current analysis and that from the 2017 IRP is shown in Table F.l and Table F.2. Table F.l - Portfolio lation Reserve uirements Table F.2 - 2019 FRS Flexible Resource Costs as Com ared to 2017 Co $/MWh In the 2017 FRS, PacifiCorp calculated an inter-hour system balancing integration cost reflecting sub-optimal gas plant commitment based on day-ahead [oad, wind, and solar forecasts, rather than actuals. However, gas plants are dispatched in EIM to meet regional demand, not just the PacifiCorp demand reflected in the PaR model, and quick-start gas plants can be committed within EIM. In light of the minimal impact of the calculated cost in the 2017 IRP, and possible interaction with EIM, the company opted not to include inter-hour system balancing integration costs in the 20l9IRP. The 2019 FRS results are applied in the 2019IRP portfolio development process as a cost for wind and solar generation resources. Once candidate resource porrfolios are developed using the SO model, the PaR model is used to evaluate portfolio risks. The PaR model inputs include regulation reserve requirements specific to the resource portfolio developed using the SO model. As a result, the IRP risk analysis using PaR includes the impact of diflerences in regulation reserve requirements between portfol ios. PacifiCorp's flexible resource needs are the same as its operating reserve requirements over the planning horizon for maintaining reliability and compliance with the North American Electric Reliability Corporation (NERC) regional reliability standards. Operating reserve generally consists ofthree categories: (l) contingency reserve (i.e., spinning and supplemental reserve), (2) regulation reserve, and (3) frequency response reserve. Contingency reserve is capacity that PacifiCorp holds available to ensure compliance with the NERC regional reliability standard BAL- 79 ', 1\'7 1,050 998 38% 2019 Base Casc 2;150 1.021 994 4',7y,531 20t'1 2018-2036Study Period 20t'7 lntra-hour Rcserye $0.43 $0.46 $l.l I s0.85 Intcr-hour System Balancing $0. r4 $0. r4 nla tu'a Total Flexiblc Rcsource Cost $0.57 $0.60 sl.ll $0.85 Flexible Resource Requirements Casc Wlnd Capscity (MW) Solar Crpacity MW Stand-alone Regulation Requlremetrt rMw) Portfolio Diversity Credit (o/o\ Regulation Requirement with Diverslty iMw) 2017 Base Case 6t'7 Wiqd 2017 FRS (2016s) Solar 2017 FRS (20165) Wind 2019 FRS (2018$) Solar 2019 FRS (2018S) 2018-2036 PACIFIC0RP _ 20I9 IRP APPENDD( F _ FEXIBLD I(ESERVE Snn)Y 002-WECC-2a.7 Regulation reserve is capacity that PacifiCorp holds available to ensure compliance with the NERC Control Performance Criteria in BAL-001-2.8 Frequency response reserve is capacity that PacifiCorp holds available to ensure compliance with NERC standard BAL-003-I.e Each type ofoperating reserve is firther defined below. Contingency Reserve Purpose: Contingency reserve may be deployed when unexpected outages of a generator or a transmission line occur. Contingency reserve may not be deployed to manage other system fluctuations such as changes in load or wind generation output. Volume: NERC regional reliability standard BAL-002-WECC-2a specifies that each BAA must hold as contingency reserve an amount ofcapacity equal to tkee percent ofload and three percent of generation in that BAA. Duration: Except within 60 minutes of a qualifying contingency event, a BAA must maintain the required level ofcontingency reserve at all times. Generally, this means that up to 60 minutes of generation are required to provide contingency reserve, though successive outage events may result in contingency resewes being deployed for longer periods. To restore contingency reserves, other resources must be deployed to replace any generating resources that experienced outages, typically either market purchases or generation from resources with slower ramp rates. Ramp Rate: Only up capacity available within ten minutes can be counted as contingency reserve. ln accordance with Requirement 2 of BAL-002-WECC-2a, at least half of a BAA's requirement must be met with "spinning" resources that are online and immediately responsive to system frequency deviations, while the remainder can come from "non-spinning" resources that do not respond immediately, though they must still be fully deployed in ten minutes.r0 Regulation Reserve Purpose: NERC standard BAL-001-2, which became effective July l, 2016, does not specify a regulation reserve requirement based on a simple formula, but instead requires utilities to hold suffrcient reserve to meet specified control performance standards. The primary requirement relates to area control error ("ACE'), which is the difference between a BAA's scheduled and actual interchange, and reflects the difference between electrical generation and load within that BAA. Requirement 2 of BAL-001-2 defines the compliance standard as follows: Each Balancing Authority shall operale such that its clock-minute average of Reporting ACE does not exceed its clock-minute Balancing Authority ACE Limit (BAAL) for more than 30 consecutive clock-minutes... 7 NERC Standard BAL-002-WECC-2a - Conthgeocy Reserve: www.nerc.com/filesiBAL-002-WECC-2.pdf 8 NFIRC Standard BAL-001-2 - Real Power Balancing Control Performance: www.nero.cor/filesiBAl-0o t-2.pdf e NERC Standard BAL{03-I - Frequency Response and Frequency Bias Setting: www. nerc-com/pa./Stand./ReliabiliqP/o20Standards/BAL-003- l.pdfr0 Retirement of the minimum spinning reserve obligation in BAL-002-WECC-2a is heing considered due to redundancy with frequency response obligations under BAL-003-1. More intbrmation is available online at: www. wecc.org/Stao&rds/PageVWECC-0 t I 5.aspx 80 P^CIFICoRP _ 2O I9 IRP APPENDX F _ FIfXBLE RISERVE STIJDY In addition, Requirement I of BAL-001-2 specifies that PacifiCorp's Control Performance Standard I (.'CPSI") score must be greater than equal to 100 percent for each preceding 12 consecutive calendar month period, evaluated monthly. The CPSI score compares PacifiCorp's ACE with interconnection frequency during each clock minute. A higher score indicates PacifiCorp's ACE is helping interconnection fiequency, while a lower score indicates it is hurting interconnection frequency. Because CPSI is averaged and evaluated on a monthly basis, it does not require a response to each and every ACE event, but rather requires that PacifiCorp meet a minimum aggregate level of performance in each month. Regulation reserve is thus the capacity that PacifiCorp holds available to respond to changes in generation and load to manage ACE within the limits specified in BAL-001-2. Volume: NERC standard BAL-001-2 does not specify a regulation reserve requirement based on a simple formula, but instead requires utilities to hold sufficient reserve to meet performance standards as discussed above. The 2019 FRS estimates the regulation reserve necessary to meet Requirement 2 by compensating for the combined deviations ofthe [oad, wind, solar and Non- VERs on PacifiCorp's system. These regulation reserve requirements are discussed in more detail later on in the study. Ramp Rate: Because Requirement 2 includes a 30 minute time limit for compliance, ramping capability that can be deployed within 30 minutes contributes to meeting PacifiCorp's regulation reserve requirements. The reserve for CPSI is not expected to be incremental to the need for compliance with Requirement 2, but may require that a subset ofresources held for Requirement 2 be able to make fiequent rapid changes to manage ACE relative to interconnection frequency. Duration: PacifiCorp is required to submit balanced load and resource schedules as part of its participation in EIM. PacifiCorp is also required to submit resources with up flexibility and down flexibility to cover uncertainty and expected ramps across the next hour. Because forecasts are submitted prior to the start of an hour, deviations can begin before an hour starts. As a result, a flexible resource might be called upon for the entire hour. ln order to continue providing flexible capacity in the following hour, energy must be available in storage for that hour as well. The likelihood ofactually deploying for two hours or more for reliability compliance (as opposed to economics) is expected to be small. Frequency Response Reserve Purpose: NERC standard BAL-003-l specifies that each BAA must iurest frequency deviations and support the interconnection when frequency drops below the scheduled level. When a frequency drop occurs as a result ofan event, PacifiCorp will deploy resources that increase the net interchange of its BAAs and the flow of generation to the rest ofthe interconnection. Volume: When a frequency drop occurs, each BAA is expected to deploy resources that are at least equal to its Frequency Response Obligation. The incremental requirement is based on the size of the fiequency drop and the BAA's Frequency Response Obligation, expressed in megawatt (MWy0.l Herts (Hz). To comply with the standard, a BAA's median measured liequency response during a sampling of under-frequency events must be equal to or greater than its Frequency Response Obligation. PacifiCorp's 2019 Frequency Response Obligation was 20.2 MW0.lHz for PACW, and 47.4 MW0.lHz for PACE. PacifiCorp's combined obligation amounts to 67.6 MW for a ftequency drop of 0.1 Hz, or 202.8 MW for a frequency drop of 0.3 Hz. 8l I,^CI}]CORP 2I)I9 IRP APPENDX Ii_ FI-EXIBLF] R}:sI.]RVE STLIDY The performance measurement for contingency reserve under the Disturbance Control Standard (BAL-002-3)'r, allows for recovery to the lesser ofzero or the ACE value prior to the contingency event, so increasing ACE above zero during a frequency event reduces the additional deployrnent needed if a contingency event occurs. Because contingency, regulation, and frequency events are all relatively infrequent, they are unlikely to occur simultaneously. Because the frequency response standard is based on median performance during a year, overlapping requirements that reduced PacifiCorp's response during a limited number of frequency events would not impact compliance. Ramp Rate: Frequency response performance is measured over a period of seconds, amounting to under a minute. Compliance is based on the average response over the course ofan event. As a result, a resource that immediately provides its full frequency response capability will provide the greatest contribution. That same resource will contribute a smaller amount if it instead ramps up to its full frequency response capability over the course ofa minute or responds after a [ag. Black start service is the ability ofa generating unit to start without an outside electrical supply and is necessary to help ensure the reliable restoration of the grid following a blackout. At this time, PACW grid restoration would occur in coordination with Bonneville Power Administration black start resources. The Gadsby combustion turbine resources are capable of supporting grid restoration in PACE. PacifiCorp has not identified any incremental needs for black start service during the IRP study period. Ancillary Services Operational Distinctions In actual operations, PacifiCorp identifies two types of flexible capacity as part of its participation in the EIM. The contingency reserve held on each resource is specifically identified and is not available for economic dispatch within the EIM. Any remaining flexible capacity on participating resources that is not designated as contingency reserve can be economically dispatched in EIM based on its operating cost (i.e. bid) and system requirements and can contribute to meeting regulation reserve obligations. Because ofthis distinction, resources must either be designated as contingency reserve or as regulation reserve. Contingency events are relatively rare while opportunities to deploy additional regulation reserve in EIM occur frequently. As a result, rr NERC Standard BAL{02-3 - Disturbancq Clonlrol Standard - Contingency Reserve for Recovery liom a Balancing Contingercy.Evcnt: www.nerc.com/pa./Stand eliability Staodards/BAL-002-3.pdf 82 As a result, any available capacity not being used for generation is expected to contribute to meeting PacifiCorp's Frequency Response Obligation, up to the technical capability ofeach unit, including that designated as contingency or regulation reseryes. Frequency response must occur very rapidly, and a generating unit's capability is limited based on the unit's size, governor controls, and available capacity, as well as the size ofthe frequency drop. As a result, while a few resources could hold a large amount ofcontingency or regulation reserve, frequency response may need to be spread over a larger number ofresources. Additionally, only resources that have active and tuned governor controls as well as outer loop control logic will respond properly to frequency events. Duration: Frequency response events are less than one minute in duration. Black Start Requirements PACrI-rCoRr - 2019 IRP APPENDIX F _ I't.ExIBI,E R.ESERVE STL1DY PacifiCorp typically schedules its lowest-cost flexible resources to serve its load, and blocks off capacity on its highest-cost flexible resources to meet its contingency obligations, subject to any ramping limitations at each resource. This leaves resources with moderate costs available for dispatch up by EIM, while lower-cost flexible resources remain available to be dispatched down by EIM. This section describes the data used to determine PacifiCorp's regulation reserve requirements. In order to estimate PacifiCorp's required regulation reserve amount, PacifiCorp must determine the difference between the expected load and resources and actual load and resources. The difference between load and resources is calculated every four seconds and is represented by the ACE. ACE must be maintained within the limits established by BAL-001-2, so PacifiCorp must estimate the amount of regulation reserve that is necessary in order to maintain ACE within these limits. To estimate the amount of regulation reserve that will be required in the future, the FRS identifies the scheduled use ofthe system as compared to the actual use ofthe system during the study term. For the baseline determination ofscheduled use for load and resources, the FRS used hourly base schedules. Hourly base schedules are the power production forecasts used for imbalance settlement in the EIM and represent the best information available concerning the upcoming hour.12 The deviation from scheduled use was derived from data provided through participation in the EIM. The deviations of generation resources in EIM were measured on a five-minute basis, so five-minute intervals are used throughout the regulation reserve analysis. EIM base schedule and deviation data for each wind, solar and Non-VER transaction point were downloaded using the SettleCore application, which is populated with data provided by the CAISO. Since PacifiCorp's implementation of EIM on November l, 2014, PacifiCorp requires certain operational forecast data iiom all of its hansmission customers pursuant to the provisions ofAttachment T to PacifiCorp's Federal Energy Regulatory Commission (FERC) approved Open Access Transmission Tariff(OATT). This includes EIM base schedule data (or forecasts) from all resources included in the EIM network model at transaction points. EIM base schedules are submitted by transmission customers with hourly granularity, and are settled using hourly data for load, and fifteen-minute and five-minute data for resources. A primary function of the EIM is to measure load and resource imbalance (or deviations) as the difference between the hourly base schedule and the actual metered values. 83 Reserve Data Oven'iew 12 The CAISO, as the markct operator tbr the EIM, requests base schedules at 75 rninutes ('l -75) prior to the hour of delivery. PaciliCorp's transmissiorr customers are required to submit base schedules by 77 minutes (T-77) prior to the hour ofdelivery - two minutcs in advance ofthe DIM Entity deadline. This allows all transmission customer base schedules enough time to be submittcd inlo thc EIM systems beforc the overall deadline ofT-75 for thc cntirety of PacifiCorp's two BAAs. The base schedules are due again ro CAISO a1 55 mioutes (f-55) prior to the delivery hour and can be adjusted up until that lime by the EIM Entity (i.e., PacifiCorp Crid Operations). PacifiCorp's transmissior customers arc required to submit updated, frnal base schedules no laler than 57 minutes (T-57) prior to lhe delivery hour. Again, this allows all transmission customer base schedules enough time to be submitted into the EIM systems bclbre the overall deadline ofT-55 for the entirety ofPaciliCorp's two BAAs- Base schedules may be finally adjusted again, by the EIM Entity only, at 40 minutes (T-40) prior to the delivery hour in response to CAISO sufficiency tesLs. T40 is the base schedule time point used thoughout this study PACIFICoR} _ 20I9 IRP A summary of fte data gathered for this analysis is listed below, and a more detailed description ofeach type ofsource data is contained in the following subsections. Source data:- Load datao Five-minute interval actual load o Hourly base schedules VER datao Five-minute interval actual generation o Hourly base schedules Non-VER datao Five-minute interval acrual generationo Hourly base schedules Load Data The toad class represents the aggregate firm demand of end users of power from the electric system. While the requirements of individual users vary, there are diumal and seasonal pattems in aggregated demand. The Load class can generally be described to include three components: (l) average [oad, which is the base load during a particular scheduling period; (2) the trend, or "ramp," during the hour and from hour-to-hour; and (3) the rapid fluctuations in load that depart from the underllng trend. The need for a system response to the second and third components is the function of regulation reserve in order to ensure reliability ofthe system. In addition, intemrptible loads can be curtailed if their deviations are contributing to a resource shortfall. Because of these unique characteristics, these loads are excluded from the FRS. This treatrnent is consistent with that used in the CAISO load forecast methodology (used for PACE and PACW operations), which also nets these interruptible customer loads out of the PACE BAA. Actual average load data was collected separately for the PACE and PACW BAAs for each five- minute interval. Load data was downloaded from PacifiCorp's Ranger PI system and has not been adj usted for transmission and distribution losses. Wind and Solar Data The wind and solar classes include resources that: (l) are renewable; (2) cannot be stored by the facility owner or operator; and (3) have variability that is beyond the control ofthe facility owner or operator.rJ Wind and solar, in comparison to load, often have larger upward and downward rr Order No. 764 at P 28ll Order No. 764-8 at P 210 APPENDX F - T TEXBLE RISERVF] STLTDY The PACE BAA includes several large industrial loads with unique patterns of demand. Each of these loads is either intemrptible at short notice or includes behind the meter generation. Due to their large size, abrupt changes in their demand are magnified for these customers in a manner which is not representative of the aggregated demand of the large number of small customers which make up the majority of PacifiCorp's loads. 84 P^CIIICoRP_20I9IRP APPL.NI)Ix I] I]l-ExtBLt RESERVF]S II;I)Y The Non-VER class is a mix of thermal and hydroelectric resources and includes all resources which are not VERs, and which do not provide either contingency or regulation reserve. Non- VERs, in contrast to VERs, are often more stable and predictable. Non-VERs are thus easier to plan for and maintain within a reliable operating state. For example, in Order No. 764, FERC suggested that many of its rules were developed with Non-VERs in mind and that such generation "could be scheduled with relative precision."lsThe output of these resources is largely in the control of the resource operator, particularly when considered within the hourly timeframe ofthe FRS. The deviations by resources in the Non-VER class are thus significantly lower than the deviations by resources in the Wind class- The Non-VER class includes third-party resources (OATT or legacy transmission customers); many PacifiCorp-owned resources: and other PacifiCorp-contracted resources, such as qualifying facilities, power purchases, and exchanges. In total, the FRS includes 2,2O2 megawatts of Non-VERs. In the FRS, resources that provide contingency or regulation reserve are considered a separate, dispatchable resource class. The dispatchable resource class compensates for deviations resulting from other users of the transmission system in all hours. While non-dispatchable resources may offset deviations in loads and other resources in some hours, they are not in the control of the system operator and contribute to the overall requirement in other hours. Because the dispatchable resource class is a net provider rather than a user of regulation reserve service, its stand-alone regulation reserve requirement is zero (or negative), and its share ofthe system regulation reserve requirement is also zero. The allocation of regulation reserve requirements and diversity benefits is discussed in more detail later on in the study. Overview This section provides details on adjustments made to the data to align the ACE calculation with actual operations, and address data issues. Base Schedule Ramping Adjustment In actual operations, PacifiCorp's ACE calculation includes a linear ramp from the base schedule in one hour to the base schedule in the next hour, starting ten-minutes before dre hour and ra Order No. 764 at P 20 (emphasis added) ti Id. atP 92.. 8-5 fluctuations in ouput that impose significant and sometimes unforeseen challenges when attempting to maintain reliability. For example, as recognized by FERC in Order No. 764, "lncreasing the relative amount of [VERS] on a system can increase operational uncertainty that the system operator must manage through operating criteria, practices, and procedures , including the commitment oJ atlequate reserves."t4 The data included in the FRS for the wind and solar classes include all wind and solar resources in PacifiCorp's BAAs, which includes: (l) third-party resources (OATT or legacy contract transmission customers), (2) PacifiCorp-owned resources; and (3) other PacifiCorp-contracted resources, such as qualifuing facilities, power purchases, and exchanges. In total, the FRS includes 2,750 megawatts of wind and I ,021 megawatts of solar. Non-VER Data Reserve Data and PACU'rCoRP - 2019 IR?APPtsNDIX F _ FEXIBLE RTSERVF] S,I I]I)Y continuing until ten-minutes pasl the hour. The hourly base schedules used in the study are adjusted to reflect this transition from one hour to the next. This adjustment step is important because, to the extent actual load or generation is transitioning to the levels expected in the next hour, the adjusted base schedules will result in reduced deviations during these intervals, potentially reducing the regulation reserve requirement. Figure F.l below illustrates the hourly base schedule and the ramping adjustment. The same calculation applies to all base schedules: Load, Wind, Non- VERs, and the combined po(folio. Figure F.l - Base Schedule Ramping Adjustment 5000 5900 5ao0 5700 5500 5600 5400 5300 5200 5100 5000 4900 4AO0 ooooooooooooooooor4 Iq I9q ee I a oa e::J:l:{(, o o P P N) N) UJ U' S D (^ Cn O O P P(, o( o (Jro (,o ( o (,o (^o (^ o o oooooooooooo+!f!fq!f99tq99q9(rootsPNl\)(r(rJ55(^(,o(^o(o(ro(no(no Ti I Adjusted Base Schedule I Base Schedule me (lnterval Ending) Data Corrections Load: Stuck meter/flat meter reading 86 The data extracted from PacifiCorp's systems for, wind, solar and Non-VERs was sourced from CAISO settlement quality data. This data has already been verified for inconsistencies as part of the settlement process and needs minimal cleaning as described below. Regarding five minute interval load data from the PI Ranger system, intervals were excluded from the FRS results ifany five-minute interval suffered from at least one of the data anomalies that are described further below: E ==_ca!oI o ID PACITICoRP _ 2OI9 IRP APPEN'DIX F _ [II.EXIBLI RISTRVI STLIDY a Telemetry spike/poor connection to meter Wind, Solar, and Non-VERs:o Generator trip events. Curtailment events Load in PacifrCorp's BAAs changes continuously. While a BAA could potentially maintain the exact same load levels in two five-minute intervals in a row, it is extremely unlikely for the exact same load level to persist over longer time frames. When PacifiCorp's energy management system (EMS) load telemetry fails, updated load values may not be logged, and the last available load measurement for the BAA will continue to be reponed. Similarly, rapid spikes in load either up or down are also unlikely to be a result ofconditions which require deployment of regulation reserve, particularly when they are transient. Such events could be a result of a transmission or distribution outage, which would allow for the deployment of contingency reserve, and would not require deployment of regulation reserve. Load telemetry spike inegularities were identified by examining the intervals with the largest changes from one interval to the next, either up or down. lntervals with inexplicably large and rapid changes in load, particularly where the load reverts back within a short period, were assumed to have been covered through contingency reserve deployment or to reflect inaccurate load measurements. Because they don't reflect periods that require regulation reserve deployment, such intervals are excluded from the analysis. As with Load, certain Wind and Non-VER deviations are more likely to be a result of conditions that allow for the deployment ofcontingency resewe, rather than regulation reserve. In particular, contingency reserve can be deployed to compensate lor unexpected generator outages. For Non- VERs, these are relatively straightforward-namely, periods when generation drops to zero despite base schedules indicating otherwise. Certain Wind outages also qualifu as contingency events. Notably, wind generators can be curtailed when wind speed exceeds the maximum rating of the equipment (sometimes referred to as "high speed cutout"). In such instances, generation is curtailed until wind speeds drop back into a safe operating range in order to protect the equipment. When wind speed oscillates above and below the cut-offpoint, generation may ramp down and up repeatedly. Because events which qualifu for deployment of contingency reserve do not require deployrnent of regulation reserve they have been excluded from the analysis. As the regulation reserve requirements are calculated using a rolling thirty-minute timeline, data ilom the prior hour is necessary during the first several five-minute intervals ofthe next hour. An error in one hour thus results in the need to remove the following hour. This is relevant to error adjustments for both Wind and Non-VERs. After review of the data for each of the above anomaly types, and out of 105,120 five-minute intervals evaluated, only l.l percent and 0.52 percent ofthe total FRS term hours were removed from PACW and PACE, respectively, The system-wide error rate was 1.36 percent, slightly lower than the sum ofthe PACW and PACE rates due to coincident hours. While cleaning up or replacing anomalous hours could yield a more complete data set, determining the appropriate conditions in those hours would be difficult and subjective. By removing anomalies, the FRS sample is smaller but remains reflective of the range of conditions PacifiCorp actually experiences, including the impact on regulation reserve requirements ofweather events experienced during the study period. 81 PACTrcORP _ 20I9IRP APPENDX F - FEXIBLE RESER!,E STIJDY Overview This section presents the methodology used to determine the initial regulation reserve needed to manage the load and resource balance within PacifiCorp's BAAs. The five-minute interval load and resource deviation data described above informs a regulation reserve forecast methodology that achieves the following goals: Complies with NERC standard BAL-001-2; Minimizes regulation reserve held, and Uses data available at time of EIM base schedule submission at T-40.16 The components of the methodology are described below, and include Operating Reserve: Reserve Categories; Calculation of Regulation Reserve Need; Balancing Authority ACE Limit: Allowed Deviations, Planning Reliability Target: [.oss of Load Probability ("LOLP"); and Regulation Reserve Forecast: Amount Held. Following the explanation below ofthe components ofthe methodology, the next section details the forecasted amount of regulation reserve for: Wind: Solar; Non-VERs; and Load. Components of Operating Reserve Methodology Operating Reserve: Reserve Categories Operating reserve consists of three categories: (l) contingency reserve (i.e., spinning and supplemental reserve), (2) regulation reserve, and (3) frequency response reserve. These requirements must be met by resources that are incremental to those needed to meet firm system demand. The purpose of the FRS is to determine the regulation reserve requirement. The contingency reserve and frequency response requirements are defined formulaically by their respective reliability standards. Of the three categories of reserve referenced above, the FRS is primarily focused on the requirements associated with regulation reserv'e. Contingency reserve may not be deployed to manage other system fluctuations such as changes in load or wind generation output. Because deviations caused by contingency events are covered by contingency reserve rather than regulation reserve, they are excluded from the determination ofthe regulation reserve requirements. Because frequency response reserve can overlap with that held for contingency and regulation reserve requirements it is similarly excluded from the determination of regulation reserve requirements. 16 ,See footnote l2 above for explanation o[ PaciliCorp's use tll' the I -40 base schedule time point in the FRS Regulation Reserve Requirement Methodology 88 PACIFICoRP _ 20 I9 IRP AppriNr)rx f' - f'r.F;xrBr.F; RFrsFiRvFr sTrrDy The types ofoperating reserve and relationship between them are further defined in in the Flexible Resource Requirements section above. Regulation reserve is capacity that PacifiCorp holds available to ensure compliance with the NERC Control Performance Criteria in BAL-001-2, which requires a BAA to carry regulation reserve incremental to contingency reserve to maintain reliability.lT The regulation reserve requirement is not defined by a simple formula, but instead is the amount of reserve required by each BAA to meet specified control performance standards. Requirement two of BAL-001-2 defines the compliance standard as follows: Each Balancing Authority shall operate such that its clock-minute average of' Reporting A(.IE does not exceed ils clock-minute Balancing Authority ACMimil (BAAL).for more than 30 conseculive clock-minutes... PacifiCorp has been operating under BAL-001-2 since March l, 2010, as part of a NERC Reliability-Based Control freld triaI in the Westem Interconnection, so PacifiCorp has experience operating under the new standard, even though it did not become effective until July I, 2016. The three key elements in BAL-001-2 are: (l) the length of time (or "interval") used to measure compliance; (2) the percentage of intervals that a BAA must be within the limits set in the standard; and (3) the bandwidth of acceptable deviation used under each standard to detennine whether an interval is considered out of compliance. These changes are discussed in further detail below. The flrrst element is the length of time used to measure compliance. Compliance under BAL-001- 2 is measured over rolling thirty-minute intervals, with 60 overlapping periods per hour, some of which include parts of two clock-hours. In effect, this means that every minute of every hour is the beginning ola new, thirty-minute compliance interval under the new BAL-001-2 standard. If ACE is within the allowed limits at least once in a thirty-minute interval, that interval is in compliance, so only the minimum deviation in each rolling thirty-minute interval is considered in determining compliance. As a result PaciflrCorp does not need to hold regulation reserve for deviations with duration less than 30 minutes. The second element is the number of intervals where deviations are allowed to be outside the limits set in the standard. BAL-001-2 requires 100 percent compliance, so deviations must be maintained within the requirement set by the standard for all rolling thiny-minute intervals. The third element is the bandwidth ofacceptable deviation before an interval is considered out of compliance. Under BAL-001-2, the acceptable deviation for each BAA is dynamic, varying as a function of the frequency deviation for the entire interconnect. When interconnection frequency exceeds 60 Hz, the dynamic calculation does not require regulation resources to be deployed regardless of a BAA's ACE. As interconnection frequency drops further below 60 Hz, a BAA's permissible ACE shortfall is increasingly restrictive. Planning Reliability Target: Loss of Load Probability When conducting resource planning. it is common to use a reliability target that assumes a specified loss of load probability (LOLP). In effect, this is a plan to curtail firm load in rare '7 NERC Standard BAL-001 -2, www.ncrc.conr/lilcsiBAl.-001-2.pdf 8S APPENDD( } _ T I.EXIBLE RESERVE STf]DY circumstances, rather than acquiring resources for extremely unlikely events. The reliability target balances the cost of additional capacity against the benefit of incrementally more reliable operation. By planning to curtail firm load in the rare event of a regulation reserve shortage, PacifiCorp can maintain the required 100 percent compliance with the BAL-001-2 standard and the Balancing Authority ACE Limit. This balances the cost ofholding additional regulation reserve against the likelihood ofregulation reserve shortage events- The 2019 FRS assumes that a regulation reserve forecasting methodology that results in 0.50 loss of load hours per year due to regulation reserve shortages is appropriate for planning and ratemaking purposes. This is in addition to any loss of load resulting from transmission or distribution outages, resource adequacy, or other causes. The FRS applies this reliability target as follows: lf the regulation reserve available is gteater than the regulation reserve need for an hour, the LOLP is zero for that hour. Ifthe regulation reserve held is less than the amount needed, the LOLP is derived from the Balancing Authority ACE Limit probability distribution as illustrated below. Balancing Authority ACE Limit: Allowed Deviations Even if insufficient regulation reserve capability is available to compensate for a thirty-minute sustained deviation, a violation of BAL-001-2 does not occur unless the deviation also exceeds the Balancing Aurhority ACE Limit. The Balancing Authority ACE Limit is specific to each BAA and is dynamic, varying as a function of interconnection fiequency. When WECC frequency is close to 60 Hz, the Balancing Authority ACE Limit is large and large deviations in ACE are allowed. As WECC frequency drops further and further below 60 Hz, ACE deviations are increasingly restricted for BAAs that are contributing to the shortfall, l.e. those BAAs with higher loads than resources. A BAA commits a BAL-001-2 reliability violation if in any thirty-minute interval it doesn't have at least one minute when its ACE is within its Balancing Authority ACE Limit. While the specific Balancing Authority ACE Limit for a given interval cannot be known in advance, the historical probability distribution ofBalancing Authority ACE Limit values is known. Figure F.2 below shows the probability of exceeding the allowed deviation during a five-minute interval for a given level of ACE shortfall. For instance, a 43 MW ACE shortfall in PACW has a one percent chance of exceeding the Balancing Authority ACE Limit. WECC-wide frequency can change rapidly and without notice, and this causes large changes in the Balancing Authority ACE Limit over short time frames. Maintaining ACE within the Balancing Authority ACE Limit under those circumstances can require rapid deployment oflarge amounts ofoperating reserve. To limit the size and speed of resource deployment necessitated by variation in the Balancing Authority ACE Limit, PacifiCorp's operating practice caps permissible ACE at the lesser of the Balancing Authority ACE Limit or four times Lro. This also limits the occurrence of transmission flows that exceed path ratings as result oflarge variations in ACE.r8 re This cap is reflected in Figure F.2. 18 "Regional Industry lnitiatives Assessment." NWPP MC Phase 3 Operatiorx lntcgration Work Group. Dec. 3 l, 2014. Pg. 14. Available at: www.nwpp.org/documens/lr4C-PublicAlWPP-MC-Phase-3-Regional-Industry- lnitiativr:s-Asscssmentl 2-3 I -20 l4.pdfIe'NERC Reliability-Based Control t'ield-Irial Dmft Rcport." Wcstern Electricity Coordinating Council. Mar. 25, 2015. Availablc at: www.wecc.bizlReliability/RBC%20Field%20Tria1%20Repon%20Approved%Z03-25-20l5.pdf 90 PACTHC()RP - 2019 IRP PAcrrrCoRP - 2019 IRP APPENDLX }. _ FI,F]XTBLE RISERVE STLIDY r@% s .9 .g oo1'o 3s u0 .E1'ooxlr.l o =ltlEoo o. 90% 8Oo/o 7 Oo/o 60% 50% 40% 30% 20% 10% o% 0 50 100 150 200 AcE shortfall (MW) -Exceedance Probability(PACE) -Exceedance Probability(PACW) In2Ol7, PacifiCorp's deviations and Balancing Authority ACE Limits were uncorrelated, which indicates that PacifiCorp's contribution to WECC-wide frequency is small. PacifiCorp's deviations and Balancing Authority ACE Limits were also uncorrelated when periods with large deviations were examined in isolation. If PacifiCorp's large deviations made distinguishable contributions to the Balancing Authority ACE Limit, ACE shortfalls would be more likely to exceed the Balancing Authority ACE Limit during large deviations. Since this is not the case, the probability ofexceeding the Balancing Authority ACE Limit is lower, and less regulation reserve is necessary to comply with the BAL-001-2 standard. Regulation Reserve Forecast: Amount Held In order to calculate the amount of regulation reserve required to be held while being compliant with BAL-001-2 - using a LOLP of 0.5 hours per year or less - a quantile regression methodology was used. The regression variables consist of: o The combined deviation of load, wind, solar, and Non-VERs;o Forecasted load as a percentage ofpeak load; r Forecasted wind generation as a percentage oftotal system wind capacity;r Forecasted solar generation as a percentage oftotal system solar capacity; ando Forecasted Non-VER generation as a percentage of maximum Non-VER schedules. 9l Figure F.2 - Probability of Exceeding Allowed Deviation PACII.ICoRP - 20I9 IRP APPENDD( | - IitrxBLIl RI-isl-RVE sTIlDy The combined deviations of load, wind, solar and non-VERs (Combined Diversity Error) is calculated as [I.oad Error - Wind Error - Solar Error - Non VER Error] as illustrated below in Table F.3 for PACE. Table F.3 - Combined Di Error Exa 0 lt4 tili20l'7 llv20t1 2 0 The individual enors (load, wind, solar and non-VERs) are calculated as the difference between the actual meter data and the adjusted hourly base schedules as illustrated below for PACE wind in Table F.4. Table F.4 - Wind Error Exam le t/t/2017 3 t/t /20t'7 r l 3 951 An illustration ofthe combined diversity error and the forecasted levels of load as a percentage of peak load, the forecasted levels of wind as a percentage of total system capacity, the forecasted levels of solar as a percentage oftotal system capacity and the forecasted levels ofNon-VERs as a percentage ofpeak schedule are illustrated below in Table F.5 for PACE. Table F,5 -uts Exa 5 12I t20t'1 t0 60 0 15-2t -16 6l | /t/20t'7 -14 53 I t2011 -55 91 t/t/20t7 -48 87 t/t/20t7 -26 0 0 6'7 I /t/20t7 3 l 3 .l 3 l 3 -5 -7 -6 -4 -6 -6 5 20 t0 l5 4t) 34 40 35 36 25 35 30 36 36 I il i2017 | /y20t7 32l 3 3 3 .l -8 -5 55 45 50 30 3I 71 0 0 -41 -37 -39 -39 Ir0 66 74 -37 73 75 t/t/20t7 936 -21 t/t/20t7 5 l0 :l 95',7 956 940 -t6I /20t1 941 -14 vL/20t7 900 -55 90lJ -48 929 -26 1^ t20t7 -41 -39t/|20t'7 t/t t20t7 -39 t/t/20t7 914 9t6 918 -3'1 t/ I /20t7 911 -37 t/ | /20 t7 3 l l 3 3 l5 (r0 2t) 55 25 50 30 45 35 40 955 954 955 955 955 955 955 955 919 -32 I /V20t7 50.So/t (:)o/, 50.40a 0v, 56'Yo 560/. 50.30/o 56.1, 92 t/20t7 In l5 53 0%55Yo Trading l)ate Trading Hour Trading lnterval Load Enor Non VER Error Wind Error Solar Error Combined Diversity Flrmr ull2otT yu20t7 0 0 0 --1 40 0 I il t20t'7 1- 0 60 45 -32 I _l 3 955 916 +--T- 55% 55.i/. Date Hour Interual Base Schedules Actuals Wind Error Trading Hour Trading Interval Combined Diversity Enor Wind Forecast Solar Forccast Load Forecast Non VER ForecastDatc 3 PAcrrtCoRP - 2019 IRP N PPEN'DLX F II,EXBLE RISERVI STLIDY I /t /201'7 I /t t20t'l t/t l20t'l t/v20t1 uu20t7 t/t /2017 UIt20L7 9',7 87 6',1 50.3% 50.3% 56vo 56vo 55% 55% 0% 0% .l 0o/o 0o/o oo/. 560/o 5svo lt4 66 56V.55V.t t i t i2otl 68 50.1%o% I lu20t7 513 50.1%56% The Load Forecast, Wind Forecast, Solar Forecast and Non VER Forecast are calculated as a percentage of some measure of capacity or peak. The forecasted levels of PACE wind as a percentage oftotal system capacity is illushated below in Table F.6. Table F.6 - Wind Forecast Level Exa t5'/1898 50.5% -t- 56vo 56%. 550/. 55v'50.3o/o 0oto 0%56V.55v, 1898 | so.tvot/t t2ot7 3 3 IO I5I uv2gyI vrnon 1898 1898 50.3o/o 5O.3o/o 50.3Yo 3 20 --.1I it t2t)t1 l 25 955 1898 l^t2ot'l 3 :10 955 t 898 t/t t20t'|l -15 955 t898 I ^ /20 t'l 3 40 955 y r/?ot7 955 I^/20t7 955 ut/20t'7 954 I /t/20t7 951 Itt98 Quantile regression is a type ofregression analysis. Whereas the typical method ofordinary least squares results in estimates of the conditional mean (506 percentile) of the response variable given certain values of the predictor variables, quantile regession aims at estimating other specified percentiles ofthe response variable. Forthe 2019 FRS the response variable - Combined Diversity Error - was expressed as a function of four predictor variables - Wind Forecast, Solar Forecast, Load Forecast and Non VER Forecast. Each predictor variable contributes to the regression as a combination oflinear, square, and cubic effects. Specifically: Combined Diversity Error varies as a function of: Wind Forecast * Wind Forecast2 * Wind Forecast3 I Solar Forecast + Solar Forecast2 + Solar Forecast3 + Load Forecast t Load Forecast2 I Load Forecast3 | NonVER Forecast t NonVER Forecast2 The instances requiring the largest amounts of regulation reserve occur infrequently, and many hours have very low requirements. If periods when requirements are likely to be low can be distinguished from periods when requirements are likely to be high, less regulation reserve is necessary to achieve a given reliability target. The regulation reserve forecast is not intended to compensate for every potential deviation. Instead, when a shortfall occurs, the size ofthat shortfall determines the probability of exceeding the Balancing Authority ACE Limit and a reliability 30 20 25 l5 50 55 560 60l 55% 55% 5t/ I t20t7 l 50.3% t898 1898 50.3% 50.3% 50.3v. IJ98 50.3Yo 1898 50.3% 50.l% 3 93 50.3% 0% 50.\Yr 50.3vr 50.3%-l-40 45 q0 74 956 955 955 45r3 _s0 I 55 160 Date Hour lnterval Base Schedules Wind l'orccast PACIICoR? _ 20I9 IRP APPENDD( F _ FI.EXItsLE T{ESERVE STUDY Overview The following forecasts are polynomial functions that cover a targeted percentile ofall historical deviations. These forecasts are stand-alone forecasts - based on the difference between hour-ahead base schedules and actual meter data - expressing the errors as a firnction ofthe level of forecast. The stand-alone reserve requirement shown achieves the annual reliability target of 0.5 hours per year, after accounting for the dynamical Balancing Authority ACE Limit. The combined diversity error system requirements are discussed later on in the study. Wind Figure F.3 illustrates the relationship between the regulation reserve requirements for PACE wind during 2017 and the forecasted level of output, stated as a capacity factor (i.e., a percentage of the nameplate wind capacity). Figure F.4 illustrates this relationship for PACW. Figure F.3 - Wind Regulation Reserve Requirements by Forecast - PACf, 20'17 PACE Wind Forecast vs Enor {0 0%- 5.30 0% Ez $ zo ox (L E 3'r0 0% E, - oDca oor - Rosoiw Req,iromant it 00%- 0% 10!6 2016 30% 40i6 50* 609t 70!a Forecad Ceacty Factot 80* 90* 1009a 94 violation occurring. The forecast is adjusted to achieve a cumulative LOLP that corresponds to the annual reliability target. 2017 Regulation Reserve Forecast .i:i' t: ir trt PACrFrcoRr - 2019 IRP APPENDLX [ _ FI-EXIBLE RIST,RVT:STI]DY Figure F,4 - Wind Regulation Reserve Requirements by Forecast Capacity Factor-PACW 2017 PACW Wlnd Forecast vs Enor a0 0%- .E E z (L E 30 0% {r;!0 1 - Reserve Requlaamant I I E 0 Fo{ecad Capocly Fetor 80% 9096 100% The forecast results in an average 201 7 stand-alone regulation reserve requirement for wind of434 MW for the PacifiCorp system, or approximately I 5.8 percent of nameplate capacity. Solar Figure F.5 illustrates the relationship between the regulation reserve requirements for PACE solar during 2017 and the forecasted level ofoutput, stated as a capacity factor (i.e., a percentage ofthe nameplate solar capacity). Figure F.6 illustrates this relationship for PACW. 95 .tI I '1.';;: .' :r:: -..: PACTFTCoRP - 2019 IRP APPF]NDIX [ _ FIEXIBLE RTSERVT-: S'ITIDY 70 0%- l. - Rasam RequGmanl r0 0* - 00%- 0% 1096 20* 30* 1016 50% 60!a 70!6 80% 90% 100x Forecasl Capacity Factor Figure F.6 - Solar Regulation Reserve Requirements by Forecast Capacity Factor-PACW 2017 PACW Solar Foracast vs Enor o6o -g E 250 E.o o E n - RasdYa Raqlaamerl 096 096 0!a t0% 2(}r 3ot a0$ 50% 60!a 70!a 809a 90t 1009a 96 Forecasi Capacry Factor Figure F.5 - Solar Regulation Reserve Requirements by Forecast Capacity Factor-PACE 2017 PACE Solar Forecast w Eror a E z500%- E no o*- & I :o ox- E e200*- E t: P^crrrCoRP - 2019 IRP APPENI)XF FLEXIBLE RESERVE STLIDY The forecast results in an average 2017 stand-alone regulation reserve requirement for solar of 145 MW for the PacifiCorp system, or approximately 14.8 percent of nameplate capacity. Non-VERs Figure F.7 below illustrates the regulation reserve requirements for PACE Non-VERs during 2017 as a function of the forecasted level of output, stated as a peak schedule factor (i.e., a percentage of the peak Non-VER schedule observed for 2017). Figure F.8 illustrates this relationship for PACW. -9 (L (L E E. 15.0*- la.oqa - t3 ota - t2.096- 't10*- 'r0 0t - 9{}r- 8.094 - 7ora- 6.0qa - 5.0*- 4.0*- 3.1)* - z!*- r (Ir- 0.0i6' i! . I ..'tr.{!' It J - .Rasani Reqarmanl ' Fall . Spino . &rnmaaI1 .l l.' I 10 0x 200% 30 0!a 40 096 :O 0* 60.09t 70 0!6 80 0% 90 0* 100.096 Fo.ecasl Ped( Schedle Ffito. 97 Figure F.7 - Non-VER Regulation Reserve Requirements by Forecast Schedule Factor- PACE 2017 PACE Non VER Forecast vs Eror I a i.. I I 1 r,t .i Ir ) PAcITICoRP _ 2OI9 IRP ATPENDD( F _ FI"F]XII}I,E ITI,SERI'E STTIDY Figure F.8 - Non-VER Regulation Reserve Requirements by Forecast Schedule Factor- PACW 2017 PACW Non VER Forecast vs Enor 150*- 140X- 13.096-lt 312 d 9, o- E 2 l,t t I 0* 0x 0!t ,i :' a I s I :\.i! roI- 00x- r0 0% 20 096 30 0l(400* 50.0* 600* 70 096 80 0x 90 0t6 100094 Fo.ecad Pe.* Sch€dre Factor Load Figure F.9 below illustrates the regulation reserve requirements for PACE load during 2017 as a function ofthe forecasted level of output, stated as a peak load factor (1.e., a percentage ofthe peak load observed during 2017) for PACE. Figure F.l0 illustrates this relationship for PACW. 98 I t.tIIq I t a :l II -.RaserE Rcqilma ' F.( ' SP.rno. Survnet 1 I The forecast results in an average 2017 stand-alone regulation reserve requirement for non VERs of I l0 MW for the PacifiCorp system, or approximately 5.7 percent of the peak schedule. PACITICoRP _ 2OI9 IRP APPENDIX F _ IJLEXIBI,E RISERIT STIIDY Figure F.9 - Stand-alone Load Regulation Reserve Requirements-PACE 2017 PACE Load Forecasl vs Error 6 0096 _ 0.00%' !.el 500%- f, roor- !aoon-.L ! z.oon- E 1 009l- , t l,' l"; t - .Ra3aavt Reqirama.Fd . spitnc ' SutntnGr -.Rasarv! Raqrlamaol . spdng 40 0!6 r50a 500* 55096 600% 65 096 70 o.r 7501 800i 850% 900* 950% 100.0% Foreca6l Peak Load F*to. Figure F.l0 - Stand-alone Load Regulation Reserve Requirements-PACW 2017 PACW Load Forecast vs Error 5 0096 3roor $:oon(L izoo* '5 t 1 009c 0 u)!l- .t. 30 0t 35 0X40.0!arl5 0%50 0155 0%60 0X 65 0!170.0t75.0i80.09685 0*90 09695 096100.0L Fo.rcasl Pcd( l-oad F*tor 99 I I l. .l f;, PACIFICoRP _ 20I9 IRP APPI.,NI)IX F _ }LIXIBLE RISERVI.] Sft]DY The EIM is a voluntary energy imbalance market service tkough the CAISO where market systems automatically balance supply and demand for electricity every fifteen and five minutes, dispatching least-cost resources every five minutes. PacifiCorp and CAISO began full EIM operation on November l, 2014. A number of additional participants have since joined the EIM, and more participants are scheduled to join in the next several years. PacifiCorp's participation in the EIM results in improved power production forecasting and optimized intra-hour resource dispatch. This brings important benefits including reduced energy dispatch costs through automatic dispatch, enhanced reliability with improved situational awareness, better integration of renewable energy resources, and reduced curtailment of renewable energy resources. The EIM also has direct effects related to regulation reserve requirements. First, as a result of EIM participation, PacifiCorp has improved data used in the analysis contained in this FRS. The data and control provided by the EIM allow PacifiCorp to achieve the po(folio diversity benefits described in the first part of this section. Second, the EIM's intra-hour capabilities across the broader EIM footprint provide the opportunity to reduce the amount of regulation reserve necessary for PacifiCorp to hold, as further explained in the second part ofthis section. As shown in Table F-7 below, PacifiCorp calculated the proportional reduction to the standalone requirements that could be applied such that the PacifiCorp system achieves the target determined through the quantile regression on the Combined Diversity Error. A total portfolio requirement of 635 MW was the result of this regression, a reduction of 36 percent. Applyng this 36 percent reduction to each ofthe stand-alone regulation forecasts results in the diversity benefits shown in the second column. The last column shows the regulation requirements for each class after subtracting the portfolio diversity benefit. 100 The forecast results in an average 2017 stand-alone regulation reserve requirement for load of305 MW for the PacifiCorp system, or approximately 3.0 percent of the peak load. Portfolio Diversity and EIM Diversi8 Benefits Portfolio Diversity Benefit The regulation reserve forecasts described above independently ensure that the probability of a reliability violation for each class remains within the reliability target: however, the largest deviations in each class tend not to occur simultaneously, and in some cases deviations will occur in offsetting directions. Because the deviations are not occurring at the same time, the regulation reserve held can cover the expected deviations for multiple classes at once and a reduced total quantity of reserve is suffrcient to maintain the desired level of reliability. This reduction in the reserve requirement is the diversity benefit from holding a single pool of reserve to cover deviations in Solar, Wind, Non-VERs, and Load. As a result, the regulation reserve forecast for the portlolio can be reduced while still meeting the reliability target. For this reason the portfolio regulation requirements were calculated on the Combined Diversity Error. |0 (40)7oNon-VER 305 (ll0)195Load 434 (ts'7)217 145 (s3 )93VER - Solar 635Total994(360) Table F,7 - Results with PacifiCo Portfolio Diversi EIM Diversity Benefit In addition to the direct benefits from EIM's increased system visibility and improved intra-hour operational performance described above, the participation of other entities in the broader EIM footprint provides the opportunity to further reduce the amount of regulation reserve PacifiCorp must hold. By pooling variability in load, wind, and solar output, EIM entities reduce the quantity ofreserve required to meet flexibility needs. The EIM also facilitates procurement of flexible ramping capacity in the fifteen-minute market to address variability that may occur in the five-minute market. Because variability across different BAAs may happen in opposite directions, the flexible ramping requirement for the entire EIM footprint can be less than the sum of individual BAA requirements. This difference is known as the "diversity benefit" in the EIM. This diversity benefit reflects offsetting variability and lower combined uncertainty. This flexibility reserve (uncertainty requirement) is in addition to the spinning and supplemental reserve carried against generation or transmission system contingencies under the NERC standards. The EIM does not relieve participants oftheir reliability responsibilities. EIM entities are required to have sufficient resources to serve their load on a standalone basis each hour before participating in the EIM. Thus, each EIM participant remains responsible for alI reliability obligations. Despite these limitations, EIM imports from other participating BAAs can help balance PacifiCorp's loads and resources within an hour, reducing the size of reserve shortfalls and the likelihood of a Balancing Authority ACE Limit violation. While substantial EIM imports do occur in some hours, it is only appropriate to rely on PacifiCorp's diversity benefit associated with EIM participation, as these are derived from the structure of the EIM rather than resources contributed by other participants. Table F.8 below provides a numeric example of uncertainty requirements and application of the calculated diversity benefi t. l0l PAcTHCoRP - 2019 IRP APPENDLX F _ FEXTBLE RESF-RVE SI.(IDY Strnd-alore Regulation Forecast (aMWl Dlversity Betrefit (aMW) Portfolio Regulation Forecast (sMW)Scenario VER - Wind The CAISO calculates the EIM diversity benefit by first calculating an uncertainty requirement for each individual EIM BAA and then by comparing the sum of those requirements to the uncertainty requirement for the entire EIM area. The latter amount is expected to be less than the sum ofthe uncertainty requirements from the individual BAAs due to the portfolio diversification effect offorecasting a larger pool ofload and resources using intra-hour scheduling and increased system visibility in the hypothetical, single-BAA EIM. Each EIM BAA is then credited with a share of the diversity benefit calculated by CAISO based on its share of the stand-alone requirement relative to the total stand-alone requirement- Table F.8 - EIM Di Benefit A lication Exam le While the diversity benefit is uncertain, that uncertainty is not significantly different from the uncertainty in the Balancing Authority ACE Limit described above. In the 2019 FRS, PacifiCorp has credited the regulation reserve forecast with a historical distribution of calculated EIM diversity benefits. While this FRS considers regulation reserve requirements in 2017, the CAISO identified an error in their calculation of uncertainty requirements in early 2018. CAISO's published uncertainty requirements and associated diversity benefits are now only valid for March 2018 forward. To capture these additional benefits for this analysis, PacifiCorp has applied the historical distribution of EIM diversity benefits from March 20'18 through the beginning of this study in July 2018. Relatively small incremental EIM diversity benefits are expected going forward as additional entities participate in EIM; however, operational data on new participants was not available at the time the study was prepared. The inclusion of EIM diversity benefits in the 2019 FRS reduces the probability of reserve shortfalls and, in doing so, reduces the overall regulation reserve requirement. This allows PacifiCorp's forecasted requirements to be reduced. As shown in Table F.9 below, the resulting regulation reserve requirement is 531 MW, a 47 percent reduction (including the portfolio diversity benefit) compared to the stand-alone requirement for each class. The average regulation reserve requirement is reduced by 104 MW relative to the PacifiCorp portfolio reserve requirement without the EIM diversity benefit. The portfolio regulation forecast is expected to achieve an LOLP of 0.5 hours per year, based on a quantile regression at a 99.35 percent exceedance level. Table F.9 - 2017 Results with Portfolio and EIM Dive Benefits As previously discussed, Requirement I of BAL-001-2 specifies that PacifiCorp's CPSI score must be greater than equal to 100 percent for each preceding 12 consecutive calendar month period, evaluated monthly. The CPSI score compares PacifiCorp's ACE with interconnection frequency during each clock minute. A higher score indicates PacifiCorp's ACE is helping interconnection t02 I 550 I t0 165 100 925 583 342 31 .0o/o 6I 104 I l0 165 975 636 339 34.\Yo 5'1 t082600100 3 650 I l0 I65 I l0 1,035 689 146 55 I l0 4 66',7 120 180 3 I,080 '/42 338 31.1%56 t24 Non-VFIR ll0 5.'10/o 59 3.lo/o 1.912 I2 CP I-oad 305 3.00/o r63 t.60/"10,044 I2 CP VER - Wind 232 ? 750 Narneplate43415.8v.8.4v" VER - Solar 78 983 Nameplate14514.8%1 .90/o Total 994 531 APPF,NI)Ix t.._ FI.EXBLE RESERVF] SlI]I)YPACITICOR.P _20I9 IRP Fast-Ramping Ressrve Requirements Hour CAISO req't. before berefit (Mw) NEl? req't. before benefit (Mw) PACE rcq't. before beDelit (Mw) PACW req't before betrelit (M}v) Total req'L before beoelit (MW) Totrl req't. after bcoefit (Mw)(Mw) Totsl diverslty benefit (Nrw) Diversity benefit rstio (Mw) PACE benelit PACE req't. rfter benclit (Mw) 33.4% Sceoario Stand-alone Regulation Forecast (aMW) StEod- alonc Rate (Vo\ Portfolio Regulatlon Forecsst w/EIM (aM\ ) Portfollo Rrt€ to/ol 2017 Cspacity (MWl Rate Determinant --------T-------t PACTFTCoRT - 2019 IRP AppF:Nr)rx F - FrrxrBLE RTSERVE STttDy frequency, while a lower score indicates it is hurting interconnection liequency. Because CPSI is averaged and evaluated on a monthly basis, it does not require a response to each and every ACE event, but rather requires that PacifiCorp meet a minimum aggregate level ofperformance in each month. The 2017 Regulation Reserve Forecast described above is evaluating requirements for extreme deviations that are at least 30 minutes in duration, for compliance with Requirement 2 of BAL- 001-2. In contrast, compliance with CPSI requires reserve capability to compensate for the majority of over a minute to minute basis. These fast-ramping resources would be deployed frequently, and would also contribute to compliance with Requirement 2 of BAL-001-2, so they are a subset of the 2017 Regulation Reserve Forecast described above. To evaluate CPSI requirements, PacifiCorp compared the net load change for each five-minute interval in 2017 to the corresponding value for Requirement 2 compliance in that hour from the 2017 Regulation Reserve Forecast, after accounting for diversity (resulting in the 53 I MW average requirement shown in Table F.9). Resources may deploy for Requirement 2 compliance over up to 30 minutes, so the average requirement of 53 I MW would require ramping capability of at least 17.7 MW per minute (53 I MW / 30 minutes). Because CPS I is averaged and evaluated on a monthly basis, it does not require a response to each and every ACE event, but rather requires that PacifiCorp meet a minimum aggegate level of performance in each month. Resources capable ofensuring compliance in 95 percent of intervals are expected to be sufficient to meet CPS l, and given that ACE may deviate in either a positive or negative direction, the 97.5th percentile of incremental requirements was evaluated. This corresponds to 87 MW, or approximately 16.3 percent of the average Requirement 2 value. Because this value is for a five-minute interval, meeting it would require a ramping capability of at least 17.3 MW per minute (87 MW / 5 minutes). This value is actually slightly lower than the ramping capability for Requirement 2. Note that resources must respond immediately to ensure compliance with Requirement l, as performance is measured on a minute to minute basis. As a result, resources that respond after a delay, such as quick-start gas plants or certain intemrptible loads, would not be suitable for Requirement I compliance, so these resources cannot be allocated the entire regulation reserve requirement. However, because Requirement I compliance is a small portion ofthe total regulation resene requirement, these restrictions on resource tlpe are unlikely to be a meaningful constraint. In addition, CPS I compliance is weighted toward performance during conditions when interconnection frequency deviations are large. The largest frequency deviations would also result in deployment of frequency response reserves, which are somewhat larger in magnitude, though they have a less stringent performance metric under BAL-003-1, based on median response during the largest events. In light ofthe overlaps with BAL-001-2 Requirement 2 and BAL-003-l described above, CPSI compliance is not expected to result in an additional requirements beyond what is necessary to comply with those standards. 103 PACII'ICoRP _ 2O I9 IRP AppENDrx F - FtEXIBLE RrsERvE S' [)y The IRP portfolio optimization process contemplates the addition ofnew wind and solar capacity as part of its selection of future resources, as well as changes in peak load due to load growth and energy effrciency measures. As PacifiCorp's portfolio grows, the diversity ofthat portfolio is also expected to increase. As a result, incremental regulation reserve requirements are expected to be lower than the average requirement for a given portfolio. The need to develop realistic deviation data for a period during which resources did not exist makes measuring an incremental diversity effect a difficult proposition. Lrstead, PacifiCorp's FRS evaluated the change in regulation reserve requirements associated with cumulatively stacking the individual wind and solar facilities throughout the two BAAs. Under this methodology as each MW ofVERs is added to the system the rate of increase ofthe regulation reserve requirement is quantified and incorporated in the forecasted portfolio regulation results discussed later on in the study. Figure F.ll and Figure F.l2 show this relationship between increased capacity and increasing reserve requirements for wind and solar by BAA. Similarly for load the relationship between the daily peak load and the daily maximum error over the course of20l7 was observed for both BAAs and this relationship was extrapolated forward to develop a multiplier for the effect ofpeak load on the reserve requirements. A linear relationship between daily peak load and daily maximum error was observed for both BAAs as illustrated in Figure F.l3 through Figure F.14. Figure F.l I - Incremental Wind Capacity !ncremental Wind - Extrapolated 700 500 5m 400 3m 2W 100 0 500 1000 1500 2000 2500 3000 Capacity (MW) +PACE Wind +PACW Wind -PACE Wind Extrapolated -PACW Wind Extrapolated 104 3 E !! 0 Incremental Regulation Reserve Requirements PACIITCORP 2019 IRP AppENDx l'- Ft].xlt]r.Fr RESERVE STrrDy Figure tr'.12 - Incremental Solar Capacity !ncremental Solar - Extrapolated 450 400 350 300 3 =o trJ 250 200 150 100 50 0 0 200 400 500 800 1000 Capacity {MW) 1200 1400 1600 1800 {-PACE Solar -PACE Solar Extrapolated {-PACW Solar -PACW Solar Extrapolated 3 =o tu E 'i .0 = 500 00 m 00 00 a a 4 a aaaa a a i'o 3 tr aa ,taaaa 2 oO aa 1 a a a 4,000 5,000 5,000 7,000 8,000 Daily Peak toad (MWh) 9,000 10,000 a Max Error - Linear (Max Error) 105 Figure F.l3 - Increasing Peak Load-PACE PACE Daily Peak Load - Extrapolated 500 a a a I,ACITICoRP _ 2O I9 IRP AppE]\DD( [ - FLLXBLH RF]SERVE STUDY Figure F.l4 - Increasing Peak Load-PACW PACW Daily Peak Load - Extrapolated 400 350 t 3 2 2 1 1 00 50 m 50 m a t aa aaa aI aaa a a a 50 0 2,000 -a 2,500 3,000 3,500 4,000 Daily Peak toad (MWh) 4,500 s,000 Overvielv A single pool of regulation reserve is held to cover deviations by load, wind, solar, and non- dispatchable generation. Simultaneous large deviations by all classes are unlikely - as a result, this pool ofregulation reserve can be smaller than what these classes would require on their own. The reduction in regulation reserve is a result of the diversity ofthe portfolio ofrequirements. The most important element in PacifiCorp's portfolio diversity estimate is the system diversity, including EIM benefits, associated with load, wind, solar and Non-VERs during 2017. This diversity reduced reserve requirements by 47 percent. This captures the majority of the regulation reserve requirements today and in likely future scenarios over the near tern. However, as PacifiCorp's portfolio evolves over time, the regulation reserve requirements and diversity associated with that portfolio will vary. This section describes how incremental regulation reserve requirements for load, wind, and solar are combined to produce portfolio-specific requirements. Results Table F.l0 presents the portfolio regulation requirement results for various scenarios. As the wind and solar capacity on PacifiCorp's system increases, regulation requirements increase, but those requirements are partially offset by the increasing diversity ol the portfolio. The 2019 base case regulation reserve requirements are 531 MW. By comparison, PacifiCorp's 2017 base case from the 2Ol7 IRP identified regulation reserve requirements of 617 MW. 106 a i =o UJ E E't a0 = a a a Max of Error -Linear (Max of Error) Portfolio Regulation Reserve Requirements Table F.lo - Total tion uirement b Scenario Table F.l I presents a comparison ofthe regulation reserve requirement results in the current study and the prior study. Table F.ll - Portfolio tion urremen Percent of Na late/Peak C The 2019 FRS calculates the regulation reserve requirement for the entire po(folio implicitly accounting for diversity among components at various penetration levels. This allows incremental requirements for load, wind and solar to be aligned with the new resource additions being contemplated in the IRP. The incremental requirements for wind are slightly higher than the average requirements for wind when diversity is included, but still well below the stand-alone requirements for wind without diversity. On the other hand, the incremental requirements for solar are less than the average requirements for solar even when diversity is included. These outcomes are reasonable since solar capacity is smaller than wind capacity in the evaluated portfolio, so incremental solar capacity makes the portfolio relatively more diverse. For the first time, the 2019 FRS accounts for the incremental impact ofchanges in forecasted load on regulation reserve requirements. For instance, energy efficiency selections (which reduce load), also reduce reserve requirements. The impact ofthese changes is accounted for within the results reported by the PaR model. Regulation Reserve Cost A series of PaR scenarios were prepared to isolate the regulation reserve cost associated with incremental wind and solar capacity additions as discussed below. All studies reflect regulation reserve requirements on an hourly basis. l. Base Case The base case portfolio is the same as that used to set the planning reserve margin for the 2019 IRP, as discussed in Appendix I. This case incorporates assumptions consistent with the 2Ol7 IRP Update, updated to reflect current inputs as of August 2018 and without any wind or solar resources additions beyond those that had already been committed at that time. This case was evaluated over the study period 2018-2036. t07 2017 Base Case 2015 Actuals + Projected Solar 2,751 I,050 6t7 2019 Base Case 2019 Forecast 20l9Incr. Wind 2019Incr. Solar 2017 Actuals 2030 Portlblio 2030 Portfolio + 500 MW Wind 2030 Portfolio + 500 MW Solar 2;750 3.r96 3,696 3,196 1.021 2,201 2,201 2,70t 531 6't2 722 698 2.8%8.90/.2.4%20t7 FRS Basc Casc 4.60/o ,m5 m l.60/o 3.0% I.40/. 15.8% lO.lo/o 3.t% 5.1Yo 2019 FRS Base Case Sensitivities: Without diversity Incremcntal Wind Incremental Solar 7.9o/o t4.8% 5.lo/o 2017 portlblio 2030 ponfolio: +500 MW wind 2030 portfolio: +500 lvfW solar 20 t7 portlblio m PACIFICoRP 20I9IRP APPENDIX F _ FI.EXBLE RESERVE SIIiDY Case Portfolio Wind Capacity (MW) Solsr Crpscity (MWl Regulation Requirement wlth Dlversity (MW) WindStudvLoad Non-VER Solar Notes PACI}ICORP _ 20 I9 IRP AppENDx !' - Ft-ExBLE RESERVE S rtJDy 2. Wind Reserve Case The wind reserve case adds the incremental regulation reserve requirement associated with 500 MW of proxy wind resource additions. Wind capacity increases by 100 MW at each of five locations: Dave Johnston, Goshen, Utah South, Walla Walla, and Yakima. The addition of this wind capacity results increases regulation reserve requirements by an average of 50 MW. This case was evaluated for the study period 2030. Wind integration costs are equal to the increase in system cost in Study 2 relative to Study l, divided by the incremental wind generation. 3. Solar Reserve Case The solar reserve case adds the incremental regulation reserve requirement associated with 500 MW of proxy solar resource additions. Solar capacity increases by 250 MW in Utah South and by 125 MW each in Southern Oregon and Yakima. The addition of this solar capacity results increases regulation reserve requirements by an average of 24 MW. This case was evaluated for the study period 2030. Solar integration costs are equal to the increase in system cost in Study 3 relative to Study I, divided by the incremental solar generation. 4. 50 MW Reserve Case This case includes an additional 50 MW reserve requirement in every hour. This case was evaluated over the study period 2018-2036 and was used to escalate the wind and solar results over time, relative to the 2030 values. 108 The incremental regulation resen e cost results for wind and solar are shown in Figure F.15. The comparable regulation reserv'e costs from the 2017 FRS are also shown. While regulation reserve costs in 2018 are comparable to the result in the prior study, the 2019 FRS demonstrates how these costs are expected to vary over time. Figure F.l5 - Incremental Wind and Solar Regulation Reserve Costs s2.oo s1.80 -c. o (! oUo o oG.c ]:ll, f ooot So.oo?ot7 2019 202t 2023 2025 2027 ?O?9 2031 2033 2035 -2019lRP Wind 2019 IRP Solar o 2017 IRP Wind o 2017 IRP Solar The difference in regulation reserve costs for wind and solar reflects timing differences. Per MWh of generation, the wind reserve obligation is approximately 60 percent higher than the solar obligation; however, the solar obligation is higher during the summer when market prices and marginal reserve costs are typically higher. As a result, per MWh of generation, wind integration costs are only slightly higher than solar integration costs. The 2019 FRS results are applied in the portfolio development process as an additional cost for proxy wind and solar generation resources available for selection within the SO model. Once the SO modeI has developed a candidate resource portfolio, the PaR model is used to evaluate portfolio risks. The PaR model inputs include regulation reserve requirements specific to the resource portfolio developed using the SO model, so the costs identified in the 2019 FRS are not applied in the PaR results. Instead, the IRP risk analysis using PaR specifically accounts for both differences in regulation reserve requirements and the resources available to meet those requirements in each portfolio. When evaluated in PaR, a portfolio will be evaluated on its ability to meet operating reserve requirements, including regulation reserves, but as indicated previously, the SO model does not account for either reserve obligations or the reserve capability that resources can provide. While integration costs have previously been used to account for regulation reserve obligations, for the first time in the 2019 IRP an analogous credit has been applied to highly flexible resources that primarily provide operating reserves. This "operating reserve credit" has been applied to proxy storage, gas peaking units, and Class I DSM (intemrptible load) that are available for selection 109 s1 s1 Sr so $o 5o 60 40 s1.20 00 80 60 40 So.2o Study Period 2OL7 IRP:2077 2019 IRP: 2018-2036 PACII,CoRP _ 2OI9 IRP APPENDX I. _ FI.I.,xIBI-E RISERVI STT,DY PACTFTCoRT - 2019 IRP APPENDD( F _ FItr]XIBLE R.ESERVI.] S'I'IJDY within the SO model. While other resources, such as combined cycle gas plants and renewables, are also capable of providing operating reserves these resources primarily provide energy which the SO model is already accounting for. As a result, no operating reserve credits are applied to these other resources. For a resource that is available throughout the year, such as a gas peaking unit, the operating reserve credit amounts to $50/kw-year (2018S), based on the costs calculated in the 50 MW Reserve Case relative to the Base Case. For resources with limited availability, such as seasonal Class I DSM resources or storage combined with wind or solar, the credits are prorated to account for the periods when a resource provides operating reserves. Overvierv In its Order No. 12013 issued on January 19,2Ol2 in Docket No. UM 146l on "Investigation of matters related to Electric Vehicle Charging", the Oregon Public Utility Commission (OPUC) adopted the OPUC stafls proposed IRP guideline: Forecast the Demand for Flexible Capacity: The electric utilities shall forecast the balancing reserves needed at different time intervals (e.g. ramping needed within 5 minutes) to respond to variation in load and intermittent renewable generation over the 20- year planning period; 2. Forecast the Suppty ofFlexible Capacity: The electric utilities shall forecast the balancing reserves available at different time intervals (e.g- ramping available within 5 minutes) from existing generating resources over the 20-year planning period; and 3. Evaluate Flexible Resources on a Consistent and Comparable Basis: ln planning to fill any gap between the demand and supply of flexible capacity, the electric utilities shall evaluate all resource options including the use of electric vehicles (EVs), on a consistent and comparable basis. In this section, PacifiCorp first identifies its flexible resource needs for the IRP study period of 2019 through 2038, and the calculation method used to estimate those requiremens. PacifiCorp then identifies its supply offlexible capacity fiom its generation resources, in accordance with the Western Electricity Coordinating Council (WECC) operating reserve guidelines, demonstrating that PacifiCorp has sufficient flexible resources to meet its requirements. Forecasted Reserve Req uirements Since contingency reserve and regulation reserve are separate and distinct components, PacifiCorp estimates the forward requirements for each separately. The contingency reserve requirements are derived from stochastic simulations run using the Planning and Risk (PaR) model. The regulating reserve requirements are part of the inputs to the PaR model, and are calculated by applying the methods developed in the Portfolio Regulation Resewe Requirements section. The contingency and regulation reserve requirements include three distinct components and are modeled separately in the 2019 IRP: lO-minute spinning reserve requirements, lO-minute non-spinning reserve requirements, and 3O-minute regulation reserve requirements- The reserve requirements for PacifiCorp's two balancing authority areas are shown in Table F.12 below. u0 Fleilble Resource Needs Assessment 193 359 932019193 93 196 2020 t94 It)4 377 94 207 t02l t94 194 491 96 96 2ll 196 493 91 r)72022196 198 2023 t99 199 502 97 97 t96 2024 202 20)593 98 9ri 283 203 203 60t 99 282 2026 203 203 592 99 99 2tt0 2027 205 205 591 100 100 2',711 207 ?07 591 l0l l0l2028 275 2029 208 208 539 l0l t0l 2lltt 2030 2t0 210 651 102 102 286 2t2 2t2 642 102 102 286 2t4 644 t0220322t4 102 282 2033 215 2t5 626 I02 t02 296 216 2t6 620 102 1022034 296 2t7 2t1 604 l0l t0t2035 299 2036 2t<)219 601 l0l l0l 3 011 203',7 220 220 600 l0t t0l 307 221 22t 560 l0l l0l 30t Table F.l2 - Reserve uirements Flexible Resource Supply Forecast Requirements by NERC and the WECC dictate the types of resources that can be used to serve the reserve requirements. l0-minute spinning reserve can only be provided by resources cunently online and synchronized to the transmission grid; l0-minute non-spinning reserve may be served by fast-start resources that are capable of being online and synchronized to the transmission grid within ten minutes. Intemrptible load can only provide non-spinning reserve. Non-spinning reserve may be provided by resources that are capable ofproviding spinning reserve. o 3G.minute regulation reserve can be provided by unused spinning or non-spinning reserve. Incremental 30-minute ramping capability beyond the l0-minute capability captured in the categories above also counts toward this requirement. The resources that PacifiCorp employs to serve its reserve requirements include owned hydro resources that have storage, owned thermal resources, and purchased power contracts that provide reserve capability. Hydro resources are generally deployed first to meet the spinning reserve requirements because of their flexibility and their ability to respond quickly. The amount ofreserve that these resources can provide depends upon the difference between their expected capacities and their generation level at the time. The hydro resources that PacifiCorp may use to cover reserve requirements in the PacifiCorp West balancing authority area include its facilities on the Lewis River and the Klamath lll PACIFICORP _ 20 I9 IRP APPENDD( F _ TujxIBt,E RESERVE STLTDY .}tlt Year East RequiremeDt West Requiremcnt Spin (10-minute) Non-spin (10-mlnute) Regul&tion (30-minute) Spin (10-minute) Non-spin Il0-minulel Regulation (30-minute) 94 2025 t)t) 203 r 2038 PACITICoRP _ 2OI9 IRP APPENDD( F _ FLEXIBLE RESERV}; S ITJDY River as well as contracted generation from the Mid-Columbia projects. ln the PacifiCorp East balancing authority area, PacifiCorp may use facilities on the Bear River to provide spinning reserve. Thermal resources are also used to meet the spinning reserve requirements when they are online. The amount ofreserve provided by these resources is determined by their ability to ramp up within a lO-minute interval. For natural gas-lired thermal resources, the amoturt of reserve can be close to the differences between their nameplate capacities and their minimum generation levels. In the current IRP, PacifiCorp's reserve are served not only from existing coal- and gas-fired resources, but also from new gas-fired resources selected in the preferred portfolio. Table F.l3 lists the annual reserve capability from resources in PacifiCorp's East and West balancing authority areas.20 All the resources included in the calculation are capable ofproviding all types ofreserve. The non-spinning reserve resources under third party contracts are excluded in the calculations. The changes in the flexible resource supply reflect retirement of existing resources, addition ofnew preferred portfolio resources, and variation in hydro capability due to forecasted streamflow conditions, and expiration ofcontracts from the Mid-Columbia projects that are reflected in the preferred portfolio. Table F.l3 - Flexible Resource Su Forecast Figure F.16 and Figure F.l7 graphically display the balances of reserve requirements and capability of spinning reserve resources in PacifiCorp's East and West balancing authority areas 2o Frequency rcsponse capability is a subset of the l0-minute capability shown. Battery resorrrccs are capable of responding with their maximum output during a frequency event, and can provide an evcn €treater response il they were charging at the start ofan event. PacifiCorp has sufiicient frequency response capability at present and by 2024 the battery gapflcity added in the prcl'crred pont'olio will excced ofPacifiCorp's current 202.8 MW frcquency response obligation fbr a 0.3 Hz event. As a rcsult, compliance with the frcquency response obligation is not anticipated to require incremental supply. tt2 2019 1,843 701 2528 965 2020 1.893 703 2 528 967 202t 1,897 684 24'12 948 2022 t,9t3 611 2488 935 2023 t,931 683 2387 94'7 2024 2,158 965 26t3 t262 2025 2,16(t 963 2621 t260 2026 ) 11p 2134 t260 2027 ') )')!a 964 2134 t26t 2028 2,t44 1,143 2650 t440 2029 ?,?(t8 1,645 2',711 I876 203 0 2,562 I,645 2987 t876 201I ) sq,1.645 3017 1876 2,604 1.765 3 019 1996 2033 2,604 I,tilt4 3029 2016 2034 2.426 1.884 2'789 2016 2035 2,44t I,884 2804 2016 2036 2,415 1,988 2808 2r20 203'7 3,104 2,240 3308 2172 2038 3,601 2.(t22 3804 2622 Year East Supply (10-Minute) West Supply (10-Minute) East Supply (30-Minute) West Supply (30-Minute) 963 2()12 P^CIFICORP _ 2OI9 IRP APPENDIX F _ III.EXIBLI, ITESERVE STUDY respectively. The graphs demonstrate that PacifiCorp's system has sufficient resources to serve its reserve requirements throughout the IRP planning period. Figure F.l6 - Comparison of Reserve Requirements and Resources, East Balancing Auth Area (MW) 4.000 3.500 3.000 2.5m 2.000 1.500 1.000 500 0 %., 9r, *g %f, %., 8., Bt, Br, %r-, %r* 8., B% 9". %* ts* %r, Br. gr,sr, Br, r Requfueoletrt: spin ( lo-minute) - Requircm€nt: ReSulation (SGminute) -:- East srpply (3GMinue) r Requfuem€ot: No[-spfu ( lGulinue) -East Swply ( lGMintre) I Figure F.17 - Comparison of Reserve Requirements and Resources, West Balancing Aut Area 4.000 3.500 3.000 2.500 a 2.ooo2 1.500 1.000 500 n r Requfu€rnent: Spin ( lO-minute) r Requfuem€nt: Regulation (30-minute) ----r- west sryply (3GMinute) JJJJJJJJJJJJJJJJJ'?., '3d '4.-r, 'o.ro '4.r, '?-'o.r., '?, aoo ?9 bu., ?o, 'oo, 'S, bo, bo- ?o,B.rB.,rs+ I l-3 I IIIII IIIIIITIIIITII r RequheDent: Non-spin ( lGmhrtre) - West Srryply (lGMinue) I I I T T T I IrIIIITIITI PacifiCorp and the California Independent System Operator Corporation implemented the energy imbalance market (EIM) on November l, 2014, and participation by other utilities has expanded sigrrificantly with more participants scheduled for entry throtgh 2022. By pooling variability in load and resource output, EIM entities reduce the quantity of reserve required to meet flexibility needs. Because vanability across different BAAs may happen in opposite directions, the uncertainty requirement for the entire EIM footprint can be less than the sum of individual BAAs' requirements. This difference is known as the "diversity benefit" in the EIM. This diversity benefit reflects offsetting variability and lower combined uncertainty. PacifiCorp's regulation reserve forecast includes a credit to account for the diversity benefits associated with its participation in EIM. As indicated in the OPUC order, electric vehicle technologies may be able to meet flexible resource needs at some point in the future. However, the electric vehicle technology and market have not developed sufliciently to provide data for the current study. Since this analysis shows no gap between forecasted demand and supply of flexible resources over the IRP planning horizon, this IRP does not evaluate whether electric vehicles could be used to meet future flexible resource needs. il4 PACIFICoRP _ 2019 IRP APPENDD( F _ FIIXIBLD RESERVE STUDY Flexible Resource Supply Planning In actual operations, PacifiCorp has been able to serve its reserve requirements and has not experienced any incidents where it was shon ofreserve. PacifiCorp manages its resources to meet its reserve obligation in the same manner as meeting its load obligation - through long term planning, market transactions, utilization ofthe transmission capability between the two balancing authority areas, and operational activities that are performed on an economic basis. PACI,TCORP - 20l9IRP A-pptNl)tx (i- PLANT WAr FrR CoNSUMp'lloN AppBNorx G - PlaNr Wersn CoNsunaprroN The information provide in this appendix is for PacifiCorp owned plants. Total water consumption and generation includes all owners for jointly-owned facilities. ll5 ooI]. .9.o Q \o o (ll q7 @ c\l o o) q) cl o o-o q) bI) !.) o $ (! I 0)bI) h clo F , ooc.l t> 'F.2iv ooe o0 b0cq !ac!^9;; .r, oEt'=,ar tr c.l dj q.) (u:: =oH ./)e.g eg ia 4., E} =-2) ia ADi= -EZ *ra Ir €q) I L oU 6l I 4) z : z O Fz<, 5az o- o. I 9 o\ c\;d} =\c- ] 3. \ o \ 1 ai 'd .o. -t a .-.r rt > z z z z .3 E! U U I o o 5 5 E p J Eb z I + >' >E F \c !isi .c' F I I es E z .Js t- T]TAH PLANTS 2012 2013 2014 2015 2016 2017Plant Narne Curant Creek 90 92 t24 il6 259Gadsby1,059 367 t00 18,266 I7.00 r t6-662 16,386 14.225 r5,383 10,643 9,888 9.r89 9,653Hr-ntington t0,423 I .361 1 169 3,619 2,698I,693 2.960 29,699 30,320 29,9E0 27,419 27,gs0TOTAL31,531 Table G.2 - Plant Water Consum tion b State acre.feet Percent of total water consumpti on = 42.3 Table G.3 - Plant Water Consum tion b Fuel T e acre.feet Percent oftotal water consumption = 93.7 l7 WYOMINGPLANTS Plant Narne 2012 2013 2014 20r5 2016 2017 8.941 9,736 8.864 8.231 Jim Brrdger 23,977 25.O59 23.936 ,? 101 18.000 19,047 Naughton 8,745 9.622 7,484 7,?15 6,896 6,927 Wyodak 322 319 332 228 329 332 TOTAL 40,765 43,941 41,225 39,672 34,089 34,537 COAL FIRED PI..ANTS 2012 2013 2014 2015 2016 2017Plant Name 8.941 9,474 s 716 8.864 8,231Dave Johrston 7,72t Hmter 18,266 r 7.001 16,662 16,386 t4.225 l5 lRl Huntington t0.423 10,643 t 0.240 9,888 9.1 89 9,653 ,5 osq 23,936 22.493 18,000 t9,o47Jim BriJger 23.977 9,622 7,484 7,215 6,896Nauglton8.745 3t9 228 329 -t)-LWyodak322 69,454 71,585 68,127 65,946 57,503 59,573TOTAL NATI]'RAL GAS FIRED PLAI{TS Plant Narne 2012 2013 2014 2015 2016 2017 Cr.rrant Creek 90 84 l l6 55 6()t50 52 48 Gadsbv I.059 610 259 Iake SiIe t.693 r ,361 2,960 1?6S 3.6r9 2,698 TOTAL 2,897 2,141 3,568 3,758 4,053 2,968 PACTFTCoBT - 2019lRP APPENDD( G - PLANT WerER CoNsur'rprroN Percent oftotal water consumption = 55.9 84 78 610 262 Hunter 10.240 Iake Side Dale Johrston 7,72t 9.47 4 6.927 ) ),/. 92 t6 r24 Chehalb 54 367 262 100 Percent of total water consumption:4.6 16,386 14.225 15,383Hurtert8,266 r 7,001 16.662 Hrurtington 10,423 t0.643 10.240 S RRR 9,189 9,653 Nauglron 8,745 9,622 7,484 7,215 6,896 6,927 Jim Brileer 23,977 25.059 23,936 ,, dqt 18,000 t9,o47 PACTFTCoRP - 2019 IRP AppENDrx (i - PLAN r WATER CoNsuMprroN Table G.4 - Plant Water Consumption for Plants Located in the Upper Colorado River Basin acre-feet Percent oftotal water consumption = 82.0 ll8 2012 2013 2015 2016 2017Plant Name 2014 55.9E2 5r.0r0TOTAL6r,4rr 62,325 58,322 48,310 ApppNprx H - SrocHASTrc PRRevsrpRs For this IRP, PacifiCorp updated and re-estimated the stochastic parameters provided in the 2017 IRP for use in the Planning and Risk (PaR) model runs. PaR. as used by PacifiCorp, develops portfolio cost scenarios via computational finance in concert with production simulation. The model stochastically shocks the case-specific underlying electricity price forecast as well as the conesponding case-specific key drivers (e.g., natural gas, loads, and hydro) and dispatches accordingly. Using exogenously calculated parameters (i.e., volatilities, mean reversions, and correlations), PaR develops scenarios that bracket the uncertainty surrounding a driver; statistical sampling techniques are then employed to limit the number of representative scenarios to 50. The stochastic model used in PaR is a two-factor (short- and long- run) mean reverting model. PacifiCorp used short-run stochastic parameters for this Integrated Resource Plan (IRP); long-run parameters were set to zero since PaR cannot re-optimize its capacity expansion plan. This inability to re-optimize or add capacity can create a problem when dispatching to meet extreme load and/or fuel price excursions, as often seen in long-term stochastic modeling. Such extreme out-year price and load excursions can influence portfolio costs disproportionately while not reflecting plausible outcome. Thus, since long-term volatility is the year-on-year growth rate, only the expected yearly price and./or load growth is simulated over the forecast horizonr. Key drivers that significantly affect the determination of prices tend to fall into two categones: loads and fuels. Targeting only key variables from each category simplifies the analysis while effectively capturing sensitivities on a larger number of individual variables. For instance, load uncertainty can encompass the sensitivities ofweather, transmission availability, unit outages, and evolving end-uses. Depending on the region, fuel price uncertainty (especially natural gas) can encompass the sensitivities of weather, load growth, emissions, and hydro availability. The following sections summarize the development ofstochastic process parameters and describe how these uncertain variables evolve over time. Long-term planning demands specification ofhow important variables behave over time. For the case of PacifiCorp's long-term planning, important variables include natural gas and electricrty prices, regional loads, and regional hydro generation. Modeling these variables involves not only a description oftheir expected value over time as with a traditional forecast, but also a description of the spread of possible future values. The following sections summarize the development of stochastic process parameters to describe how these uncertain variables evolve over time2. I Mean reversion is assumed to be zero in the loug run- 2 A stochastic or random process is the counterpart b a deterministic process. lnstead ofdealing with only one possible reality ofhow the variables might evolvc ovqr time, there is some indeterminacy in the futule evolution described by probability distributioDs. ll9 AppENDrx H - STocHASTIc PARAMETERSPACTFTCoRP - 2019 IRP Introduction Overview PACTFTCoRP - 2019 IRP AppENDrx H - STocHAsfl c PARAMETERS The standard deviationr(o) is a measure of how widely values are dispersed from the average value: Xi'=r(ri - P)2 (n-1) where p is the average value of the observations {xl, x2,...,xn}, and n is the number ol observations. Volatility (dr) incorporates a time component so a variable with constant volatility has a larger spread ofpossible outcomes two years in the future than one year in the future: I=oT=o!l Volatilities are typically quoted on an annual basis but can be specified for any desired time period (I). Suppose the annual volatility of load is two percent. This implies that the standard deviation of the range of possible loads a year from now is two percent, while the standard deviation four years from now is four percent. If volatility was constant over the forecast period, then the standard deviation would increase linearly with the square root of time. This is described as a "Random Walk" process and often provides a reasonable assumption for long-term uncertainty. However, for energy commodities as well as many other variables in the short-term, this is not typically the case. Excepting seasonal effects, the standard deviation increases less quickly with longer forecast time. This is called a mean reverting process - variable outcomes tend to revert back towards a long-term mean after experiencing a shock. I "Standard Deviation" and "Variance" are standard statistical terms describing the spread ofpossible outcomes. The Variance equals the Standard Deviation squared. 120 Volatilitv o= Mean Reversion PA( rHCoR? - 2019 IRP App[NDlx II - s lo( HAsnc PARANtT:TERs Figure H.l - Stochastic Processes 2.5 2.O <--- Observed , Forecast--> t\Random Walk Expectation (,!Eq, .9 al 1.5 1.0 {ttT:: 0.5 0.0 0 10 20 40 50 60 For a random walk process, the distribution of possible future outcomes continues to increase indefinitely, while for a mean reverting process, the distribution ofpossible outcomes reaches a steady-state. Actual observed outcomes will continue to vary within the distribution, but the distribution across all possible outcomes does not increase: Figure H.2 - Random Walk Price Process and Mean Reverting Process Random Walk Price Process Mean Reverting Price Process 30 Time to Delivery The volatility and mean reversion rate parameters combine to provide a compact description ofthe distribution ofpossible variable outcomes over time. The volatility describes the size ofa typical shock or deviation for a particular variable and the mean reversion rate describes how quickly the variable moves back toward the long-run mean after experiencing a shock. IZt AppENDIx H - ST(rHAsrrc PARAME rERs Short-term uncertainty can best be described as a mean reverting process. The factors that drive uncertainty in the short-term are generally short-lived, decaying back to long-run average levels. Short-term uncertainty is mainly driven by weather (temperature, windiness, rainfall) but can also be driven by short-term economic factors, congestion, outages, etc. The process for estimating short-term uncertainty parameters is similar for most variables of interest. However, each of PacifiCorp's variables have characteristics that make their processes slightly different. The process for estimating short-term uncertainty parameters is described in detail below for the most straightforward variable - narural gas prices. Each ofthe other variables is then discussed in terms ofhow they differ from the standard natural gas price parameter estimation process. The first step in developing process parameter estimates for any uncertain variable is to determine the form ofthe distribution and time step for uncertainty. In the case of natural gas, and for prices in general, the lognormal distribution is a good representation of possible future outcomes. A lognormal distribution is a continuous probability distribution of a random variable whose logarithm is normally distributeda. The lognormal disribution is often used to describe prices because it is bounded on the bottom by zero and has a long, asymmetric "tai[" reflecting the possibility that prices could be significantly higher than the average: Figure H.3 - Lognormal Distribution and Cumulative Lognormal Distribution Lognormal Distrlbution Cumulative [oBnormal Distribution The time step for calculating uncertainty parameters depends on how quickly a variable can experience a significant change. Natural gas prices can change substantially fiom day-to-day and are reported on a daily basis, so t}te time step for analysis will be one day. a A normal distribution is the most common continuous distribution represented by a bell-shaped cuwc lhat is synxnetrical about the mean, or average, value. 122 PACTTTCoRP - 20t9 IRP Estimating Short-term Process Parameters Stochastic Process PACTFTCoRP 20l9lRP AppE].'DIx H -ST(x HAS'tr(' PARAMETERS All short-term parameters were calculated on a seasonal basis to reflect the different dynamics present during different seasons ofthe year. For instance, the volatility ofgas prices is higher in the winter and lower in the spring and summer. Seasons were defined as follows: Table H,l - Seasonal Definitions Data Development Basic Data Seti The natural gas price data was organized into a consistent dataset with one natural gas price for each gas delivery point reported for each delivery day. The data was checked to make sure that there were no missing or duplicate dates. [f no price is reported for a particular date, the date is included but teft blank to maintain a consistent 24-hour time step between all observed prices. Four years of daily data from 2014 to 201 7 was used for this short-term parameter analysis. The following chart shows the resulting data set for the Sumas gas basin: ure H.4 - Dail Gas Prices for SUMAS Basin,2014-2017 30 E1s'i =10o 5 ian-14 )u!14 Dec 14 Jul-15 Dec-15 Jun-15 Dec-1.6 Jun-17 Dec-17 Development of Price Index: Uncertainty parameters are estimated by looking at the movement, or deviation, in prices from one day to the next. However, some of this movement is due to expected factors, not uncertainty. For instance, gas prices are expected to be higher during winter or as we move toward winter. This 123 Winter Decembcr, January, and February Spring March. April, and May Summer June, July, and August Fall September, October, and Novcmbcr P^crrrCoRP - 2019 IRP APPENDlx H _ ST(TIhSTIC PARAMFTLRS expectation is already included in the gas price forecast and should not be considered a shock, or random event. In order to capture only the random or uncertain portion ofprice movements, a price index is developed that takes into account the expected portion of price movements. Three categories of price expectations are calculated: Seasonal Averaqe: The level ofgas prices may be different from one year to the next. While this can be attributed to random movements or shocks in the gas markets, it is not a short- term event and should not be included in the short-term uncertainty process. In order to account for this possible difference in the level ofgas prices, the average gas price lor each season and year is calculated. For example, Sumas prices in the winter of 2014 average $4.92,MMBtu. Monthly Averaqe: Within a season , there are different expected prices by month. For instance, within the fall season, November gas prices are expected to be much higher than September and October prices as winter is just around the corner. A monthly factor representing the ratio of monthly prices to the seasonal average price is calculated. For example, February prices in Sumas are 106 percent ofthe winter average price. Weeklv Shaoe: Many variables exhibit a distinct shape across the week. For instance, loads and electricity prices are higher during the middle ofthe week and lower on the weekends. The expected shape of gas prices across the week was calculated and found to be insignificant (expected variation by weekday did not exceed two percent of the weekly average). These three components seasonal average, monthly shape, and weekly shape - combine to form an expected price for each day. For example, the expected price of gas in Sumas in February of 2014 was $5.22lMMBtu, the product ofthe seasonal average and the monthly shape factor The following chart shows the comparison ofthe actual Sumas prices with the "expected" prices: t24 Expected Gas Price - Seasonal Avg. Price * Monthly Shape within the Season ActualPrices Expected Praces ian'14 lul 14 0ec-14 iul-15 0ec-15 Jun-16 ,un-17Dec-16 0ec-17 5 30 2S e20 E .g$a I810 o PACIFICoRP - 2019 IRP AppEN'Dtx H - STocHASTIc PAR^METERS ure H.5 -Gas Prices for SUMAS Basin with "e ctedtt rlc 2014-2017 Dividing the actual gas prices by the expected prices forms a price index that averages one. This index, illustrated by the chart below, captures only the random component ofprice movements- the portion not explained by expected seasonal, monthly, and weekly shape. 125 I',\( lflCoRP 20l9lRP APPENDIX H _ STCTHASTIC PARAMEI ERS Figu re H.6 - Gas Price Index for SUMAS Basin, 2014-2017 6 5 4 3 7 I lan-14 Jul-14 Dec-14 lul-15 Dec'15 Jun'16 Oe€-16 lun-77 Dec-r7 Parameter Estimation - Autoregressive Model Uncertainty parameters are calculated for each variable by regressing the movement of each region's price index compared to the previous day's index. Step 2 - Perform Regression The log deviations ofprice index are regressed against the previous day's logarithm ofprice index for each season as well as for the entire data set. The following chart shows the log ofthe price index versus the log deviations for Sumas gas for all seasons and the resulting regression equation: t26 Step I - Calculate Log Deviation of Price Index Since gas prices are lognormally distributed, the regression analysis is performed on the natural log of prices and their log deviations. The log deviations are simply the differences between the natural log ofone day's price index and the natural log ofthe previous day's price index. I .> P^( nrCoRP - 20l9IRP AppENDIx H - SToCHASTIC PARAMI]]IRS fisue E. z-: reesur&r ru!44! 9:s Basin 1.50 1.@ o.50 y= o.1029x 0.0013 Rr - 0.o515 The last component of the regression analysis is the STANDARD ERROR or STEYX. This measures the portion of the price movements not explained by mean reversion and is the estimate of the variable's volatility. Both the mean reversion rate and volatility calculated with this process,ue daily parameters and can be applied directly to daily movemenls in gas prices. Step 4 - Results The natural gas price parameters derived through this process are reported in the table below. a {r.m)(csoi .t..a"' o:5o ' {o.so)' 11.0o) {r.so) Step 3 - Interpret the Results The INTERCEPT of the regression represents the log of the long-run mean, So in this case, the intercept is approximately zero, implying that the long-run mean is equal to one. This is consistent with the way in which the price index is formulated. The SZC)PE ofthe regression is related to the auto conelation and mean reversion rate: auto cot"?"eLation - @ = | I slope Mean Reuersion Rate d = -ln(0) The autocorrelation measures how much ofthe price shock from the previous time period remarns in the next time period. For instance, if the autocorrelation is 0.4 and gas prices yesterday experienced a l0 percent jump over the norm, today's expected price would be 4 percent higher than normal. In addition, today's gas price will experience a shock today that may result in prices higher or lower than this expectation. The mean reversion rate expresses the same thing in a different manner. The higher the mean reversion rate, the faster prices revert to the long-run mean. 127 Prlcelnd.x lo6arlthm AppF.NDIx H - s r(x ttAsIC PAR^METIRS SpringWinter Summer Fall KERN OPAL Daily Volatility Daily Mean Reversion Rate 11'.t4Yo 0.110 3.9e/" 0.152 2.460/o 0.102 3.620/o 0.071 SUMAS Daily Volatility Daily Mean Reversion Rate t2.w% 0.092 6.07% 0.26s 4.87% 0.105 4.38% 0.!o7 Table H.2 - Uncertain Parameters for Natural Gas Electricity Price Process For the most part, electricity prices behave very similarly to natural gas prices. The lognormal distribution is generally a good assumption for electricity. While electricity prices do occasionally go below zero, this is not common enough to be worth using t}e Normal distribution assumption, and the distribution of electricity prices is often skewed upwards. In fact, even the lognormal assumption is sometimes inadequate for capturing the tail of the elecricity price distribution. Similar to gas prices, electricity price can experience substantial change from one day to the next, so a daily time step should be used. Basic Dala Set: The electricity price data was organized into a consistent dataset with one price for each region reported for each delivery day, similar to gas prices. The data covers the 2014 through 2017 time period. However, electricity prices are reported for "High Load Level" periods (16 hours for six days a week) and "Low Load Level" periods (eight hours for six days a week and 24 hours on Sunday & NERC holidays). ln order to have a consistent price definition, a composite price, calculated based on 16 hours of peak and eight hours of o{f-peak prices, is used for Monday through Saturday. The Low Load Level price was used for Sundays since that already reflects the 24 hour price. Missing and duplicate data is handled in a fashion similar to gas prices. Illiquid delivery point prices are filled using liquid hub prices as reference. Mid-C is the rnost liquid market in PACW, so missing prices for COB are filled using the latest available spread bet'ween COB and Mid-C markets. Similarly, Four Comer prices are filled using Palo Verde prices. Development of Price Inde.r: As with gas prices, an electricity price index was developed which accounts for the expected components ofprice movements. The "expected" electncity price incorporates all tkee possible adjustments: seasonal average, monthly shape and weekly shape. For instance, the expected price for January 2,2014 n the Four Corners region was $43- l2lmegawatt hours (MWh). This price incorporates the 2014 winter average price of $39.I4lMWh times the monthly shape factor for January of 102 percent and the weekday index for Thursday of 108 percent. The following chart shows the Four Comers actual and expected electricity prices over the analysis time period. 128 PAqrrCoRP - 2019 IRP PACFTCoR-P - 20l9IRP AppENDtx H - SToctIAsnc PARAMEiI:Rs ure H.8 - Dail1, Electricit1' Prices for F-our Corners,2014-2017 i: E 200 180 160 140 120 100 m 60 N 20 Expected Pri.es lan-14 lul'14 lul-15 Dec-15 lun-15 Dec-16 lun'17 Dec 17 Table H,3 - Uncertain Parameters for Electrici Re ons Regional Load Process There are only two significant differences between the uncertainty analysis for regional loads and natural gas prices. The distribution of daily loads is somewhat better represented by a normal distribution rather than a lognormal distribution, and, similar to electricity prices, loads have a significant expected shape across the week. The chart below shows the distribution of historical Spring 9.U% 0.125 LO.47% 0.434 t5.47% 0.338 10.L3% 0.370 Four Corners Daily Volatility Daily Mean Reversion Rate 29.97o/o 0.463 to.19% o.257 CA-OR Border Daily Volatility Oaily Mean Reversion Rate !3.44% 0.119 26.73% 0.551 27.28% o.277 1o.340/, o.279 Mid-Columbia Daily Volatility Daily Mean Reversion Rate 76.sso/o 0.140 7.46% o.ztL t4.@% 0.220 9.83% 0.415 Palo Verde Daily Volatility Oaily Mean Reversion Rate 129 Dec.14 Electricity Price Uncertainty Parameters Uncertainty parameters are calculated for each electric region, similar to the process for gas prices. The electricity price parameters derived through this process are reported in the table below. Winter Su mmer Fall 47.460/0 0.551 9.22% 0.110 P^crFrCoRP - 2019 IRP APPENDXII STOCHASTIC PARAME,I IRS load outcomes for the Portland area as well as normal and lognormal distribution functions representing load possibilities. Both distributions do a reasonablejob ofrepresenting the spread of possible load outcomes, but the tail ofthe lognormal distribution implies the possibility ofhigher loads than is supported by the historical data. ure H.9 - Proba Distribution for Portland Load, 2014-2O17 Devekryment of Load Index: As with elecricity prices, a load index was developed which accounts for the expected components of load movements, incorporating all three possible adjustments. For instance, the expected load for January 2, 2014 in Portland was 324 megawatts (MW). This load incorporates the 2014 winter average load of 305 lvIW times the monthly shape factor for January of 103 percent and the weekday index for Thursday also of 103 percent. The following chart shows the Portland actual and expected loads over the analysis time period. 2,W6 2.m96 1.$% 1.m86 0.50% 0.m* !!I 150 2m 150 - actu a I D istribution -t08 Normal Distribution 4mzfi 3m Av.r.a. D.lly Lo.d ln Porthnd (Mwl -Norrnat oistribution 130 PACTFTCoRP -20l9IRP AppLNDrx H - STC)CHASTTC PARAMETTRS ure H.l0 - D Ave Load for Portland, 2014-2017 Load Llnce rtain ty Pa rameters : Uncertainty parameters are calculated for each load region, similar to the process for gas and electricity prices. Since loads are modeled as normally, rather than log-normally distributed, deviations are simply calculated as the difference between the load index and the previous day's index. The uncertainty parameters for regional loads derived through this process are reported in the table below. 450 Actual toads Expected Loads lan'15 ,u1.15 Jan-16 Dec-17Jul-14 iul-16 Dec-16 iul-17 400 300 200 350 250 150 Jan-14 l3l 33 a g : o California Daily Volatility Daily Mean Reversion Rate 4.7% 0.268 4.2% 0.218 4.9% 0.311 Daily Volatility Daily Mean Reversion Rate ldaho 3.5% 0.153 6s% 0.204 5.7% 0.095 4.2% 0.218 Portland Daily Volatility Daily Mean Reversion Rate 3s% 0.777 3.3% 0.247 5.O% 0.280 3s% 0.242 Oregon Other Daily Volatility Daily Mean Reversion Rate 4.2% 0.182 3.4% 0.379 4.2% 0.195 4.2% 0.253 Daily Volatility Daily Mean Reversion Rate Utah 2.1% 0.363 2.8% 0.595 4.5% 0.213 3.5% 0.249 Washington Daily Volatility Daily Mean Reversion Rate 5.3% 0.181 3.7% 0.341 s.0% 0.157 4.3% 0.203 wyoming Daily Volatility Daily Mean Reversion Rate 1,.6% 0.235 !.7% 0.267 1,.6% 0.273 L8% 0.254 PACTFTCoRP - 20l9 lR?Appl:NDrx H - SrocHASrr( PA.RAMETERS Table H.4 - Uncertain Parameters for Load s Hydro Generation Process There are two differences between the uncertainty analysis for hydro generation and natural gas prices. Hydro generation varies on a slower time frame than other variables analyzed. As such, average hydro generation is calculated and analyzed on a weekly, rather than daily, basis. Generation is calculated as the average hourly generation across the 168 hours in a week. The hydro analysis covers the 2013 through 2017 time period. Development of Hydro Index: A hydro generation index was developed which accounts for the expected components of hydro movements, incorporating seasonal and monthly adjustments. For instance, the expected hydro generation for the week of January l, 2013 through January 7, 2013 in the Westem Region was 388 MW. This generation incorporates the 2013 winter average generation of 422 MW times the monthly shape factor for January of 92 percent. The following chart shows the western hydro actual and expected generation over the analysis time period. 132 Winter Spring Summer Fall 3.8% 0.185 PACTFTCoRP - 20l9IRP APPENDIX H - STocHASnc PARAMITrRS F re H.ll - Wee Avera H ro Generation in the West, 2Ol3-2O17 l,@ 900 800 7tx) 5at) rx) 400 Ib 200 t@ 3 =,9! .} t ri Hytlro Generation Llncertainty Parameters : Uncertainty parameters are calculated for each hydro region, similar to the process for gas and electricity prices. The uncertainty parameters for hydro generation derived through this process are reported in the table below. Table H.5 - Uncertain Parameters for H dro Generation Short-term Correlation Estimation Correlation is a measure ofhow much the random component ofvariables tend to move together. After the uncertainty analysis has been performed, the process for estimating correlations is relatively straight-forward. Step I - Calculate Residual Errors Calculate the residual errors of the regression analysis for all of the variables. The residual error represents the random portion ofthe deviation not explained by mean reversion. It is calculated for each time period as the difference between the actual value and the value predicted by the linear regression equation: Error = ActuaL Devtation - (Slope * Preuious Deuiatton 1- Intercept) All ofthe residual errors are compiled by delivery date. 2t.t5%16.l7o/o 16.78o/o 30.08%Weekly Volatility 0.63 0.50 l.5l 0.86Weekly Mean Reversion Rate t33 Winter Spring Summer Fall Correlatton(X ,Y) -Xi[(r, - *o,n.) * (yi - yo,,.)l DT(r, - *",n)' *L!(yi - y""s.)' There are a few things to note about the correlation calculations. First, correlation data must always be organized so that the same time period is being compared for both variables. For instance, weekly hydro deviations cannot be compared to daily gas price deviations. Thus, a daily regression analysis was performed for the hydro variables. Also, note that what is being correlated are the residual errors ofthe regression - only the uncenain portion of the variable movements. Variables may exhibit similar expected shapes - both loads and electricity prices are higher during the week than on the weekend. This coincidence is captured in the expected weekly shapes input into the planning model. The correlation calculated here captures the extent to which the shocks experienced by two different variables tend to have similar direction and magnitude. The resulting short-term correlations by season are reported below. Table H.6 - Short-term Winter Correlations SHORT-TEiM WINTER CORREI.ATIONS(-o suMAs 4c coB Mid-c Pv KO SU CA lD Portl.nd OR Other UT WA WY 4C coB Mid-c D OR Deviation events that impact one part ofPacifiCorp's system do not necessarily affect other pans ofthe system, due to its geographic diversity and transmission constraints. The correlation between these different deviations can be low if the deviations are caused by different drivers. An example flom the winter season is the -l I percent correlation between the Southeast Idaho load area, which is driven by weather events in PacifiCorp's PACE balancing area, and Hy&o, which is predominantly driven by weather events in PacifiCorp's PACW balancing area, the unit commitment stack and unplanned unit outages. t34 66% 61% 39( 5% lff/6 a% 14% t7x 20% 17% t3% 14% 24% 22% 7Vr 72% 5% t7% 77% a% 22% 72% 3% 14% 2096 13% 1096 24% 1096 5% 6%2% 396 PA( rrCoRP - 2019 IRP APPENDx II. ST(THASTIC PARAMITIRS Step 2 - Calculate Correlations Correlate the residual errors ofeach pair ofvariables: looga 8996 I 6i% 15% fi% __!9!____1998_1 57% 4cF/o 42ro 63r/. 57% 10094 5a% 'Vh15v" 40% 58% 10096 94%)a% 42% 57% 94% 1C[96 66% 6r% 83% 61* 5996 10% 15% 27% 27% 20% 29% 12% 14% 19% 30% 37% 2t% 43% 1996 74% 2!% 36% 4St 25% 46% 24% lG/6 10% 24% 23% t7% 29% t2% 83% 61% s9% 10095 6% 3% 6% 2% 3% -4% -11% -4% 3%{x 15% -2% 15% 19% 21% 109( 10% 14% 32 27% 30% 36% 24% 27% 37% 40x 23% 72% 19% 74% t2% 20,4 21% 2596 t7* lm 231 29% 43% 46% 29% 10096 7% 7vo lVA 2% &7%13 -r% 4% 7% 24% s% 8% 6% 8% 1% 73% 2094 10,t 1% 13% 1% 7% 2% a6 7% 5% 7% l0/" 2% 4% 3% -5% a% 3% 3%2%-&M PA( rr,rCoRP 20l9 lRP App[NDIx H - STocHAsrlc rARAMEIERS Table H.7 - Short-term Spring Correlations SHORT-TERM SPRING CORREIANONS K-O SUMAS 4C CO8 Mid-C PV CA lD Portland OR Other UT WA WY K co Mid-c c I OR Othe Similarly, the spring season shows a very low correlation of nine percent between the Northem Califomia and Wyoming loads, which are &iven by different local weather deviations and different customer types. Wyoming loads are mostly driven by large industrial customers, whose loads are relatively flat across the year. Table H.E - Short-term Summer Correlations SHORT-TERM SUMMER CORRELATIONS K.O SUMAS 4C COB Mid.C PV CA lD Ponland OR Other UI K-O SUMAS 4C co8 Mid-c CA ID OR Other UT ln the summer season, zero correlation has been observed between the deviations of Kem-Opal gas prices and Palo Verde power prices. Palo Verde prices are driven by a resource mix of southwest nuclear operations and gas unit dispatch based off SoCal gas prices. The operations of gas storage facilities and physical planned and unplanned maintenance of Kem-Opal and SoCal pipelines are independent of each other. 5% 0% 2% 0% s96 1gr l% o% 5% -396 -3% 8% 4% -4% -1% -5% 3% @6 -4% 5% -7%-t% tv" -49t 7% 4% s% 135 70/196 55%2A% 6% 10096 34t6 *fa ro% 8% a4% 1@96 86* 33% 13% 62% 39% 31% 7% 1% 35% a6% 10[,6 096 13% 13% 3% 1% -3% 1% 15% 7 24% 26% 17% 6% 21% 21% 14% t3% 8% 11% 24% 12% 31% 29% 24% a6 3% 7% -5% 15% 896 11% 7416 rv 431. 22.. 31! 100 1% 3% l1* l39C 15% 13% 209 6% 100 639 6% 2t% 2tx 74% 55 331 12% 31% 29% 24% 3% . 096 w6 -3% -1% -t7x t1% lM -11% 18% 5% A% 1% O% 5% S% 10% r% 7Un6 27% 2996 5296 7* 85% 1m% 51* 21% 15% 279{ 12* 11% L6% 16% 16% t7% 32% 48% 1A% t7% 28% 45% 25% 219i Wr 15X 25% 18% 2A% 38% 20% lm% 45% w. -4% 1% 4% s% -3% 5X 1696 -1Y 9% -11% 1396 8% 4% 4% -4% 1 32% 4896 17% 28% 45% 21% 15% 22% r1% 169r 16% 21% 996 15% 18% 28% 38% 2@5 PA( rrCoRP - 2019 IRP A?PENDH H - ST('IrAsrrc PARAMETERS Table H.9 - Short-term Fall Correlations SHORT.TERM FALI. CORRETATIONS K-O SUMAS 4C CO8 Mid-C PV CA lO Pordand OR Other UT WA wY K-O SU 4C co8 Mid-c to OR In the fall, a very low correlation ofthree percent has been observed between Mid-C market price deviations and Wyoming load deviations. Market deviations are due to deviations in northwest weather pattems and resource mix while Wyoming loads are mostly dictated by planned or unplanned outages of industrial customer class. 6%7% 10%22% 15% 28% lt% 23% 1 33% 11% 24% 17X 32% 14% 15% 72% 13% 109{ l3% 13% 7% 15% 6% 1196 19% 11% 17 7 2a% r0% 25% z1% 74% 32% 22% 2% 4% 136 t4% \5% 10v" t3./" 100% 36%53% 63% 44% 100/ 22* 7A16 1fl)9{ 44% 12% 13% t3% 1% 35X 2296 53% 1009( 78v. 63% 21% 19% 22% 9% 416 3% -5% 23% 24% 22% 16% 21% 24* 19% 20% 2@6 1696 n6 1096 2% 896 9% 19% 9% l0ts 9% 9% 1096 9%2% 8% vr24% 22% 16% 16% 18% T* 24% 19X 2M19}6 22% 94 396 7X -59( 1916 1o.t 23% 2@6 2L% 2t% 4X 47 19% 1tn 7ari 45% 13,6 -4% -2% -4% 1% -5% -12% t7% 7% -7% 9* 4% l7%10096 PA( lrrCoRP 20l9lRP App[NDrx I - PLAr\NrNc [{EsERVE MARCTN S n]Dy AppExolx I - PIaNNTNG REssRve MeRcm Sruoy The planning reserve margin (PRM), measured as a percentage ofcoincident system peak load, is a parameter used in resource planning to ensue there are adequate resources to meet forecasted load over time. PacifiCorp selects a PRM for use in its resource planning by studying the relationship beween cost and reliability among eight different PRM levels, accounting for variability and uncertainty in load and generation resources.l Costs include capital and run-rate fixed costs for new resources required to achieve eight different PRM levels, ranging from I I to l8 percent, along with system production costs (fuel and non-fuel variable operating costs, contract costs, and market purchases). In analyzing reliability, PacifiCorp performed a stochastic loss of load study using the Planning and Risk (PaR) production cost simulation model to calculate the following reliability metrics for each PRM level: Expected Unserved Energy (EUE): Measured in gigawatt-hours (GWh), EUE reports the expected (mean) amount ofload that exceeds available resources over the course ofa given year. EUE measures the magnih:de of reliability events, but does not measure frequency or duration. Loss ofLoad Hours (LOLH): LOLH is a count ofthe expected (mean) number ofhours in which load exceeds available resources over the course of a given year. A LOLH of 2.4 hours per year equates to one day in l0 years, a common reliability target in the industry. LOLH measures the duration of reliability events, but does not measure frequency or magnitude. Loss ofLoad Events (LOLE): LOLE is a count of the expected (mean) number ofreliability events over the course of a given year. An LOLE of 0.1 events per year equates to one event in l0 years, a common reliability target in the industry. LOLE measures the frequency ofreliability events, but does not measure magnitude or duration. Objective The purpose of the PRM is to ensure that Integmted Resource Plan (IRP) portfolios a) meet customer load b) while maintaining operating reserves, c) meeting a one day in ten year reliability target, d) at a low reasonable cost. The 2019 IRP PRM selection is made by analyzing: rCosts and reliability metrics are calculated for cight difibrent PRM levels, ranging tiom ll to 18 perc!'nt. Comparative analysis among cach PRM is performed for sevcn dill'erent PRM levels by comparing the cost and reliability results from PRM levels ranging between I I and l8 perccnt to those liorr the l0 percent PRM. t37 Introduction PacifiCorp's loss of load study results reflect its participation in the Northwest Power Pool (NWPP) reserve sharing agreement. This agreement allows a participant to receive energy fiom other participants within the first hour ofa contingency event, defined as an event when there is an unexpected failure or outage of a system component, such as a generator, transmission line, circuit breaker, switch, or other electrical element. PacifiCorp's participation in the NWPP reserve sharing agreement improves reliability at a given PRM level. Upon evaluating the relationship between cost and reliability in its PRM srudy, PacifiCorp will continue to use a l3 percent target PRM in its resource planning. PACIIC0RP - 2019 IRP AppEl"Drx I - Pr.A.NNNG R-ESERVE MARGTN S ruDy Relationships between reliability modeling and production cost modeling results PRM cases range from I I to l8 percent in the target year (2030) Bookend cases will be run for years 2O22 and 2O36 Figure I. I shows the workflow used in PacifiCorp's PRM study. The four basic modeling steps in the workflow include: (l) using the System Optimizer (SO) model, produce resource portlolios among seven different PRM levels ranging between l1 and 18 percent; (2) using PaR, produce reliability metrics for each resource portfolio; (3) using PaR, produce system stochastic variable production costs with full market access for each resource portfolio: (4) produce the marginal cost of reliability using outcomes ofdifferent PRM levels, (5) select PRM level. Figure I.l - Workflow for Planning Reserve Margin Study CapihlCorts Development of Resource Portfolios The SO model is used to produce resource portfolios assuming PRM levels ranging between I I and l8 percent. The SO model optimrzes expansion resources over a 2O-year planning horizon to meet peak load inclusive of the PRM applicable to each case. Consistent with the 2017IRP. as the PRM level increases additional resources are added to the portfolio. Resource options used in this step ofthe workflow include demand-side management (DSM), gas-fired combined cycle combustion turbines (CCCT), gas-fired simple cycle combustion turbines (SCCT), renewable resources and front office transactions (FOTs). R.li.bility (EUE. LOLE. LOrH) Exprrtrd Cort compare costs and rel i abillty out.omes of dlff.rcntPRMs n rriotc?{* ofnehr&t Portfolio Stocha5tic Sim ulations with full market access (PaR Model) New Resources Portfolio Stochastic Reliability simulations fPaR [/odel) Fange of PfiM levels Ease Porffollo of Exls6ng Ftsour(Et Seled PRM LeYel 138 The target year of 2030 is selected based on a preliminary assessment aligned with significant assumed retirements; bookend years were developed as a check on this assumption. Methodolocy System Optim izer Portfolios (one per Reserve Margin level) Updated Assumptions Front OIfice Transactions (FOT) FOTs are considered as a resource expansion option in this phase ofthe workflow. FOTs are proxy resources used in the IRP portfolio development process that represent firm forward short-term market purchases for summer and winter on-peak delivery, which coincides with the time of year and time ofday in which PacifiCorp observes its coincident system peak load. These proxy resources are a reasonable representation offirm market purchases when performing comparative analysis of different resource portfolios to arrive at a preferred portfolio in the IRP. In the 2019 IRP, PaR market purchases are restricted to FOT limits in all months of the PRM models. This change makes PaR reliability measures consistent with market reliance assumptions, and allows the impact of market purchase reliance to be assessed in reliability analysis. Planning Capacity Factor (PCF) The planning capacity factor for DSM, solar and natural gas resources has been updated for the 2019 IRP Planning Reserve Margin Study, based on updated analysis and the latest information. Demand Resoonse (Class I DSM) Demand Response contracts define limits on the number of intemrptible hours per day and hours per year reduce capacity contribution. In order to represent these limitations accurately, the capacity factor (CF) approximation method has been applied to each demand response program. PCF is consequently reduced by a weighted average of I I percent, ranging from -2 to -22 percent by program. Also, in alignment witlr actual practice, summer demand response availability has been expanded to June through September and winter, and winter demand response has been expanded to October through December. Enersv Efficiencv (Class 2 DSM) Similar to demand response, energy efficiency has limitations on hours per day and hours per year, restricting capacity contribution. Taking these limitations into account reduces energy efficiency PCF by a weighted average of 15 percent, ranging from -24 to +13 percent by bundle. Solar In response to rapid increases in solar penetration, PacifiCorp assessed a 2030 solar resource PCF, measured relative to a case with no solar. East solar has an overall effective capacity contribution of 29.3 percent, down from 37.9 percent for fixed and 59.7 percent for tracking. West solar has an 139 PA('rrrCoRP - 2019 IRP APPENDIX I _ PI-ANNTNG RESERVE I\4\RGIN SI.UDY The front office transaction reserve credit, previously calculated at six percent of load, has been lowered to three percent, reflecting the thee percent of load/three percent of generation requirement which is new this IRP cycle. Market Purchases The SO model planning limit for FOT selection as a capacity resource in the 2019 IRP is 1,425 megawatt (MW) in both summer and winter. In past IRPs, PaR has allowed for market balancing purchases up to transmission limits for the purpose ofvaluing portfolios in all months ofthe year. As a consequence, in the 2017 IRP, all PRM levels met PaR loss of load hour (LOLH) requirements, relying on market purchases. P^ rrCoRP - 2019IRP APPENDIX I - PLANNTNG RHSERVE lvfaRcrN sTUDY Upfront capital and run-rate fixed costs from each portfolio are recorded and used later in the workllow where the relationship between cost and reliability is analyzed. Resources from each ponfolio are used in the subsequent workflow steps where reliability metrics and production costs are produced in PaR. Development of Reliability Metrics The PaR model is used to produce reliability metrics for each ofthe resowce portfolios developed assuming PRM levels ranging between I I and l8 percent. PaR is a production cost simulation model, configured to represent PacifiCorp's integrated system that uses Monte Carlo random sampling of stochastic variables to produce a distribution of system operation. For this step in the workflow, reliability metrics are produced from a 50O-iteration PaR simulation with Monte Carlo draws of stochastic variables that affect system reliability-load, hydro generation, and thermal unit outages. As discussed above, system balancing hourly purchases are enabled to capture the contribution offirm market purchases to system reliability. The PaR reliability studies are used to report instances where load exceeds available resources, including system balancing hourly purchases. Reported EUE measures the stochastic mean volume of instances where load exceeds available resources, and is measured in GWh. EUE measures the magnitude of reliability events. Reported LOLH is a count ofthe stochastic mean hours in which load exceeds available resources. LOLH measures the duration of reliability events. Reported LOLE is a count of the stochastic mean events in which load exceeds available resources. LOLE is a measure of the frequency of reliability events. Each ofthe reliability metrics described above is adjusted to account for PacifiCorp's participation in the NWPP reserve sharing agreement, which allows a participant to receive energy from other participants within the first hour ofa contingency event. PacifiCorp accounts for the NW?P reserve sharing agreement by assuming the first hour ofany event is covered and removed in the tabulation of EUE, LOLH and LOLE measures. NWPP pa(icipation reduces each of these measures by roughly half. For PaR, the contribution of firm market purchases are removed and instead include system balancing hourly purchases that cover the firm market purchases, limited by transmission and market depth limits, for the reliability metrics. Development of System Variable Production (losts In addition to using PaR to develop reliability metrics, PaR is also used to produce system variable production operating costs for each of the resource portfolios developed assuming PRM levels ranging between I I and 18 percent. For PaR's system variable production cost runs, its Monte Carlo sampling of stochastic variables is expanded to include natural gas and wholesale market prices in addition to load, hydro generation, and thermal unit outages. At this step, the stochastic treatment ofmarket prices is key given its influence on the economic dispatch ofsystem resources, 140 overall effective capacity contribution of 35.6 percent, down from 53.9 percent for fixed and 64.8 percent for tracking. Natural Gas Past IRPs have relied on monthly average temperature impacts. The 2019 IRP uses a summer peak temperature to improve PCF consistency with peak capacity needs. PACTTTCoRP - 20t9 IRP APPENDD( I _ PLANNTNG RLSERVE MARGTN STt]DY cost of system balancing purchases, and revenues from system balancing sales. In this step, full market access is included for the simulation. The stochastic mean ofsystem variable costs is added to the upfront capital and run-rate fixed costs from each portfolio so that total portfolio costs are captured for each PRM level. Selection of the Planning Reserve Margin Using the incremental cost of reliability analysis, guided by additional measures detailed below, the PRM level is selected for use in the 2019 IRP. Resource Portfolios In the summer, each I percent PRM increases system capacity by roughly l00MW. At each odd- numbered PRM increase, the model adds an additional single-cycle gas resource, partially offset by a reduction in FOTs and intemrptible load selections. This trade-off occurs because new gas resources are added in blocks indicative of a typical plant size (i.e. the model cannot add a two MW SCCT plant), and thus the additions in each separate resource category do not move uniformly with an increase in the PRM. Table I.l - Summer E nsion Resource Additions PRNI Table I.2 shows new resources added to the portfolio for the winter at PRM levels ranging between I I and l8 percent. Winter additions are led by summer additions where summer DSM selection may contribute to winter depending on the attributes of bundle selections; while winter additions follow a general trend, variations are observed at the l6 and l8 percent PRM levels in particular. 14t 824 82t 240 2t9 I,313 1,416 1,2$ t,287 3l 3l 3,672 3,'t75 ti30 844 854 244 2t8 241 I ,313 1,416 1,313 1,459 I ,468 1,639 3l 3l 3l 3,877 3,977 4,07lt {t70 853 891 27t 273 323 t,3t2 1,315 1,313 t.694 I,810 I,865 3l 3l J1 4,177 4,282 4,423 Results Table I.l shows new resources added to the portfolio for the summer at PRM levels ranging between I I and l8 percent. Each portfolio includes FOTs ranging from 1,312 I\iIW to 1,416 MW. In the summer, FOTs don't vary much as all PRMs are relying on most of the FOT limit during the peak. Natural gas resource additions escalate from 1,264 MW ofresource to I ,865 MW across the PRM studies as the margin increases. DSM resource additions range between 218 MW and 89r MW. Caoacity at Summer Peak (MW) DSM PRM (Yol Demand Resoonse Enerry EIficiencv FOT Natural Gas Geo- ThermaU Other Total ll 12 13 t4 l5 l6 t7 l8 PACIFTCoRP - 20l9 IRP Table I.2 - Winter Ex nsion Resource Additions b PRM Table I.3 - Simulated Reliabili Metrics b PRNI Capacity at Winter Peak (MW) DSM PRM (%\ Enerry Efficiency Demand Response FOT Nat. Gas Geo- ThermaU Other Totnl 729 727 0 0 306 314 I,458 l,484 3l 3l 2,524 2,556 736 749 759 0 0 0 321 328 336 1,682 t,692 r,889 3t 3l 3l 2,769 2.801 3,0t5 I I I I I I I I I 2 3 4 5 6 1 8 775 759 796 0 0 0 0 350 0 I,915 2,087 2.1 l3 3l 3t 3l 2,721 \'r)1 2,940 Before NWPP Adjustment After NWPP Adjustment Year PRM (%) Simulated Energy Not Served (G!Yh) LOLH (<2.4 target year) (Hour) Loss of Load Episodes EUE (Glvh) LOLH (Hour) Modeled Loss of Load Episodes 2OT9 IRP ll t2 l3 t4 l5 l6 t7 l8 2.46 3.7 5 1.97 r.64 0.98 0.87 0.54 0.41 t.t2 1.45 0.90 o.79 o.44 0.38 o.27 0.19 327 637 279 196 106 88 35 56 0.54 0.78 0.45 0.37 0.23 0.18 0.09 0.08 APPENDIX I _ PLANNINC RISFRVF: MARGIN S-ILIDY In aggegate, the summer and winter additions result in a smooth progression of reliability measures (e.g., loss ofload hours, loss ofload events, and incremental cost ofreliability) reported in the next section of this appendix. Reliability Metrics Table I.3 shows EUE, LOLH, and LOLE reliability results before and after adjusting these reliability metrics for PacifiCorp's pa(icipation in the NWPP reserve sharing agreement. Each of the reliabitity metrics generally improve as the PRM increases and after accounting for benefits associated with PacifiCorp's participation in the NWPP reserve sharing agreement. After accounting for its participation in the NWPP reserve sharing agreement, all PRM levels meet a one day in ten year planning criteria (LOLH at or below 2.4), and PRM levels ofbetween l7 and l8 percent meet a one event in ten year planning criteria (LOLE at or below 0.1). 2030 602 1,038 514 377 193 157 7t 107 1.34 2.30 t.o7 0.85 0.54 o.49 0.27 0.21 t42 P^( n,lcoR? - 20l9lRP APPENDLX I - Pr-ANNrNc IiESERVE MARGIN STtrDy The reliability metrics do not monotonically improve with each incremental increase in the PRM. This is influenced by the physical location ofnew resources within PacifiCorp's system at varying PRM levels and the ability of these resowces to serve load in all load pockets when Monte Carlo sampling is applied to load, hydro generation, and thermal unit outages. The l2 percent reports higher EUE, but is able to meet the l2 percent PRM with an efficiency that keeps the incremental cost ofEUE in line with the rest ofthe PRM levels (refer to Table I.5 under System Costs, below). Absent the NWPP adjustment, the PRM l3 percent is the cross over point where the LOLH is below the 2.4 hour per year limit. Considering that the reliability metrics are measuring very small magnitudes ofchange among the different PRM levels, the PaR outputs are fit to a logarithmic function to report the overall trend in reliability improvements as the PRM level increases. Table I.4 shows the fiued EUE LOLH, and LOLE results. Figure I.2, Figure I.3 and Figure I.4 show a plot of the fitted trend for EUE, LOLH, and LOLE, respectively, after accounting for PacifiCorp's participation in the NWPP reserve sharing agreement. Table I.4 - Fitted Relia )Ietrics PRNI 504 353 265 202 154 l14 8l 52 t.92 1.38 1.06 0.84 0.66 0.52 0.40 0.29 0.78 0.58 0.46 0.37 0.31 0.25 0.2t 0.17 878 619 467 360 2',t6 208 l5l l0l 3.36 2.43 1.88 1.50 1.20 0.95 o.14 0.56 1.44 1.05 0.82 0.66 0.53 0.43 0.35 0.27 143 After NWPP AdjustmentBefore NWPP Adjustment Modeled Loss of Load Episodes EUE (GWh) LOLH (Hour) LOLH (4.4 target year) (Hour) Modeled Loss ofLoad Episodes ETIE (GWh) PRM (%) l1 t2 l3 t4 l5 l6 l7 l8 700 600 500 400 -r00 200 100 0 t E ll t2 l3 16 t7 +ELIE -LI(EUE) 18 v : -217.-3ln(x) + 503.63 R': 0.5826 14 15 PR\r (%) I)^( rFrC(]Rr, - 2(ll9 [RIr AppFNDrx I - Pr-,^NT.llNC RFSFRVF MAR(irN STr ]Dy F re I.2 - Ex ed and Fitted Relation of EUE to PRM Figure I.3 - Expected and Fitted Relationship of LOLH to PRll 2.5 2.0 -] R! = 0.6326 I.5 .0 0.5 0.0 ll l3 l4 l5 l6 t1 Itr PRNI (%) +LOLII - ln(t.OLH) t2 t44 PACTFTCORP 20l9lRP AppENDx I - Pr.AMirNG R-ESERVE MARGIN St uDy 0.m 0.80 0.70 0.60 0.50 0.,!0 0.30 0.20 0.10 0.00 1' : -0.2961n(x) + 0.7318z\ I a f-l ,.1 rJ ll l6 t7 l8l3t2 +LOLE -ln(LOLE) t4 15 PRM (o/o) I.4 - Simulated Relations of Loss of Load sode to PRNI System Costs For the 2020 reference year, Table I.5 shows the stochastic mean of system variable production costs and the upfront capital and run-rate fixed costs, including the cost of new DSM resources, for each portfolio developed at PRM levels ranging between I I and 18 percent. The fixed costs associated with these new resource additions drive total costs higher as PRM levels increase. DSM run-rate costs vary depending on resource additions for demand response and new resources where gas was added. Table I.5 -tem Var U front Ca ta and Run-rate Fixed Costs PRM l l.368 l l.383 818 802 120 l3l 2.823 2,823 3,398 3,472 18,527 18,61 I I1,3s2 l l.302 I I ,313 833 855 886 122 130 t20 2,823 2.823 2,823 3.540 3,609 3,684 18,670 18,719 18,825 18,887 18,939 19,o23 936 863 983 2,82f 2,823 2,823 lr,l34 I 1,289 11.149 132 134 137 3,862 3.830 3,931 145 ---n: = 0.'1299 Energr Efficiency ($m) Demand Response ($m) Existing Resource Fixed Costs ($m) PRM (o/ol System Production Costs ($m) New Resource tr'ixed Cost ($m)Total ($m) ll t2 13 t4 5 6 7 8 Incremental Cost of Reliabilitv Figure I.5 depicts the incremental cost of reliability, stated as the nominal levelized cost ofEUE relative to I I percent PRM, at PRM levels ranging between l2 and 18 percent. The incremental cost ofreliability rises intuitively as PRM levels increase, and illustrates a significant step-change noted when the PRM hits 15 percent and onward. Figure I.5 - Incremental Cost of Reliability by PRM d s !^ d,ulda (,, iz 38m t7m 3@ $sm 34.@ t3m ,5 12% PRI!{ 139;PRII l4'.,o PRM I5%PR.V I67.PRM I7%PRV I8%PRM PacifiCorp will continue to use a l3 percent target PRM in its resource planning after evaluating the relationship between cost and reliability in the PRM study. A PRM below l3 percent would not sufficiently cover the need to carry short-term operating reserve needs (contingency and regulating margin) and longer-term uncertainties such as extended outages and changes in customer load.2 A PRM above 15 percent improves reliability above a one event in ten year planning level, although with a 300 to 700 percent increase in the incremental cost per megawatt- hour of reduced EUE when compared to a l3 percent PRM. With these considerations, the selected 13 percent PRM level ensures PacifiCorp can reliably meet customer loads while maintaining operating reserves, with a planning criteria that meets one day in l0 year planning targets, at the lowest reasonable cost- 2 PacifiCorp musl hold approximately six percent oiils rcvrurces in rcserve to meet contingency reserve requirements aod an estimated additional 4.5 percent to 5.5 percent of its resources in resewe, depending upon syst€m condilions at the timc ofpcak load, as regulating margin. This sums to 10.5 percent to I1.5 percent ofoperating reserves betbre cvcn considering longer-term uncerlainties such as extended outages (transmission or generation) and customer load growth. 146 P^( rrrCoRP - 2019 [RP APPENDD( I - Pr-ANNTNG R-ESERVE MARGTN sTrIDy Conclusion AppsNorx J - WpsrERN RssouRCE Aoequacv EvaluarroN The Public Service Commission of Utah, in its 2008 Integrated Resource Plan (lRP) Order, directed PacifiCorp to conduct two analyses pertaining to the company's ability to support reliance on market purchases: Additionally, we direct the (lolnpavly to include an analysis of the adequacy of the weslern power market to support the volumes ofpurchases on which the company expects to rely. We concur wirh the Ofiice fuf Consumer Servicesl , the IYECC is a reasonable source for this evaluation. ll/e elirect the Company to identifl whether customers or shareholders will be expected to bear the risks associated with its reliance on the wholesale market. l'inally, we direct the Company b discuss methods to augment the Company's stochastic analysis oJ'this issue in an IRP public input meetingfor inclusion in the next IRP or IRP upiate.) In the past, PacifiCorp has fulfilled this requirement by evaluating the Westem Electriciry Coordinating Council (WECC) Power Supply Assessment (PSA) to glean trends and conclusions from the supporting analysis. While an updated PSA has not been published in time for this IRP, there is a published update available for the North American Electric Reliability Corporation (NERC) Long Term Reliability Assessment (LTRA). Past PSA reports were based on data publicly available in the NERC LTRA, and the latest available LTRA report2 is used in lieu of the WECC PSA in this appendix. This evaluation, along with a discussion on risk allocation associated with reliance on market purchases, is provided below. As part of this evaluation, PacifCorp also reviewed the status of resource adequacy assessments prepared for the Pacific Northwest by the Pacific Northwest Resource Adequacy Forum. The NERC LTRA, issued December 20,2018, was developed based on data collected from seven regional entities, including WECC. NERC staff independently assesses collected data to develop the LTRA for the North American Bulk-Power System. The NERC LTRA assessment identifies trends and risks over a l0-year (2019-2028) study period. The 2018 LTRA concludes that the WECC, inclusive of four U.S. and two Canadian subregions, are expected to have sufficient generation capacity to exceed reserve requirements during the assessment period. I Public Servicc Commission ofUtah, PacifiCorp 2008 Integrated Resource Plan, Repofl and Order, I)o(ket No, 09- 2035-01. p.30. 2 North American lllectric Reliability Corporation 2018 [,ong Term Reliability Assessmetrt, www.nerc,com/pa,/RAlA./ra./PageVdefault-aspx 147 PACTFTCoRP-20l9lRP AppENDrx J - WESTERN R-EsouRCE ADEeUACY EVALUATToN NERC 2018 Lons Term Reliabilitv Assessment PACTHCoRP -20l9lRP Appr-NDrx.l WlsrlRN RrsoLRCI ADleLrA( y EVALLT?\I|oN Resources The NERC LTRA organizes resources into two broad categories its l0 year WECC region reliability assessment: Anticipated Resources: Existing generating capacity able to serve peak hour load with firm transmission) Capacity that is either under construction or has received approved planning requirements Firm net capacity transfers with firm contracts Less confirmed retirementsa Prospective Resourceso Existing capacity that may be available to serv'e peak hour load, but lacks certainty associated with firm transmission, peak availability, etc.. Capacity additions that have been requested but not received approval o Nonfirm net capacity transfers and transfers without firm contracts, but assessed to have a high probability of furure implementationo Less unconfirmed retirements Planninq Reserve Marsin The LTRA defines "planning reserve margin" as Resources less Demand, divided by Demand, shown as a percentile, Resources - Demand o/,oDenautl Resources in this calculation are reduced by expected operating limits due to fuel availability, transmission and environmental limitations. Comparing the anticipated resonrce-based reserve margin to the reference planning margin yields one ofthree risk determinations: . Adequate: Anticipated Reserve Margin exceeds the Reference Margin Levelo Marginal: Anticipated Reserve Margin exceeds the Reference Margin Level but there are low expectations in meeting all forecast parameters; altemately, Anticipated Reserve Margin is below the Reference Margin Level but sufficient Tier 2 resources are projected to cover the shortall-. Inadequate: Anticipated Reserve Margin is significantly less than Reference Margin Level and load intemrption is likety. 148 t l Wf,CC Subregions Table J.l presents the WECC subregions used for the NERC LTRA. In the data that follows, the two subregions in Canada are not considered. PACTFTCoRP - 20t9 IRP AppENDrx J - WESTERN RrsouRcf ADEeUACY [.]vAt.t,ATroN Table J.l - WECC Sub n Desc ons LTRA WECC Assessment Table J.2 through J.4 represent the three types ofreserve margins relevant to the WECC planning reserve margin calculation. In each table, the figures do not include WECC subregions outside of the United States. Table J.2 - NERC LTRA An Reserve Table J.3 - NERC LTRA ve Reserve Table J.4 - NERC LTRA Reference Reserve Mar n United StatesCAMXCalifornia to Mexico NWPP Northwest Power Pool United States RMRG Rocky Mountain Reserve Group United States Southwest Reserve Sharing Group United States SummerSRSG CanadaABAlberta Winter CanadaBCBritish Columbia Winter 27.60/0 25.9o/o 24.6%22.8v.23.8o/o 23.6%23.7%22.0o/oNWPPSuumer23.7v.26 5% 11.7%26.60/"24.9%2t.to/o t9.6%t4.0%R MIi(;Surnmer 23.5%18,0%t6.89i,15.5% 10.8%29.4%21.5v"20.9o/o 18.8%t6.60/.t0.5%SRS(i Summcr 24.0%15.0%t2.oo/o 233%10.6%24.svo 20.'7%20.401t 20.10/oCAMXSun'uncr 24.1"/.?3.6%?tJ.gvo 20.7% NWPP Summcr 21.8%26.1"/o 24.Bvo 22.r%24.0%21.80/.2-l.lr%23.90/o 26.60/0 222% RMRG Sumrnar 33.1o/o 26.6.1t 24.90/o r.5r/r 21.5"/"20.0%t2\.49/o t7.to/o 15.8%14.4o/o SRSG Sunxncr 31.6%32.4%.r0.9%27.59',o 24.1%)2.lott l9.t)tt/o 18.2%l5.l%13.60/0 CA/MX Summcr 32.50/.43.3%4L.P/o 42.9"/.43.90/o 40.2o/o 39.8o/.40.4v.10.2!/.19.70/o t9.1vo 19.10/o t9.50/o t9.6V.19.6%19.5o/o t9.40/"t9.4v"l9.t%t9.t%NWPP Summcr 16 8o/o 16.8%t6.5%t6.4v.l6.lo/o t59vo t5.1vo 15.3%liM It(;Sumnlcr 15.6't t5.40/. 15.10lo l5.lolo 14.9v.t4.6v.t4.50/r l4.3vo 14.20/"t4.ov,t 3.996 1.r.8%SRS(i Summcr t2A9n t2.3v.12.16/0 12.t%t2.o%t2.t.n 12.0%12.0o/o t2.oo/.t2.ty/"CATfi Summer 149 Using this data, a reserve margin position can be calculated to show project shortfalls, both with and without the inclusion ofprospective resource additions. Table J.5 reports the reserve miugin differential based on Anticipated resources, whereas Table J.6 reportes the reserve margin differential assuming Prospetive resources are achieved during the study period. In either table, a Designation Subregion Country Peaking Assumption Summer Summer Summer AnticiD{ted Reserve lll {rsin 2019 2020 2021u.s. wEcc Subreoion Peaking AsslmDtion 2022 2023 2024 2025 2026 2027 2028 ProsDeclive Reserve M{rsitr u.s. wEcc Suhreoion Perking Arsumntion 2019 z02tl ,o2l 2022 2023 2024 2025 2026 2027 2028 Refclence Phnnins Reserve Mmcin 2019 2020 2021 2025 2028u.s. wEcc Subr€oion Pesking AarlrmDtiotr 2022 2023 2024 2026 2027 PA('rrCoRP - 2019 IRP AppF.NDrx J - WEstERN RISOURCE ADF-euACy IVALUATIoN Based on this evaluation, potential shortfalls in Planning Reserve Margin are small and 8-9 years distant. Table J.5 -Plan Reserve Nla in Shortfalls Subre on with Antici ated Resources Table J.6 - Plannin Reserve n Shortfalls Sub wirh P tive Resources Figure J.l graphically illustrates the relative margins for each subregion. Figure J.l - WECC Subregion Reserve Margin Percentage Summary NWPP Reserve Marg,nr RMPG Re5erve Margins lltrflrrll JflHrr,r.r rol9 ro:o ro2l ror ,ol, 202. loI5 lot6 tct, to23 -lrn(ip.r.d -lElp€(dr r--i.hft. SRSG Reserve Marglns 2019 t020 lotl 2022 20ltt lot! 2025 )o)ri l0?7 ?o:a -Ann(p.t.d -P.otocdiv. ---i.hrm(c CAMX Rese.ve Martins ''illilJltJl',, lll Hr rrr, NWPP Summer 7.9%6.2%3.2%4.1%5.1%43%43%'1.2%2.9% RMRC 16.9o/oSrnnmer 9.8%8.4"/,,'t.t%5.t%3.',|vo 2.fo/o t.2%0.1% SRSG Sufirlner t5.7%14.30/o 12.60/o 9.4"/.6.4r;4.5o/o t.ov. CAJ},O(Summcr r0.9%t8..r%t2.2vr I t.6%t2.5%8.6%8A%8.9./"8.7%8.2% NWPP Summcr 8.1%6 40/"5.1%3.3%4.5o/o 4.30/.4.4%4.5o/o 7.4%l. t% RNlRG Summer t6.90/o 9.ao/"{,i.4%7.1%5.4vo 1.5%4.Ooh 2.6%0.40/o SRSC Summer t8.5%t7.30/o t2.gvo 9.80/o16.0%'7.8Vo 5.7%4.2Vi t.2% CAA,fX Sullnrcr 20.2o/o -l t.0%10.0%30.80/o 31.9o/r 2a.tv"27.8v.28.40/o 2R.2%2'7.7v. l -s0 Shortfalls Arsumins Anticiorled Res€rve Mrrpin u.s. wDcc Subrecion Penking AlsumtrlioD 2019 2020 2021 2022 2023 2024 2025 2t26 2127 202E -l.lo/a -2-00/"-330/" positive percentage represents a margin of overage where WECC is expected to have resources above the Reference Margin target; a negative number (highlighted for emphasis) represents a year where a given subregion is at risk offalling below the Referene Margin. Shortf{lls Assumins ProsD€ctiye Re$erl{: Maroin u.s. rvEcc Suhrpoion Pcflking 2019 2[20 2021 2022 2023 2074 2025 2026 2028zl27 4.90/o -0.20/o PACTFTCoRP - 20t9IRP APPENDIX J _ WESTERN RESOURCE ADIQUACY EVALUATIoN Prior Measures PacifiCorp's past assessents, relying on caluclations incorporated into the WECC PSA, have reporting a rolling succession ofpower supply margins, where each year there is a downward trend in reserve margins extending into the future. Figure J.2 presents this trend based on past WECC PSA reports. The rolling nature of each year's outcome tells us that while declining reserve margins are important, in reality the trend line is rarely followed from one year to the next - rather the trend line tends to be pushed forward like a wave, where the future shortage is not allowed to materialize because of cumulative actions taken within the WECC in recognition of future need. re J.2 - WECC Forecasted Power Su Issued 2009 to 2016 ummer Nole: WECC Power Supply Assessmenls include Class I Pltnned Resources Only As in the 2017 IRP, the Pacific Northwest Resource Adequacy Forum (later replaced by the Resource Adequacy Advisory Committee) issued resource adequacy standards in April 2008, which were subsequently adopted by the Northwest Power and Conservation Council. The standard calls for assessments three and five years out, conducted every year, and including only existing resources and planned resources that are already sited and licensed. The Resource Adequacy Advisory Committee issued a Pacific Northwest Power Supply Adequacy Assessment for 2021 on August 10, 20163. This assessment concluded that power supply is expected to be adequate through 2021 primarily focused on winter season. Consistent with the prior year filing, the updated forecasts indicate Pacific Northwest energy and capacity surplus will become a deficit around years 2O?l and 2022, primarily focused on winter and spring season. r Pacific Northwest Power Supply Adequacy Ass€ssment for 2021, at: www.nwcouncil.org/media/71505M12021- adequacy-assessmenrfinal-au 9_9_20 I 6.pdf l5l 35,000 30,ooo 25,000 20,000 15,q)0 10,000 s,000 0 -5,000 -10,000 -15,000 PSA Year -2009 -2010-.2011 -2O!2 -2013 -2015 -20162017 9E t- 3 I ,drs-rdr$"rdlrd;t"d9r*""*f "o""rdrot"o9"o"rol".*"sPr<r""dr<r"rdFORECAST YEAR Pacific Northwest Resource Adequacy Forum's Adequacy Assessment ATPENDIX J _ WESTERN RES0URCE AT,EQUACY EVALUATIoN Market purchase costs are reflected in rates. Consequently, customers bear the price risk of PacifiCorp's reliance on a given level of market purchases. However, customers also bear the cost impact of the company's decision to build or acquire resources if those resources exceed market altematives and result in an increase in rates. These offsetting risks stress the need for robust IRP analysis, efficient RFPs and ability to capture opportunistic procurement opportunities when they arise. Figure J.3 to Figure J.5 illustrates PacifiCorp's energy position developed from the 2017 IRP Update, progress from annual to hourly views of system position: o System Annual Heavy Load Hour (HLH) position r July Monthly Heavy Load Hour positiono Sample July Peak Day Position The energy position is compared to a load target, where load includes projected sales and reserve requirement. The gap between energy and load are met by market energy, however in many cases could have been met by other system resources. ure J.3 - S stem Annual Hea Load Hour Position 152 2018 2019 2020 2027 2022 2024 Icoal, dispatch EGas, dispatch IHydro -twindIothe. EGas, available Ecoel, available +Ioad ;t, r 50,mo 50,o00 30,000 20,mo 0 2021 2025 mz6 2o2' Isdar Iconse atlon + Load+sales+Rrv PA( r CoRP - 2019 IRP Customer versus Shareholder Risk Allocation Pacifi Corp's Energy Position The annual position during healy load hour with existing and planned resources, demonstrated system position without market purchases. The top blocks on each bar represents available ++{ o roII TI I I III I I -l 40,mo 10,000 APPENDLX J- WESTERN RESoURCE ADEeUACY EvAI.(rATIoN F ure J.4 - Ju \lont HLH Position The peak heavy load hour is the month of July, the system runs tighter compared to the annual basis. There is less undispatched thermal capacity available to meet load-plus-sales-plus-reserves than in the system annual HLH view. However, r"rndispatched capacity still exceeds requirements on a monthly level. The gap between energy position and load-plus-sales-plus-reserves could be met by market purchases, increased dispatch, reduction in sales, or a combination ofthe three. The model makes this decision on the basis ofeconomics and prevailing transmission constraints in a given hour. IEn I I ;ll I I e II I'; I I dII I t?,I !5 o 3,mo 4soo 4,tm 3,5m 3,000 2,ffi 2.(m 1,51tr 1,000 300 0 = 2021 2022 202' IHyd.o Ewind -lco.l,.vall.ble +Load 2018 ICoal, dispatch Iother 2019 2020 EGas, dispatch EGas, av.ilable 202ir 2029 2076 2oa7 Isolar Iconservatlon +l.oad+Salci+Rrv 153 PACTFTCoR" - 20l9IRP undispatched capacity. The gap between energy position and load-plus-sales-plus-reserves could be met by market purchases, increased dispatch, reduction in sales, or a combination actions. +*tk ar. Figure J.5 - Sample July Peak Day Position 12,tno 11,m0 10,m0 9,0m E,txr 7,0m 6,(xD s,o(tr 40(n 3,(m 2,txr !"otx) o ----t rIIrrrIIl llr---0 500 lom 9t^!iE: t: t t 2 t a 5 6 7 E 9 l()11 U('L15 15 i rA 19n2t222321 ]loarr Icoal dspelch -Gaq, dspatch I Hydro Ewind I(xher EGas avaibble :coa[ avaibble rPurchas€s Isobr Icon* vetlon +toadrs.b{{sv As described in Volume I, Chapter 6 (Resource Options), PacifiCorp, other utilities, and power marketers who own and operate generation engage in market purchases and sales ofelectricity on an ongoing basis to balance the system and maximize the economic effrciency of power system operations. In addition to reflecting spot market purchase activity and existing long-term purchase contracts in the IRP portfolio analysis, PacifiCorp models front office transactions (FOT). FOTs are proxy resources, assumed to be firm, that represent procurement activity made on an on-going forward basis to help PacifiCorp cover short positions. Solicitations for FOTs can be made years, quarters or months in advance, however, most transactions made to balance PacifiCorp's system are made on a balance of month, day-ahead, hour-ahead, or intra-hour basis. Annual transactions can be available three or more years in advance. Seasonal transactions are typically delivered during quarters and can be available from one to three years or more in advance. The terms, points of delivery, and products will all vary by individual market point. 154 l'^crFrCoRP - 20lt) IRP AppFNDrx J - Wris rERN REsotrRcE ADEeUA(y EVALUATIoN I I II I I II I -- I Lr It t T't n I I Et L The peak heavy load hour day runs tighter again compared to both annual and month view. The hourly variations and purchase drivers are captured in the sample day that cannot be seen in either annual or month peak HLH in Figure J.4 and Figure J.5. On an energy basis, the gap between energy and load-plus-sales is highest in hour 19 and 20. This is generally consistenl with the highest solar shoulder hour, or twilight peak, where solar is fading and other generation is ramping up to meet the gap. Market Purchases PACTTCoRP -20l9lRP ATPENDIX J - WF-SrERN RrsouRCE ADEeUACY EVALUATToN In developing FOT limits for the 2019 IRP, PacifiCorp reviewed the studies described in the sections above as part of its assessment ofmarket reliance in addition to consideration of its active participation in wholesale power markets, its view of physical delivery constraints, and market liquidity and market depth.The 20l9lRP FOT limits is 1,425 MW, reduced from 1,575 MW in the 2017 IRP, due to a COB decrease of 150 MW, reflecting expired reservation and review of historical derates as shown in Table J.7. Market Hub Figure J.6 shows PacifiCorp historical market purchases at three volume tkesholds. The majority of actual purchases conform to IRP FOT planning limits. As PacifiCorp is a summer- peakingsystem higher volume purchases occurred more Iiequently in the summer than in the winter. This assessment showed that from 2009 to 2ol7,27 percert of winter peak load hour purchases and 43 percent of summer peak load hour purchases were higher than the assumed IRP FOT planning limit of 1,425 MW. 250 I00 300 300 400 375 400 375 Reduced to 25() from 400 No Change No Change Mid-Columbia (Mid-C) Flat Annual or Hearry Load Hour Hcavy Load Hour California Oregon Border (COB) Flat Annual or Healy Load Hour Netado 0regon Border (NOR) Heavy Load Hour Mona Heavy Load Hour 1,4251,425 1,575 1,575l'olal 155 Aveilability Limit (MW) 2019 2017 Summer Winter Summer Winter (Julv)fi)ecember){December) Market Hub/Proxy FOT Product Type (Julv) t00 250 No Change No Change Table J.7 - Maximum Available Front Office Transactions PA(rH(oRP 20l9llll'APPENDIX J - WESTERN RESoURCE ADEeuAcy EvALrrATroN Figure J.6 - PacifiCorp Market Purchases 7m%otnro !(J f CLfrg(ucJs-r(E cou oo- 17.6%11.5% 809/o 6Wo 4Wo 2W6 o% r <1425 Summer I 1425 MW- 2oOO MW Winter >2(mMW 57.196 Aligned with review ofthe regional studies discussed above, and the historical market purchases and transactions, PacifiCorp has selected a peak-season FOT limit of l,425MW for the 2019 IRP. The company will continue to refine its assessments ofmarket depth and liquidity for transactions, informed by actual operations, to quantiry the risk associated with the level of market reliance. Several FOT studies are discussed and evaluated in Volume I, Chapter 7 (Modeling and Portfolio Evluation Approach) and Chapter 8 (Modeling and Portfolio Selection Results). 156 71.196 25,3% PAOFTCoRP 20l9lRP AppENDlx K - CApAcrry ExpANSroN [tEsrrLTS DEIAIL AppnNorx K - Cepecrry ExpeNsroN Rssulrs DprRrl This section provides the System Optimizer portfolio build tables for cach ofthe case scenarios as described in the portfolio development section ol Chapter 7. Thcre are thirty Initial Development cases, ten C-cases, seven CP-cascs, six front office nansactions (FOT) risk assessment cases, six Gateway & No Gas cases, eight sensitivity cases, tlree re-bundled demand- side management (DSM) cases, and five P-70 cases. Table K.l - Initial Dev ent Stu Reference Guide 24.407P-01 Coal Sludy Bgnchmark tsas.Med Cns, M.d Co,SegmenlI :0-r:l lt.l9 tP-02 Regional Hazc RefLrences/ Regional Hsze Bas.tsas.Med Cas. Med (()1 Segnlent l'loi I P-01 Regional Hszc Inteturqool/ Rcgion6l Haze Base Int€rtcrngoml I1,951 Mcd Gas. Mcd COr Scgmcnl F 20.10 P-04 Coal study C.42l Coal Srudy Basc Med Cas, Mcd CO:Segm€nl I 2028 P-06 I r.980 Ull\c Base Med Gas, Med COl Segntcnt I 1030Traruition Case C- ,l4slA ltcmative Ba3e P-07 Transition Case C-44b P-tl6 21,905 M€d Gas. M.d Co1 Segm.nt F 2029 2t,979P-08 Naughton I Small CC (P{3 basis)P-01 Rr\e MedCas. Mcd Co,Segnrcnif :0lo P-0.1 2t,885 Br\c IP-09 Naushron 3 t,arge GC (P-03 basis)Bas.Med Gas, Mdd CO: P-10 P-0.1 2t,723 Med Gas. Mcd aO"Segnrcnl Il 2019Economic Retirm€ l' P-l I Cholla ,l Rciiremed 1020 P-09 2 r,873 M€d Gas, M€d Col S€gftnr F 2010 21,854P-r2 Econonric Retirdenl l*P-06 Med C.rs, Mcd Co?I 2029 P-tl P.I I 22.:46 Base M€d Cas. Mcd CO:Segmcnll 20.11Bridscr l&2 sCR P- t.l Naushlon u1d Jim Bridssr Rerir€mcnr 2022 (Pl I Balis)P-09 2 r,696 Bise Med Gas. Mcd CO:Segm.nr F t0l8 P- 15 Retire All Corl by 2010 P28 tsasc Med Gas, Med COz SegmentI 2077 P- l6 P0.r 18.634 Base MedGas, No CO:2018No Co1 P-I7 Hi8h Co,P- 15 22,070 B.se Mcd Cas, tligh CO:S€gnrcdl I:2028 P-ln P- 15 30.022 Bacc Low Cas, SCC Co!Segm€nt F l02lrSoci.l Cost of Carboo P- 19 Lorl cas 20.882 LoB (hs, Mcd Co,SeSm.nt r 2021 22,746 Segrncnt IrP'20 Ili8h cas P-07 Br.e High G.s. Mcd Co,2029 P-28 Early Cmlstrip Retirement P-l I 21,805 Basc Mcd Gas. Med CO:Segmcol F l0i0 P-10 Naughlon I & 2 Retir.mcnt 2022 (Pl I Basis)P-II 2t,708 Med cas. Mcd Cor Ii;,sc Scgftlcnl I 2029 P--t I 21.652 S.gmenl I l0:6Naughlon I & 2 Retirement 2025 (Pl I B€sis)P-t I Med Gas, Nled ( O: P-12 Naughtoo I & 2 Retiremenl 2025 (?07 Basis-No Gadsby 2020) P-07 21,163 Base Medcas, Mcd CO:B.'s€Scgnlcnl T :016 t57 Portfolio Case Build Tables Cr!€Crs€ so PVRR(shl Lord Privr.e Gen COr Poltcy rOT3 G.t€$ry l" Y|tr of D.!criptior 20lo P-OJ P-34 Orcgon Study (Pl I - JBI & 2 RclirE 2022, Gadsby Rctirc) P-l I 2t,949 Bise Bilsc Med Gas. Mcd CO!Segrnent F l0l8 JimBridger3&4Retirillg 2022 (Pll wirt JBI a 4 r€tidnc 2022) P-lI 2t,132 Med Gas. Med Co!Base Segmeor 1029 P-15 P3l irith Jts I & 2 R.tircmcnt P-.1r 21.59-l Ba{c Mcd cas, Med CO:Base l 2026 P-.16 P3l $iih JB 2 & 4 Relircrnent P.]I 2t.419 B.sr Mcd Gas, Med Co:Base Segmeni F 1026 P,53 P-3 | with JBI-2 Retiritrg 2025. JB3 R€riring 2028, a$d JB4 Ret na 2032 P-l t 2l,.ll8 Basc Mcd Gas. Med COI S.grnent F 2016 P-5.r P-31 wilh IB2 Rctinng 2024 P--r I Basc B.\c M.d Gas, Med CO:Base f t0t6 PAcrrCoRP - 20l9IRP AppENDx K CAI,ACrry ExpANsIoN Rrsur.TS Dh l AlL P--rl orcsotr Study (Pl I JBI & 2 tutire 2022)P-ll 2 t,E95 Basr B.se Med Gas, Med CO,Bs.Segm€nL l0l0F Table K.2 - C-Case Stud Reference Guide P.:IIC P-l I with Nru8hton 1-2 Ac.elerared to 2025 P-l r : I,639 Bas.M.d Gas, Med Co:Base SeBn}.ntI P-.16C Economic R.tircmcnt 2* with cat way Scgmmt F (Pl2 with Gateway Segmcnt[] P-36 Dusc Basc S.gtnenI IMed Cas, MedCOs Basc P-.15C P3l wilh JB I & 2 Retircmcnt P-,15 2l,4t I B.r.M€dCas. Med Col Segmenl F P-.164 2t.422P,.16 BaJc Basc Mcd Gas, Med CO:Base Segment F l0l6 P-46J23C JimBridser3&4 Retiremcltt 2023 P-{6 Blrc Med a;ar, Mcd CO:T 2026 P.47C P45 GWS 2025.2028 P-47 :t..t67 B!\e Base Nl.d a;ns. N{cd CO:Base r P.48C P45 andGWS 2021 P-.18 21,481 Med Gas, Med CO:Bsse I l0t6 P.5]C P-31 with JB l-2 Rctiring 202J, JB3 RetirinB 2028, .tld JB4 Rctirins 2012 2 r.450 Bose Basc Med Cas, Med CO:Segment F 2O2(t P-5lJ2lC JimBridgerl&l Relirem.nl l02i P-5.]21,394 Basc Med Cos. Med Cor Scgment F 20_16 P-l I i*ilh JB2 Rctiring 2024 P.J.'21,59t Basc Med cas. Mcd CO:Base Segrnenlf 1026 158 P-15 F 11.708 Segmcot Cos€Delc ptton Prl.3nt C!!c so PVRR I-ord Prtl{(r Ger COr Poltcy FOTs l"Y€.r of l0l6 2026 2026 P31 wirh JB 2 & 4 Retiremenl 2026 Bas.Ba(c P-51 P.J4C Ba\c P-36( P P--',]6 2r,551 Basc Bas.M.d Gas. l,v{.d CO:S€8ment F 1026 Economic Retirclrcnt 2* with Gateway SeSment F (Pl2 with Gatelvsy S.gm€nt F) 2 t .480 Bas€Base ScSmcnt t':0t6P-45( P P3lwithJBl&2 Rctir€rrrcot P-.15 Med Grq Mcd COI 21.460P--t6( P Pll wirh JB 2 & 4 Rctircrn€nt P-.r6 M€d Goq Mcd CO:Scgmeorr 2016 21..10:P. 46J23CP P46C l,,nh JB3-4 Reriring 2021 P-46 Mcd G!s. Med Co?Blrse Segmc,rt Il 1026 P"47CP P45 cWS 202J-2028 F-41 21.469 Mcd Gas, M.d C(),Brsc Scg,ncnr Il 1016 P..1ECP P-.18 2t.151 Base Mcd Gas, Med COr B$c Scgmnt I.t0t6P45 and GWS 2ol3 21.471)Brsc S.gmcnt l 2026P-5-r( P P-3 I wi& JBl.2 RcririDg 2025, JBi Rctirin8 2028, and JB4 Retirirc 2032 P-51 Mcd Gas, Med CO1 PA( rl'rcoRr - 2019 IRP AppENDIx K - CApACrry ExpANstoN RESULTS DETAIL Table K.3 - CP-Case S Reference Guide Table K.4 - Preferred Portfolio Reference Guide Table K.5 - FOT Risk Assessment Case Stu Reference Guide P 45CNW Ir-45 2t,624 Bas€Base Mcd (ias.l,v{cd COI Base S.gmentI t026 P.15CP. t,ol P31 with JB I & 2 Retir€mcnl P.45CP 21,977 Basc M.d Gas, M.d Co:SegDeot Ir 2026 21,960 tsase Basc r 2026P-.l6CP- ToT Pll wilh JB 2 & 4 P.46CP Mcil Gas, MedCO: 2l,942 B.sc Scgm€nt I 2016P.47CP. roT P45 GWS 2025-3028 P47CP McdGas, McdCO: P-48CP. roT P..18CP 21.936 Mcd Gas. Mcd COr Brse Segmml l0:6P45 and CWS 2021 P-53CP- roT P.53CP 2t.919 Mcd Gas. Mcd CO:Basc Segmenl F 2026 P-31 with JBl-2 Rctirios 2025, JB3 Retirin8 2028, tnd JB4 Retirins 2032 P- 45CNW- FOT P.45CP 22,l5.t Base Med Gas. Med COz Il 2026P45CP No DJ Wilrd 159 so P\RR Ifid Privrte Cco CO? Poltcy( rse Dercrlptlotl Prlcra C.!e FOTr D€lcrlption so Pl?R (sm) Lord Prlvst€ GeD CO: Policy IOT!Grte*.y r! Yerr of P45CP No DJ wind Crs€Crs€ so P!'RR (sml Lord Prlvrte Gcr COr Policy rOT! l' Y€rr of Dcscrip.ion P^crrCoR.P - 2019 IRP APPENDIX K _ CAPACITY EXPANSIoN RLSTJLTS DETAIL Table K.6 - Gatewa & No Gas Case Stud Reference Guide Table K.7 - Sensitivi Case Stu Reference Guide Table K.8 - DSM Bundled Case Stu Reference Guide P-29 P-45CNW. No Ncw Grs Option P. 45CNW 2 t,798 lvtcd (;as. Mcd CO2 Segment l P.]9 PS P-29 Eith Pumpcd SbmBc P-29 I,970 Base Med Grs. Med Co?Ba*S.gm.nt F P-22 P-4sCNW, Energy Gatcwtry S€qment D.l P. 45CNW 21,886 Med Gas. MedCO2 B.rsc Add D.l 2010 P-t-1 P-4sCNW, Energy Cateway Scqmcrt D.l and F Add Seg. r afld D.l 2026P. 45CN\t'22,\5)Base Base M.d Gas. Med COz P-25 P-45CNW. EDergy Crtcway Segmenr D.3. E and H Add Sub- scg. D.3 & ScB. E &H l0lEP. 45CNW Base M.d Gas. Med Co2 Ba* P-16 P-4sCNw' Encrgy Gateway S.E ncnt H Add Scg. H 2028.15CNW I1.579 Bi\c Mcd Gas, Med CO2 s-01 20.617 tsis.l0l0P45CNU' s4l High Load P.TJ ' N\\')2,602 High Basd 2026 s-01 I in 20 Load Crowth P45CNW 21,6.14 1in20 Base 2026 s-04 Low Prilate Generuttun P45CNW 21.75E 20)9 s{5 High Private Ccneration P,15CNW 2t.37 t Base Higb tlase ?010 s-06 Busin€ss Plan P45CNW 21.695 Base 2028 s47 1030No Custorncr Prcftrence P.l5CNW :1,609 s-08 l0-10P,l5(NW 2 r.6.16 Bor. P.15DP P3l wirh JB I & 2 RetirenEnt P-.r5 21.516 Mcd cas. Med CO1 Bas.Scgmcnt I t0t6 P-I6DP P3l with JB 2 & 4 R€tirern€nt P-46 2 t.458 M€d Cas, Med COr Segmenlt 2026 Ij-5lDP P-l I wirh JBI-2 R.liring 2025, JB3 Refting 2028, and JB4 R€lirinc 2032 2026P-53 2t,478 Bose M€d Grs. Med Co:B!sc Scgmcnt F t60 Descrlptlor P.rent Crs€ so Pl?R Lord Prlvrte(;er CO) Poltcy FOTg G.r.a.y t" Yerr of Descrlptiol Pircrl Crse so Pl'RR (3m) Lord Privrte CO, PoIcJ FOTi l'Yerrof Delcrlldor Csse SO PVRR (sln)Loid Prlv.te Ccr COr Pollcy FOTs G.l.nrJ l'r Yerr oI N€s Thermrl All Custom.r Pr.tkcnce Dclcrlptlor Prrert Crse so PvRR Lord G€n FO'I'3 Grtc*ry lr Y€rI ol COr Pollcy P.O I 22,326 Med Gas, Mcd COI SegmcnlIP-70 P-01 with JB I 2022 RET 201(, P-01 22.482 Bast Med Cas. Mcd CO,P-71 P-01 \r'ith NTN I 2012 RFT Segmcnl I P-01 22_432P-12 P{l wirh Hsydcn I 2022 RET Med Gas, Med CO:Segmc I]:026 22.455P-?3 P-01 wnh Illmt.r I RET Bas.Mcd Cft. Mcd CO!Segment F 2076 22.44',1P-7.1 P4l q,ith Cmis I 2022 RET n!'.Med Ga5, Mcd CO:Ba$SeSmmrr t026 PACIITCORP - 2019 IRI AppENDLx K- CApACrry Exp NstoN RrsLrr.TS [)r]TAIL Table K,9 - P70 Case Reference Guide t6l so PI'RR lfid Prhrle GcnC.se Dr!crlpttor CO, Pollc-v FOTs G.eary Thenll 2026 P-01 P-01 a\l tr o p A oo E o) .o F .o EoQ U99,9 =,OYU@ o ) b0tr q- 6 E .E.E9z ! =F '5 .o EoU U ! EoU =oln D 60 LL o .o F a .o EoU U ! EoU z o 5 F o .o oO U a. E 8 Eoz l e .o Ftro ).o aU 9 Q o-E(, ! a trI tr o o , elL c,o Fco aU O E oz f E!! .o F E ,o U U o. Ea oz f E c.o Ftr.9 -o EoU3 O o. Ea .tr = f oo Ea b o -3aa bo Eo g b o ! oo Eo bo E so gl A EoU E & a 'ts oo.= Eo o tr o ! ,:l c > 00 Eo !c a c o + > + 00 Ec ca +! o sD Io o D DO Eo > IoE o f .q oz D o Io.c ocl> 3 o oo h + o f z oo h o+ o o tr E U o a. 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F..1) z9 z i Q iv oz c U : o- i 'l' t; n I il I tl'f I ilil I I ]t tl u tftlu u I ll T ]tul Itl I u ffi il tf tl [l' I fl' tl tt u I u ttll I IIIII # MT ttf mt tt tl tl tl tl 1t I I' [l'Itf I tl ut [17 tlll I [tff ill P^crrCoRP - 2019 IRP APPENDD( L - STocHAsrIc SIMULA.TToN RESULTS AppsNorx L - SrocHASTrc Srnaur-RrroN REsur-rs This appendix reports additional results for the Monte Carlo production cost simulations conducted with the Planning and Risk (PaR) model for the core, sensitivity and final screening cases. These results supplement the data presented in Volume I, Chapter 8 (Modeling and Portfolio Selection Results) ofthe IRP document. The results presented include the following: r Statistics ofthe stochastic simulation results . Components of portfolios' present value revenue requirements (PVRR) . Energy-not-servedo Customer rate impact of portfolios in the final screen as compared with the preferred portfolioo Loss of Load Probability of portfolios in the final screen as compared with the preferred portfolio There are thirty Initial Development cases, ten C cases, eight CP cases, six FOT Risk Assessment cases, six Gateway and No Gas cases, eight Sensitivity cases, three Rebundled DSM cases, and five P-70 cases. Table L.1 - Stochastic Mean lnitial Devel ment Cases P0l 24.t06 Pl2 23,678 P30 )1 711 P02 24.9t9 Pl3 24,0t6 P3r 23,484 P03 )1 R,Pl4 23.786 P32 P04 21.77 5 Pl5 24.285 P33 71 ROq P06 2.r.9:] 2 Pl6 23.889 P34 23,93{r P07 23,819 Pt1 24,182 P35 23.666 P08 23,875 Pl8 24.176 P45 23,525 P09 23,760 Pl9 24.000 23,4 t 3 P20 P53 23.468Pl0,'t 6ss 25.1 1 8 21,616P23.768 23,(186 P54 243 Introduction Mcd Gas, Med COr Name PVRR ($m)Name PVRR($m)Name PVRR ($m) ?1 750 P46 P28 Pl6 19.44{r 23,lr 1i9 29.847 39.712 Pl7 2t,013 24.t82 2tt.n58 _16,4t 5 Pt8 22.456 24.176 27,785 35,2'76 38,396Pl920.194 24.000 29,224 P20 25,1l8 7'7 \)1 PA( lrrCoRP - 2019 IRP AppENDx L - Sr(x'IrASTrc SIM(JLATToN R-ESULTS Table L.2 - Stochastic Mean PVRR by Price Scenario, lnitial Development Cases Table L.3 - Stochastic Mean C Cases Table L.4 - Stochastic Mean PVRR Price Scen CP Cases 23,314P3IC P36C 23,430 P45C )l ?t1 P.I6C 23.2711 P46J23C 23,312 P47C P48C 23.221 23,340P5JC P53J23C 23.391 P5.IC 23.3tJ I P36CP 36,561:ro'177 23,411 27.88 t P45CP 20.094 )t l{tl 27.186 36,934 P46CP 20.285 ,? ,())2',7,8t4 36.703 P46J23CP 20,306 36.55523,303 27,t112 P47CP 20.130 36.93623,?t9 27,805 P48CP 20.r73 36.79823,205 27,136 P53CP 20,32',7 36.82923,34n 21,889 P45CN\\'19,965 37,09521,207 27,946 244 PYRR ($m) Name Low Gas, No COr Med Gas, Med COr High Gas, High COr Social Cost of Carbon 20,833 28,397 Name Med Gas, Med COr PVRR ($m) 23,198 PVRR ($m) Name Low Gas. No COr Med Gas, Med COr High Gas, High COr Social Cost of Crrbon P^( rFrCoRP - 2(ll9 lRP AppEN'Dx [- - STocIlASt t('SIMt]LATtoN RLSULTS Table L.5 Stochastic Mean FOT Risk Assessment Cases Table L.6 - Stochastic Mean Gatewa and No Gas Cases Table L.7 - Stochastic Mean Cases P45CNW.FOT 24,015 P45CP-FOT 24,024 P46CP.FOT 24,099 P47CP.FOT 24,001 P48CP.FOT 24,098 P53CP-FOT 24.t64 P-22CN\r'23,603 P-23CN\l 24.t84 P-25C\W 24.239 P-26CNlV 23.307 P29 23.328 P29PS 23,616 s0t 22,0ta0 24,34(t s03 23.388 s04 )1 l{rx s05 )l q70 s06 24.038 s07 23.t26 s08 23. t86 245 Name Med Gas, Med CO, PVRR ($m) Name Med Gas, Med CO2 PVRR ($m) Name Med Grg Med COr PIIRR ($m) s02 PAcFICoR? - 2019 IRP AppENDrx L - ST(rrrAsrrc STMULATToN R.EsuLTs Table L.8 - Stochastic Mean DSM Rebundled Cases Table L,9 - Stochastic Mean P70 Cases P,l5DP 23,281 P46DP ,1 1SO P53DP 23,409 P70 24.04t P'71 24,OL0 P72 24.12'l P73 24,2(tl P71 24.230 246 Name Med Grs, Med CO: PVRR ($m) Name Med Gas, Med COz PVRR ($m) 95 23.952 24.228 24.258 10,521P01 24,759 25.056 25,089 10,723m2 23.612 23.945 23.996 10,395P039t{ 23.558 23.909 21.978 9,7 58P0.l 23,124 24.061P06133 24.149 10.436 P07 l3:1 23,610 )1q50 24.038 10,396 P08 134 23,664 24.006 24.1t5 t0,600 23.996 r0,5t4P09l3l 23,451 23,77I 23.875 9,8'.74P10l3:] 23.6t7Pll9ti 23.886 23.94t 10,415 Pl2 23.469 )l 7q6 23,907 to,z25 23,8'72Pr391 24.133 24,185 t0,532 Pt{185 23,54'7 23.92t 24.025 10,238 Pl5 9l 24.t29 24.387 )n a))10,t2'7 Pl6 23.648 24.045 24.151 13,505 Pl7 I l{)24.02t 24.301 24.310 10.953 24.19t 24.515 24,531 R 8{)1Pl8t3l 23,784 24,154 24.225 tt,317Pl9143 24,901 'r<'>1),\ 141 I t.377P20143 )1510 23,8 t I 23.{r59 I0 JltP2898 2 3.588 2 3.850 23,909 10.355P30t)9 23.340 23.607 23.658 t0,252PJI9l,l 23.605 10,405PJ2l0l23.875 23.940 23.607 l0,l6ttP3313423.938 24,O14 21.727 t0,143P34t3ll24.06t 24.159 P.t 5 106 ) \ 49()27.195 23.ri5l 9.818 21.373 21.647 :)l ?ol t0,284P4sl0t P46 108 ,l ,(R 23.565 23.594 9,951 P53 t09 23,3t2 23.622 23,644 10,002 10,305P54t0223.47 |23.738 23;792 PAcrrrCoRP - 2019 IRP AlpENDrx l.- SToclr^srrc SlMUr.ATroN REsuLTs Table L.l0 - Stochastic Risk Results, lnitial Development Cases - Medium Gas, Medium CO: 247 Initial Cases Medium Gas, Medium COr Standtrd Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of3 Ilighest) No Fired Coits PVRR ($m) 97 t42 23,562 23,882 132 159 Initial Cases Low Gas, No COr PVRR ($m)Standard Deviation sth percentil€90th percentlle 95th percentile Upper Tell (mean of3 Ilighest) No Fired Costs Pt6 t9;743 2 r.013 1 102I 21.080 PAcTHCOR-P -20l9lRP AppF:l'Drx L - ST(rHAsrrc STMULATIoN REstrLTs Table L.11 - Stochastic Risk Resul Initial Develo ment Cases - Low Gas, No COr Table L.l2 - Stochastic Risk Results, Initial Develo metrt Cases - Hi Gas, Hi h Co: Table L.l3 - Stochastic Risk Results, Initial Develo ment Cases - Social Cost ofCarbon Iritlal Cases High Gas, Hlgh COr PVRR ($m)Standard Deviation 5th percentile 95th percentile Upper Tail (mean ofJ Highest) No Fixed Costs Pl6 Pt1 29.0t4 21 ,947 28.010 28,970 29.407 29.539 28.7942ti.l5 I 28.700 Initial Cases Social Cost ofCarbon PVRR ($m)Standrrd Deviation 5th percentile 90th percentile 95th percentile Upper Tail (mean of3 Highest) No Fixed Costs Pl6 Pt7 2t.102 Pl tl 22.592 Pl9 P20 20.833 21.080 l9,,l4lt t9,295 19,555 19.593 Pl7 20.892 2 r.l6l 2 t,198 Pt8 22,456 22.1t5 ') ) \q))) t\)1 22,69f Pt9 20.t94 20.052 20,296 20,3t8 20.465 20.702 20.952P2020.833 20,913 90th percentile 29.847 29.555 30.056 30.202 30322 28.8511 28.652 29.069 29.|4 Pt8 2'.7.785 71 51\28.01t4 Pl9 29.224 29.659 P20 28,191 28,51s 19.593 t9,743l9,,t4lr t9.295 19.555 2 t. t9821.013 20.892 2t.t6l 71 tiS.|22.456 22.315 -r) ti)1 20.46520.194 20.o52 ,n rq6 20.318 20;702 20,913 20,952 248 PACTFTCoRP - 2019 iRP APPENDD( L- STocltAsrtc SIMULATTON REsuLTs Table L.l4 - Stochastic Risk Resul C Cases - Medium Ga Medium COr Table L.15 - Stochastic Risk CP Cases - Medium Nledium COz )1 :)11 23.507 23,536 23.580P3IC23,1',74 23,2t3 21.57 4 23,677 23,81 IP36C,1 110 23.t3I 23,409P45C23,283 23.449 23,49t P46C 23,218 23.t25 23,4(:t4 23,458 23.485 21. t60 27.445 23.506 23.526P46J23C21,312 P47C 23,l9ll 23.045 ,1 111 23,17 t 21,41I P4ttc 21,221 23,O73 21,342 23.396 23,436 P53C 23.340 23.185 23.466 23,518 23,558 P53J23C 23.391 ?l )1()l s)s 23,580 23,612 P54C 23.3It I 23.231 23,509 21.547 :)1 5()l 21.194 21,561 23,657 23;780P36CP23,413 23.043 )11))23,367 ,1 ',lq?P45CP 21,192 t? )() )23.143 23,426 21.464 23,49t)P46CP ?1 101 23.t44 23,456 21.492 23.534P46J23CP 23.06'7 23,349 23.393 23.435P4'tCP 23,219 23,051 23,321 23,374 23,42tP48CP21,205 23,348 23.t99 23,416 23.52t 23.565P53CP 23.207 23,062 23,34r,i )l ?7')23.409P45CNW 249 C Crses sth p€rcentile 90th pcrcentile 95th perccntile Upper Tail (me8n of3 Highest) No Fixed Costs PVRR ($m)Standard Devirtion CP Cases Medium Gas, Nledium COr Sth percentile 90th percentile 95th pcrcentile Upper Tail (mean of3 Hlghest) No Fixed Cosas PvRR ($m)Strndard Devlatlon PACTFTCORP - 2019 IRP AppENDIx L- SToctIAsflc Sn\,flrLATtoN RESULTS Table L.l6 - Stochastic Risk Resul CP Cases - Low Low C Table L.l7 - Stochastic Risk CP Cases -C P36CP 20.377 20.229 20,485 20,515 20,(43 P45CP 20.094 20.00r 20,187 20,2t6 20,232 P46CP 20.285 20,t87 20,387 20,409 20.427 P46J23CP 20,3 0(r 20.195 20.412 20,427 20.4it7 P47CP 20,130 20.030 20.223 20,264 20,279 P48CP 20,173 20,070 20.268 lo )o?20,320 P53CP 20,32'7 20,22ra 20.428 20.450 20,4't4 P45CP:,,tW 19,965 I9,878 20,052 20.0tt5 20. r0l P36CP 27,881 2'7 .612 28,091 28. t93 2t3,321 P45CP 27,786 27.585 27,947 28.039 28.069 P46C P 27,8t4 2'7 ,596 27,91t 28.067 28.097 P46J23CP 21,812 ?7 5q5 2U,00u ?R Osq 28.093 P47CP 2'7 .805 2'7,596 27,957 28,060 28,091 P48CP 2'7,528 21,893 27,990 28.028 P53CP 27,889 27.6'72 28.05 r 2 n,144 28.180 P4SCPNW 27.946 27.748 28.t2t 2n,190 28.222 250 CP Cases Low Gas, No COr PVRR ($m)Standard Devialion sth percentile 90th percentlle 95th percentile Upper Tail (mean of3 High$t) No fixed Costs CP Cases High Gag High COr PVRR ($m)Standard Deviation 5th percentile mth perceotile 95th percentile Upper Tail (mean of 3 Highest) No Fixed Corts 36.278 36,808P36CP36.561 36,887 36.953 36,713P45CP36.934 17 ll?3'7,t41 1',7.201 36,451P46CP36,703 36,897 36,923 36,982 P46J23CP 36,555 36.296 16 7S5 36.784 16 R',l5 P,l7CP 16 q16 36,699 37.139 37.150 37,215 36,561P48CP36,798 37.007 37,020 17.078 16 576P53CP36.829 37.025 37,043 '17 lr)L) P45CPNW '17 0gl 36,U77 11 )O')37,303 11 711 AppEN'Dx [- - SToCIIAstlc SIMTJLATIoN RESITLTS Table L.18 - Stochastic Risk CP- Social Cost of Carbon Table L.l9 - Stochastic Risk Results, FOT Risk Assessment Cases - Medium Gas, Medium CO: P45CNW 24.07 5 23,9t',7 24.212 24.258 24.298 P45CP 24,024 23,{t67 24.160 24,t91 24,264 P46CP 24.099 23,924 24,239 24.296 24.3 t4 P47CP 24.00t 23,835 24,130 24,t56 24.236 P48CP 24.098 )t q)7 24,24t 24,291 24,331 P53CP 24.t64 23,986 24.305 24,157 24,399 25t PA(r!IC0RP - 2019 IRP CP Cases Social Cost ofCarbon sth percentlle 95th percentil€PVRR (Sm)Standard Deviation 90th percentile Upper Tail (mean of 3 Highest) No Fixed Costs FOT Cases 5th percentile 90lh percentile 95th percentile Upper Tail (mean of3 Highest) No Fired Cost! PVRR($m)Standard Deviatioo Gateway and No Gas Studies Standard Deylation sth percentlle Upper Tail (mern of3 Highest) No Fixed Costs 23.(n)3 23.47 0 23.805 24.10'7 24.190 m.)11 ttR P29PS 23.616 APPENDD( L - STCTHAS'Ir( STMULATToN REsr[.Ts Table L.20 - Stochastic Risk Results, Gateway and No Gas Cases - Medium Gas, Medium COz Table L.2l - Stochastic Risk Resul Sensitivi Cases - Medium Gas, Medium C02 Table L.22 - Stochastic Risk Results, DSM Rebundled Cases - Medium Gas Medium CO: Senslth'itv Studies PVRR ($m)Standard Deviation sth perccntil€90th percentile 95th perceotile Upper Tail (mean of 3 Hlghest) No Flxed Coits 21,919 22.248 'ri t9')s02 s03 24.146 23.3 88 )t t1\24.52',7 s04 2 t.l0r{')I 44 2:t.519 s05 22.91tJ s06 24,207 292)1 s07 2t. t26 s08 tl.lti6 23.3t323.039 23.386 P45CPNIV 23.148 23.409 PVRR ($m) DP Studies Standard Doiation sth percentile 90th percentile 95th perc€ntile Upper Tail (mern of3 Hishest) No Flxed Costs P45DP P46DP 21. r04 22.956 )l rri*23.312 2.1..17It23.144 P5JDP 252 PYRR ($m) 90th percentile 95th percentilc P-22CN\ry'23,733 )1 -114 P.23CNW 24.t84 24.037 24.3 5ti P-2SCNW 24,239 24,093 24,3't2 24,4t4 24,446 P-26CNlV 23.307 23,162 23,454 23,419 23.5lri 23,182 23,46',7 )1 501 23,536 21.419 )\ 111 23,803 23.814 PACTFTCoRP - 20l9IRP s0l 22.080 22.208 22,282 24.60t ,1f 1(21,5t4 23.550 23,615 23,l6l 23,480 22.827 23,102 23,134 23,t77 24,03u 23,902 24,183 l, oo')23.254 23,301 13.I34 )11SO )1 ,r)7 23.062 )7 71) 23.248 23.174 23,Ot2 21.12t 23,232 23,070 23.3n l 21.401 21.444 PA('rr-rCoRP - 2019 IRP AppENDx L - SrocHAsrrc SIMULATToN REsuLTs Table L.23 - Stochastic Risk Resu P70 Cases - Medium Medium COz Table L,24 - Stochastic Risk usted Initial Cases Table L.25 - Stochastic Risk usted PVRR Price Scena Initial Cases P70 24,041 23,882 24,t6t 24,204 24,248 P7l 24,010 23.859 24,t39 24.206 24.23'!24,2',75 24,3t'1P1224.121 24, t00 24,191 24.426 24.46524.261 24,07 5 24,164 24,3n1 24,423P',l4 24,230 25,319 24,811 24,92t1ml PI3 25,226 P3l 24,661P0226,t',14 24.987 P32 24,941POJ,s )') P0,l 24.97 4 P15 25.506 P33 25,010 P06 25.139 Pl6 25.09'7 PJ4 25.14(r P$7 25.02t Pt7 25.400 P35 24,ti5tt P08 25,011I P18 25.602 P,l5 24,7 tO P09 24.960 25.2t t P46 24,591 Pl0 24.848 26.385 P53 24,650 24.8',79 P54 24,ti06Pll24.966 25.097 31.357 41,7 t'7Pl620,427 25.400 30.312 3't,241Pt722,07 t Pl8 23,587 25,602 29,t87 37,051 Pl9 21,209 25,21|30.701 40,334 P20 2l,88I 26.3ns 29.832 19,42t 253 P70 Studies PVRR ($m)Standard Devietion sth percentilc 90th percentile 95th pcrcentile Upper Tail (mern of 3 Highest) No Fixed Costs 24.t65 23,969 P73 Med Gas, Med CO2 PVRR ($m)Name PVRR ($m)Name PVRR ($m)Name Pl2 P30 P14 Pl9 P20 P28 PVRR ($m) Name Low Gas' No COr Med Gar, Med c(}, High Gas, High COz Socid Cost of CarDon P^crFrCoRP -20l9lRP APPENDD( L - STCTHASTTC SrMUr.ATroN R-EsrJLTs Table L.26 - Stochastic Risk usted C Cases Table L.27 - Stochastic Risk A usted PVRR b Price Scenario CP Cases Table L.28 - Stochastic Risk usted FOT Risk Assessment Cases P31C 24.55t P36C 24.614 P45C 24,456 P46C 24,45t P46J23C 24,4n8 P47C 24.367 P4IIC 24.391 P53C 24,516 P53J23C 24.570 P54C 24.558 P36CP 2r,403 24,595 )q ?so 38,405 P45CP 21.105 24.360 29.188 38.79 r P46CP 21,30s 24.465 29,?17 1'{ SSn P46J23CP 21.127 24.418 )o,)15 38,394 P,I7CP 21.143 24.388 29,208 38,794 P48CP 21.187 24,1'14 29, r35 3 tt,649 P53CP 2t.349 24.524 7().2()6 38,68 t P45CNW 20,969 24.376 29.355 38,960 P45CNW 25.288 P45CP 25,233 P46CP 25,314 P47CP 25.209 Pd8CP 25,3t? P53CP 25.382 254 NNme Med Gas, Med COr PVRR(Sm) PVRR ($m) Name Low Gas. No CO2 Med Gas, Med COz Iltgh Gas, High COI Social Cost of Carbon Name Med Gas, Med CO2 PVRR($m) PACTFICoRP - 2019 IRP AppENDx L- ST(rHAsrrc STMULATToN RESULTS Table L.29 - Stochastic Risk A usted Gatew and No Gas Cases Table L.30 - Stochastic Risk usted Sensiti Cases Table L.Jl - Stochastic Risk A usted DSM Rebundled Cases Table L.J2 - Stochastic Risk usted P P70 Cases P-22CN\1'24.792 P-23CNW 25.402 P.25CNW 25,460 P-26CNW 24,481 P29 24.503 P29PS 24.806 s0t 23.193 s02 SOJ )/ 51"( s04 24.482 s05 24.t26 s06 25.248 s07 ?4.29t s08 24.353 P45DP 24,453 P46DP 24.526 P5JDP 24.5'17 P70 25.25t P1t 25.?t8 P12 25.334 P73 25.482 P71 25.449 255 Name Med Gan, Med COr P\RR ($m) Name Mcd Gas" Med CO, PVRR ($m) Name Med Gas, Med COr PVRR (Sm) \amc Med Gas. NIed COr PVRR ($m) P^crrrCoRP - 20l9lRP AppENDIx L - STocIIASTI( SIMrrr.ATroN REsULTS Table L.33 - Carbon Dioxide Emission Initial Cases Table L.34 - Carbon Dioxide Emissions Price Sc Initial Cases P0l 6 t 6,tt96 Pl2 579,t6'7 PJO 587.905 605,1172 Pl3 604,396 P3l 588.421 595,728 Pl4 535.7'7 4 P32 sR1 565 P04 567.901 Pl5 472.569 P33 5160 5R6 P06 585,907 P34 568,422Pl6669,944 5 8 r,583P07 Pt7 475,390 P35 P08 595 956 Pl8 421,tI0 P45 5ta3,9lt I P09 5q7 RSS Pl9 607,t5'7 P46 560.199 P10 57 t,70'7 P20 607,t57 P53 562,025 Pll 596,91 I P26 594,322 584,3'77 Pr6 674.t84 669.944 496,102653,963 Pr7 465.998 415,190 166,220 Pr8 42'1,n0 32 t,0004t8,674 43 1,628 Pl9 60't .157 459.4696o't.941 598.587 P20 579,150 607.157 431,t32572.793 256 Med Gas, Med COr Name COr (thousand tons)Name COz (thourand tons)Name COz (thousand tons) m2 P03 557.4lt9 P54 CO: (thousand tons) Name Low Gas, No CO:Med Gas, Med co, High Gns, Hlgh COz Socirl Cost ol Carbon 418,',795 5 88,334PSIC 55n ' 1?P36C 578,607P45C 560.210P{6C 553,673P46J23C 573,088P4',tC 567 ,025P.18C P53C 562,972 P53J23C 556 qSO P5{C 581.465 PACTFTCORP - 2019 IRP AppENDtx L - STocHASTtc SIMULA]IoN REsrn,TS Table L.35 - Carbon Dioxide C Cases Table L.36 - Carbon Dioxide Emissions Price Scenario CP Cases Table L.J7 - Carbon Dioxide FOT Risk Assessment Cases 54() 1lq 549.427 544.O92 405,969PJ6CP 517,439 57 t.643 432.168P45CP577,n06 557,824 553,331 4t4.320P46CP5i5 I ),) 552,065 549,152 4t 1,129P46J23CP549,304 572,966 5',73,649 568.183 429.251P47CP 567, r63 567.889 562,I3 424.O',?3P4TiCP 560 55i 556,201 4t8,t l6P53CP558,1n6 585,e1 579,071 431,599P45C:rlw 586.641r P45CN\r'-FOT 542.M6 540.r34P45CP-FOT P46CP-FOT 522.51O 515.827P47CP-FOT P48CP-FOT 533,930 525.164P53CP.FOT 257 Med Gag Med CO, (ahousrrd tom)Name CO2 (thoussnd tons) Med Grs, Med COt High Ger, Iligh COI Social Cost of Carbon Name Low Gas, No COr Mcd Gas, Med CO2 (thousand tons)Namc 58 t.028P.22CNW 544,8t IP.23CNW P-25CNW 580.0t4 P-26C\\\'579,969 580.126 576,n06 PACI.ICoR] - 2019 IRP APPENDLX L _ SToC}IASTIC SIMULATIoN REST]LTS Table L,.18 - Carbon Dioxide Em and No Gas Cases Table L.39 - Carbon Dioxide Emission Sensi Cases Table L.40 - Carbon Dioxide Emission DSM Rebundled Cases Table L.4l - Carbon Dioxide E P70 Cases s0r 569,357 607 .239s02 590 115s03 S0.l 590,401 s05 5tio,957 s06 5 86,136 s07 583,916 s08 581.368 P45DP 578,417 P46DP 556,142 P53DP 559,529 P70 25.251 P7l 25.?18 P72 ?5.314 25.482P73 25_449P74 258 Med Gao, Med CO2 (thowrnd ton$)Name P29 P29PS Namc Med Gas, Mcd CO2 (thouiand tons) Name Med Gas, Med COz (thousrnd tons) Med Gaq Med CO2 (thou3and tons)Name Pl2 5.3 P30 6.4P0l4,3 Pl3 5.3 P31P025.6 5.8 P14POJ5.3 t 0.2 P32 5.5 P04 '7 .2 P15 7.9 P33 4.',7 P16 4.4P0640 P34 5.0 Pt7P074.6 37 _9 P35 6.7 P0{t 5.8 Pl8 71,3 P45 5.2 P09 5.9 Pl9 4.5 P46 8.1 Pl0 6.0 P20 4.5 P53 8.3 Pll 5l P2r,r 5.s P54 5.8 PACTFICoRP - 2019 IRP AppENDLx L - STocHAsrrc STMULATToN Rtsul-'r's Table L.42 -Annual Not Initial ment Cases Table L.43 - A Annual ENS Price Scen Initial ment Cases Table L.44 - Average Annual Energv Not Served, C Cases 4.4 4.4 4.4 4.5Pt6 I7.9 31 .9 38.0 3 7.9Pt1 73.8 71.9 13.9Pl8 4.5 4.5 4.5Pt9 4.6 4.5 4.6 4.6P20 6.8P3IC 8.9P36C 6.'.lP45C P46C 1.2 P46J23C 8.3 8.1P47C 7.5P48C 1.4P53C {,i.3P53J23C 1.7P54C 259 Med Gas, Mcd CO, Name GWh Name GWh Neme GWh GWh Low Grs, No COr Med Gas. Med co, Hlgh Gas, High col Social Cost of Carbon Name 4.5 Name Med Gas, Med COr GWh AppENDx L STocHAsl r( STMULATT0N RrsLrLTs Table L.45 - Av Annual E Not Served Price Scenari CP Cases Table L,46 - Avera Annual Ene Not Se FOT Risk Assessment Cases Table L.47 - Aver Annual En Not Gatewa and No Gas Cases P36CP 7.5 7.5 7.5 7.5 6.3 6.3 6.4 P46CP lt.4 8.4 8.4 8.4 P46J23CP 9.1 9.1 9.1 9.1 P47CP 8.9 8.9 8.9 8.9 P48CP 8.3 ll.3 8.3 8.3 P53CP 8.4 8.4 It.4 8.4 P4sCNW 5.4 5.4 5.4 5.4 P45CNW.FOT 5.2 P45CP-FOT 6.2 P46CP-FOT {t.(: P47CP-FOT 6.5 P48CP-FOT '7.6 P53CP-FOT It.5 P-22CNtV 4.9 P-23CNW 4.8 P-25CNW 4.0 P-26C\lV 4.0 P29 4.2 P29PS 260 PACFTCoR? - 20l9lRP GWh Name Low Gar, No CO2 Med Ges, Med COr High Ges, High C0r Social Cost of Carbon P45CP Name Med Gas, Med COr GWh Name Med Gas, Med CO2 GWh 30.8 3.5s0l 8.4s02 1.1s03 5.1s04 5.4s05 6.5s06 5.6s07 s08 l'^( If rCoRP - 2019 IRI'APPENDD( L - SlocHASTrc SIMULATIoN RrsuLTS Table L,48 - Av Annual Not Cases Table L.49 - Av Annual Not DSM Rebundled Cases Table L.50 - Av Annual En Not P70 Cases P45DP 6.7 P46DP 8.6 P53DP 8.6 25250.1{P70 252 I l{.3P7t 25334.3P72 254n1.9P13 25449.2P74 261 Med Gas, Med COr GWhName Name Med Gas, Med COr GWh Med Gas, Med COr GWhName a.l\oa.l \o o\ .l €- .{ -.a-\oa-\o-\o\\o-.l o,al \o .,1 o al \c or:5 a = \o a-o.o.\o \oal o\o.o c! o a-\o a-c..t\o rr o\o c o c \o- o.c o\o o. 66 a- a \o \o o.o.o \o 6o a.tqJ q!q\ t-o,\o\o a- c|,alt..6\ \o o o t-o \o o o o. o t..c.I a-t-- \co \o F.a-a-a-€l'-\o \o \oIr @FT\cr.,-\oa-\oa-aa-F.rr \o c\o.F- \o\o c- a- ar ar a\ o\ o) \o \o oo.o:I \o .i \oa-o\ .i o\ o a No: \c ;a-a o,\o o \c \o \o \o @ a-@ o o.o o o o \o o o o o. !t 9 o o.\o 6 oo !co<..o o a-<.. 9 oi c Ir .r, ar c o o o €tr €t'- U q)z 2. 6 o U U I -] F o) (h 4) F f dzotr l a2F I oF IJ z d o I 9 U A. -d5dFt .Ei=;o.lti d, Oa,sAU E'? E ..E i!,t::3,s g CQ A. c E!EE Ls# t4 oo\ ,o, Irl Fg ar!E6 \o qr [< EAE-60E>s 9 o lrEF z q\ o O + Q z '-.1 (l) Q U z 2 (l) Q !l)o (u L (u U) (J t- E U I I F U U I UNra '1o €F c) U L a (l) q) I U && It J F -dEdFt !l .E,EE;AE QI C EI?r'i 7E!Ec2s-= E'E.= -z=i a o a--c tll ?e69 orI E,q \o \o \.o\ er! .:d: & ah S= F E z Et -H.Ei=;AE € ,Q8Eo"c t.. Et?2.= Qg =.E'3E @ \o EIE.= -E:S h;a6 l'r za a-c e Fe oo!!c -t \c oF :ZY'E d:6OE>.E dd, a 1- !, F z a:: \oo'o.5 a- 5 'o \C.a \t) \o a c'io o. 5 (, a \oNs Ia- a \o o a .t ooi al o.€ o .tF o:\o =f- o\ o\o oo c-:c. F o \oq\o\o\o ol at \o$- q o a- 6 aro\ a t-o\o,ao. \.)\or-ar ot--o, .i \o o o a- o o \o !'.o. o \o a-' \o a- r--ar 6 c c.n o F. l.) zo =) !- E o J Ez +\oa.t z (,z q) Q Q U (J I\ora ..] F U o Q a Q,, U Lcl U) U (.) Iiainj o o U .o> .EiE;AE dI ESEde o.\o d, = - P8 E.E E3.s gl,d=oa ar- 6D ;E? aa6 a q)o. \o a- a- o!:e= 5o \o o.o' 53: o I& ta GE6i,1 F \o o o' z t-U !U o. zEEt 6\o \o \o .Ei=;BE € .O \J E- !o,:i. = 6D? E.E Egs ! 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