20191018IRP Volume II Appendices M-R.pdf

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VOLUME II - APPENDICES M-R
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This 2019 Integrated Resource Plan Report is based upon the hest available information at the
time of preparation. The IRP action plan will be implemented os described herein, but is subject
to change as new information becomes available or as circumstances change. It is Pacirt(brp's
inlenlion to revisit and refresh the IRP action plan no less.frequently than annually. An),
refreshed IRP action plan will be submitted to the State Commissions.for their i4formation.
For more information, contact:
PacifiCorp
IRP Resource Planning
825 N.E. Multnomah, Suite 600
Portland, Oregon 97232
(503) 813-s24s
[e-mail]
www.pacificorp.com
Cover Photos (Top to Bottom):
Marengo Wind Project
Transmission Line
Electric Meter
Pavant III Solar Plant
PACIFTCoRP 20l9lRP IABI,F, OF CONTENI'S
TanIe op CoNTENTS
TABLE OF CONTENTS
INDEX OF TABLES
INDEX OF FIGURES
APPENDIX M - CASE STUDY FACT SHEETS
CASE FACT SugpTS OVERVIEW
INITIAL PoRTFoLIO-DEVELOPMENT FACT SHpgTs
C-CeSps PORTFOLIO-DEVELOPMENT FECT SugrrS..
ENERGY GeTgwey PORTFOLIO.DEVELOPMENT FACT SHEETS
SENSITIVITY FACT SHeeTs
APPENDIX N - CAPACITY CONTRIBUTION STUDY
INTRODUCTIoN
l
lv
PREFERI-ED PoRTFOLIO FACT S9r8r........
273
278
280
340
360
374
.378
273
386
397
399
400
40r
402
403
404
577
571
578
....397
CF METHODoLOGY
ECP METHODOLOGY
NATURAL GAS RESOURCES
RELIABILITY ASSESSMENT
PORTFOLIo-DEVELOPMENT INPUTS
FTNAL CF METHoD RESULTS.........
APPENDIX O - PRIVATE GENERATION STUDY 407
APPENDIX P - RENEWABLE RESOURCES ASSESSMENT
APPENDIX Q - ENERGY STORAGE POTENTIAL EVALUATION........... s77
INTRODUCTIoN
Pnnr l: Cp.ro Spnvlces
Et\E RGY YA LLr E ............
CP-Cesgs PoRTFOLIO-DEVELOPMENT FACT SHEETS
NO GAs CASES PoRTFOLIO-DEVELOPMEruT Fecr SHEETS ...........
I
493
I
PA(rI-rCoRP - 2019 IRP TABLI OF CON'I EN TS
OpER,tnNG RESl:Rt E ytt.uE.........................
TR,lNSMtssIoN AND DtsruBUrroN C,lpACITy
G ENE R 4r'toN C,t PAC rrr.......
PRRT 2: ENERGY STOTecg OpenATING PARAMETERS
PaRT 3: DISTRIBUTED RESOI-,R.CE CoNncun TIoN AND APPLICATIoNS
SECoND,tRy VoLTAcr ......................
7'& D CApACrry DEI"t:RR"4t..............................
C1MB|NED SouR ANt, STokAGE .....
(-osr-EI-'l. Lc tIt'ENF.sJ REsLzils.....
APPENDIX R- COAL STUDIES
581
J8J
585
586
588
588
J88
589
589
591
PHASE ONE: UNIT.BY-UNIT CoIT STunIss
U N I't - R y- [ ]N rr STU D y M t:l o Do LoGf
UNIT-BY-UNIT SrUDy R85UIT5.............,,
PHASE Two: STACKED COAL STUDIES
A DDITIONAL R}JSO(I RCE OPTIONS .,.........
TR,ANSM 1 SS IoN M)DE I. fiiG E Ii I IAN. E M EI|T....
ST)O 1,1 S.I'I C RI SK ANA I,y S]S
I.I P DAT ED UNIT. B y- L] N IT SU M MA Ry R}iSLILTS
ALTERNATF, YE,4R UNIT ANALYSB
STA.KED STUDY MET\ toDoLoGy
STACKED STLTDY Rfsr //- rs..., ...... .
I N ITI A L R E I. IA B I L I Ty A S S ESSM h: N T
PHASE THREE: RELIABILITY ANALYSIS oF CoAL STUDIES
,\TAKEIk ttt R l;t.FDBn(K.......... . .
(.o1 L I I Nt t F(x 1u.........................
.lHoRt F,I L Mtt rGAi 7().v.................
RELIABILtl y Stt t Dy M ETHoDoLocf .
lll:LtAuuJ n Sn tDrRL-rt r1-s...........
591
592
592
593
595
595
596
596
596
601
602
604
605
606
606
606
607
609
.....61l
INTRoDUCTIoN
PACTTICoRP - 2019 IRP TABLE oI. ('ONTFNTS
INoEx op TRsr-ps
TABI,E N.I _ ECP METHoD CAPACITY CoNTRII]TITIoN VAI-IIES FoR WIND
^ND
SoI,AR ......
TABT.E N.2 - INrrr,tr Capacrrv CoNTRIBtJTToN VALUES FoR Wr.rD, SoLAR, AND SToRAGE
TABLE N.3 _ INIIT,CL CEPACI Y CONTRIBUTION VALTIES IIOR WIND AND
SoLAR CoMBINED wrrH S'loRAGL
TABI,t, N.4 - FIN^L CF METHoD CAPACITY CoNI.RIBUTIoN VAI,T]ES I.oR WIND, SoI,AR, AND SI.oRAGE
T^BI,E N.5 _ FINAL CF METHoD CAPACITY CONTRIT]TITIoN VAI-[,IES FoR WIND AND
Sor.AR CoMrlrNuD wtII S.t()RAGE..
401
402
403
404
........405
TABLE Q.l - ENLRcy MARGTN By ENERGY SToRAGE TECltNoLocy ...............
TABLlj Q.2 - INTRA-HouR Fr-ExrBr.E RrsouRcr, CREDrrs By RLSoURCE TYPE .............
TABI,E Q.3 _ SHARE oF DISTRIBUTION LoAD BY S-IATE WITH P(IEI.{TIAL UPGRADE DEFERRAL.....
TABLE Q.4 _ FORI,CASI'ED DISTRII]UTION LOAD GROW]II ABOVE THE 90 PIjRcLNT
PLANNTNC THRESHOLD..................
TABLL Q.5 - ENERGY SToRAGE APPI,ICATIoNS . ANNUAI, BENEIjTfS STREAM
AND CoST-EI,I.ECTIVENI]SS
580
581
584
TABI,E R
TABLE R
TABI-tr R
TABLE R
TABLT R
TABI,I j R
TABLE R
TABLE R
TABI,I' R
TABLE R
TABLI, R
TABI,E R
TABLE R
TABLI. R
TABI,E R
TAI]LI] R
TABI,Ii R
TABLE R
I _ SLIMMARY oF UNIT-BY-UNIT METHoTDLOGY STEPS ............,,.,.----
2 _ UNIT-BY-UNIT CoAI, STUDY RESULTS RANKED t}Y PoTENTIAI, CIISToMI]R BENEFITS
3 - UNIT.BY.UNIT UPD^TF- (BENEFII.YCoST oF RETIREMLNI'
4 _ SO MODEL MEDIUM CAS, MEDnIv CO2 PVRR BY UNIT..
...593
...594
...597
...598
...599
...600
...601
...602
...602
...603
...604
...604
...605
...606
...606
...607
584
590
609
6ll
5 - PAR MI]I)IIIM GAS. MIjt)ItIM CO2 PVRR BY UNII
6 - PAR HIGH GAS, HIGH CO2 PVRR 8Y UNIT
7 _ PAR Low GAS, ZERO CO2 PVRR BY UNIT.......
8 SO MoDEL ALTERNA,II] YEAR ANALYSTS, MEDIT]M GAS, MEDTTIM CO2 .....
9 _ PAR ALTERNATE YEAR ANAI,YSIS, MEDITIM GAs, MtsDIIIM CO2 ................
I 0 - Sl ACKtrD RllrRl,Ml,Nl CASES
I1 _ PI,ANNING AND RISK MEDIT]M G^S, MEDITJM CO2 PVRR BY STUDY
PLANNING AND R]SK HIGH GAS, HIGH CO2 PVRR BY STT]DY.......
PLANNINC AND RTSK Low GAs, No CO2 PVRR BY STUDY ...........
REI-IABII,ITY ANAI,YSIS CATACTIY SHoRTFAI,t,s ......
ADDITIoNAL STACKED COAI, STI ]DIIS .............
REAI, LEVEI-IZED COSI. RANKINGS OF COAI, UNII.S...................,,,,.
MoDEL GRANLTLARITY CoST-DRIVER ADruSTMENT SIJMMARY
l8 - EARLY R-ETIR-LMLNl AssuMpTIoNs SITMMARY FoR ALI- RFl.tAElLrry CoAr STUDIES ..........
t?
l3
t4
t5
t6
l7
nt
PACTHCoRP - 20l9 lRP IABLL O[ CONTENTS
INnsx or Frc;unEs
FIGU RI. R. I _ REI,IABIT,I IY S I(IDII.S M I', IHoDoLoCY PROCLSS .
FI(iI]RE R.2 - C-42 AVI,RAGE ANMIAL REPLACIMENT REsot]RCE CAPACTI,Y AND LEVELIZED CoSTS
609
612
tv
PACtrrCoRp - 2019lRP APPENDD( M- CAS8 Iect Sxrsrs
AppsNorx M - Cess Sruov Facr Sspers
This appendix documents the 20'19 Integrated Resource Plan modeling assumptions used for the preferred
portfolio, initial portfolio-development cases, C-Cases, CP-Cases, No Gas and Energy Gateway Cases, and
Sensitivity Cases.
Case Fact Sheets Overview
271
Case Fact Sheets - Overview
Preferred Portfolio Facl Sheet
The Preferred Portfolio Fact Sheet summarizes key assumptions and portfolio results for the Preferred Portfolio
developed lor the 2019 Integrated Resource Plan (IRP).
Ouick Reference Guide
Initial Portfolio-Develooment Fact Sheels
The following Initial Portfolio-Development Fact Sheets summarize key assumptions and portfolio results for
each portfolio initially developed for the 2019 IRP.
214
P-45
CNW
No Devc Johnstd Wind
Option P.45CP 2 t,480 Base Bre Mcd Gas,
MedCo,Bus Scgmcnl f 2026
P-0t Co.l Study
Benchmark 24,401 Bare 20.'llMcd Cas,
Mcd COr
P-01 Rcgional Haze R€lercnce 2t,l9l Bas€MEd Gs6,
Mcd COr Segment F 20ll
P-0-1 RcgioD"l }Iszc I1,951 tsase B.se Mcd Gas.
Mcd Co1 Ba*S.gm€nt F l0:10
P-04 Coal Stuily C-42 21,720 Med GLs.
Med CO,Base S€8mmt F 202E
P-06 Cadsby Altcmllivc Casc 21,980 Base Med Gas,
Mcd Co1 2010
P-O7 Gadsby Ahemativc Case P-06 2t,905 tsase Scgment F :019Mcd cas,
Med COr
P-08 Naughton I Srmll 6ns P-0:l 2),979 Aas.Mld Gas,
Mcd Co?Scgment F 20-10
P-09 Nau8hion 3 LaiB. Gag 21.885 Base Base Mcd Gas,
Mcd CO'Segmenl F 2010
P- 10 Nrughlon 3 Lffgc Cas P41 2t,723 Med Ga,
Mcd CG,SeSmml F 2019
P-t I Cholla4 Retir€ment:020 P-09 21.871 Mcd Gu,
Med Co,Bax Segmenl l'1030
2t.E54Cholla,{ Relirem€nt 2025 Pi(,Base Med Gas.
Mcd CO:Scgm€tr1 f 2029
P,l.j Jim Bridger l&2 sCRs P-l I 22.346 20.12Med Gas,
Mcd COr B!se Sesment F
P- 14
Neughton 1&2 and Jim
Bridger l-4 R.tircm.nt
142
P-09 21.696 Bflse Ba*Med Gas,
Med Col S.gment F 2028
P- l5 Rclirc All Coal by 2030 Pl8 l2,t l2 Btrsr Mcd Gas,
Med CO,segrnmt F 1017
P- 16 Jim Bridger l&2
Rctircmcnt 2022. No CO?PO.l 18,634 Base Mcd cas,
No CO,2028
P- l7 High CO:P-15 Btrse Med cas,
I{iah CO:ScSment F :028
P.]E Social Cost ofCa$on P-15 30.022 Rase SCC CO:S€gment F 20:8
P- t9 I-o11 Gas P-{r.1 20.882 tsase S€gment F t0tJIrw cas,
Med CO:
P-20 High cas P-07 22.146 Hi8h Cas,
Mcd CO,Sc8ment F-2029
P-:8 Colstrip 3&4 R.lircmcnt
2025 P-l I 21,805 Base Med Gas,
Mcd Co:SeSmcrlt F l0l0
P-10 Naushton l&2
Retiremert 2022 P-l I 21.708 Bax M.d Gas,
McdCO,Scgment F 2029
Crse Delcrlpdoo
so
P!'RR
($E)
Lord Prtvrte
Gen COr Policy rols
1'Yer. ol
IbtrD.l
0uick Reference Guide
C.!e Descrlpdor Prra!a
Craa
so
PVRR
($m)
Lord Privrle Ger CO! Pollcy lOTs
!r Y..r of
New
Th.rb.l
Scgmctrt I
P-0-1
Brse
Case Fact Sheets - Overview
P-i r Naughlon l&2
Rctircment 2025 P-l I 21.652 Med Gas,
Med Co:thsc ScSmeflt F 2026
P-32
NNgbron l&2
Rctir€meDr 202J widr
Gadsby l-3 Retirernent
2032
P-07 2t,761 B.*Med 6as,
Med CO:t026
l,-.ll Jim Bndgcr l&2
RctireDmt 2022 P.I I ?l 895 Basc Mcd Gas,
Mcd COr Bas.ScSmmr F
P-.14
Jim Brids.r l&2
RcrirEmcot 2022, wirh
Gadsby t-3 R.tir.rncol
2O20)
P-l I 21.949 Base tsas.Scsmcd F 2028
Ji1n Bddgcrl&4
Retir€mcnt 2022 P-l I 21.732 Arse M€d Gaq,
Med COI Brsc Scgment t'2029
P-t5
Jim Bridgcr I Rctircmeot
2023 snd Jim Bri.rscr 2
R.lircmcnt 203 I P-lt Base Segmer F l0l6
P-.16 Jim Bridger 3&4
R.tircmenr 2025 P-.t I 2l,,1l9 Mcd Cas,
Mcd CO:Scgmcnl t :026
Jirn Bridsd I &2
Rctirement 202J, Jim
Bridger 3 Retircrnc
2028,.ndJim Brids.r 4
Relircmcnr 2012
P-31 2 t,418 Brsc EAce Med Gas.
Med Co:Scgment F 2026
P-54 Jim Bridge' 2 RctiEment
2024 P-ll 21,708 Bnsc Med Gas,
Med CO1 Das.2026
C-Cases ent Focl Sheets
The following C-Cases Portfolio-Development Fact Sheets summarize key assumptions and portfolio results for
each C-Case developed for the 20l9IRP.
275
P--11(Nnughton I & 2
Rctir€mcnl 202J P-l r 21,639 M.d Cas,
MedCOz Scgrncnt F 2026
P-36C
Jim BridScr l-2 ad
Nsughton l&2
Rctiremcnt 202J
P-46 2 t.544 Med Gas,
Med CO:Scgmcnt F 2026
P-.15('
JimBridgcrl&2
RetirEment 202.1 and
20-r8
P-.1r 21,537 Med Gll5,
Mcd CO,Segmcn( F 2026
P.46C JimBridgcr3&4
RclirEmcnt 2025 P-l I 2 r .4t I Dns.M.d Gas,
Med CO:2026
P-.r6 2I.185 Brse Med Gas,
Med CO:Basc Sc8menl F 2026P-46
J2.ta
JinBridscrl&4
R.lirErnmt 2023
JimBridgcrl&4
R€tircm.ot 20.15 P-45 2t,467 Med Cas.
Med Co:B3s.S€gm.nt F 1026
P-.15 1t,482 tsase Mcd cas.
MedCO?Sesmcnt F 2016P-48C JimBridger3&4
RetilerDEDl 2033
P.53C
Jim B.idgd I & 2
Rclirement 2o25. Jim
Bridger 3 Rctire ot
2028,.nd Jim Dridger 4
Retir€m.r[ 2032
P-lr 21.450 Base Med Gas,
McdCO:Ba*Sc8rrEdt F t026
P-51 B6c Mcd Gas,
Mcd CO,Basc Segmenl f t0t6P-51
J23C
JimBridgerl&2
RctirEineor 2021
P-54('Jim Bridgcr 2
Retir.ment 2024 P-5.1 21,591 Basc Mcd Gas,
Mcd Co1 Basc Segment F 2016
Scgmcnt F
2030
M.d Cas.
MedCO:
P-35
Mcd Gas.
Med Co:
P-53
Ouick Reference Guide
D€lcrtpdon Crie
so
P\T,R
($m1
Lord Priv.te
Cen CO' Policy FOTs
Tlerm.l
B.se
Scgrnent l-
P.47C
Case Fact Sheets - Overview
C P-Cases Portfolio-Develoomenl Fact Sheets
The following CP-Cases Portfolio-Development Fact Sheets summarize key assumptions and portfolio results
for each CP-Case developed for the 2019 IRP.
No Gas &. Enerw Galewav Fact Sheets
The following Fact Sheets summarize key assumptions and portfolio results for each No Gas and Energy
Gateway Case developed for the 2019 IRP.
Ouick Reference Guide
276
P-l6CP
,im Brid8cr l-2 and
Naughtor l -2
RelirEment 2025
P-46 l:,553 Basc M€d cas.
Med Co:Scgment t 1026
P-45CP
Jim Bridgcr l-2
Retircmcnt 2023 rnd
2038
P-lt 21.480 Base Med Gas.
Mcd CO:Br\c Scgrnent F :026
P.46CP JimBridgerl&4
RetircnEnt 2025 P.]I 21.440 Mcd Gas,
Mcd CO?Ba*-S€gmetrr F :0:6
P.46CP
J23C
Jim Bridger .l & 4
Rcliremcr 202l P-46 2t,402 Basc Med Cas,
Med Co?Scgmenl F 2026
P-47CP JimBridserl&4
Retircment 20.15 P-,15 2 r,469 Basc Med Gas,
Mcd COl Scement I 2026
JimBridger3&4
Rc.ircmcnt 20ll P-45 21.457 Bas.Mcd cas,
Mcd CO:Brsc Scgrnent F t0l6
P.5]CP
JimBridgerl&2
Retircmcnt 2025. Jirn
B;dger 3 Retircmcol
2028, snd Jim Bridger 4
RetiEment 2032
P-il 21.479 M€d Cas.
Mcd COI Scgmenl Il 2026
P-45Cl.Iw, No Ncw Gas
Optiotr P-45( NW 2t,798 tlrsc Base Mcd Gas,
Med CO?Basc Segmtrl F
P-lsCNW. No Ncw Gas
Oplion Eilh punpcd P-.l5CN'rv 2t.970 Bas€Mcd Cas,
Med Cq Base SeSmml F
P-22 EDcfg], Galc{,ay S€gnEnt
D.3 P-.15( NW 21.886 B.se Mcd cas,
M€d COr Burc Add SegnEnt
D.3 t0l0
P-21 Energy Gateway S.gmeDt
D.l sad F
p-.r5cNw 22,t 5t Mcd Cas,
Med Co:
Add Segments
I ud D.l t0l6
P-?5 Energy Cateway Scgmcnt
D,3,E&H P-.t5CN1V Uase Basc I{ed C.s.
Mcd (():
Add Sesmenrs
D.3. Segmcd
E. ard II
2030
P-26 En6$' C,llewsy SeErEnt
H T'.J5CNW 2\.579 Bi{c Med Gas,
M€d COI
Add S.gm€nl
II 1028
0uick Reference Guide
Clse I!.!crlpdon Prrclt
Crse
SO
P}'TR
(sm)
Lo!d Pdvrte
Cctr (O! Policy fOTg Cat€E'ry
l'Yerr of
Tf,crnul
P-48CP
Cosa De!cripdoo PrrGnt
Ct;e
SO
PVRR
($o;
Load Prlv!.e Gen Co: Policy FOTs Grterrry
l{ Ye.r of
Th.rE l
P-29
P-29
PS
C.e D€lcription Pr.erl
Crre
SO
PlRR
($m;
Lord Pritrre
Ger COr Po[cy FOTi
t'Ya.of
Tbcr&.I
Case Fact Sheets - Overview
Se nsitivitv Fact S heels
The following Sensitivity Fact Sheets summarize key assumptions and portfolio results for each sensitivity
being developed for the 2019 lRP.
0uick Refcrence Guide
271
s-0t P-.t5( NW 10.61r Los Barc l0l0
s-{rl I lish Load P-45('NW 22,601 llish Bnsc 2tt:6
s-0-1 I in 20 Load Crowth P-45( NW 21.6-',1.t I in 2t)Bas€Basc 2026
s-0.1 ln$ Private Ge eration P-4J( NW 2 t.758 Base Base B.1sc 102<)
s-o5 lligh Pivate GenelElion P-45('NW 21,17t Ilase HiCh Basc Bas t0l0
s.06 Business Plan P-4J( NW I1.695 BL!c Basc 2028
s-07 No ( ustome' Prcfercnce P-45('NW I t.609 Aase Brse 20.t0
2t.6t6 Basc :0.10s-08 High CEtomcr P-.r5CN\V
Dcacrtpdon Pal?rt
Crle
so
Pl'RR
(tm)
l-oad Gen CO, Poliq ro'r3 Gstcw.y
r'Ye!! of
Th.rmd
Portfolio: Preferred Portfolio (P-45CNW)
PORTFoLIo ASSUMPTIoNS
Retire m e nt A s su mt tio ns
P-45CNW is the Prefened Portfolio case, aDd thc retirement
assumptions are summarized in the lblkrwing table.
Desciotion
The preferred portfolio, P-45CNW, is a variant of P-45CP with
all of the ssme assumptions and Planning and Risk
Dctcrministic methodology applied except 620 MW Dave
Johnston Wind in 2029 is removed.
I'nk l)cs{riDtion
Cholla {Retire :020
Colstrip l R.rire 2027
Colstrip 4 Reti.c 2027
Craiq I Rctire 2025
Crais 2 R€rire 2026
Dal'c ,ohnston I Retire 2017
Davc Johnston 2 Rcliic:017
Dave Johnston l Retire 2027
Dave Johnston 4 Retire:027
cadsby I Retire 2031
Gadsby 2 Rehre 2031
Gadsby 3 Retrre 20ll
Ilaydcn I R€(irc 2030
tlayden 2 Rctire 2030
llunter I Retire l04l
Hunrer 2 Retire 2043
Hunrcr l Retire:042
Huntinalotr I Retire 2016
Rctire 2036
Jim Bridscr I Reti.e 202.1
Jim BridaBr 2 Retire 2028
Jim Bridqer l Retire 2017
Jim Bridser 4 Retire 2017
Naushton I REtirc 2025
REtirc 2025
Naushl('n l Retire 2019
Retire 2039
PORTFOLIO SUMMARY
System Ootimizer PVRR 6m) $21.480
Resoarce Porlfolio
Cumulative changes to the resourcc portfolio (new resource
additions to address load scrvice and reliability requirements
antl resource retirements), represented as cumulative nameplate
capacity, are summarizcd in the figure below.
Cumulative Nameplate Capacity
illllllll't --..'llll
.sd.'ddS.ddd dC.dddddd"dd d
DesciDlion fear Copaciq*
Aeohts W|oming to Ukth S 2024 1,700
(ioshen to I hoh N 2030 800
Yakima- to S. Oreson/Califomia :0.16 150
Preferred Portfolio Fact Sheet
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Portfolio: Coal Study Benchmark (P-01)
PoRTFoLIo ASSUMPTIONS
Ret ire m e nl A s su mo tio n s
Initial portfolio-development case P-01 is the coal study case,
and the rctircment assumptions are summarized in the
ttrllowing table.
Descriorton
P-01 serves as the benchmark portfolio to which the other Initial
Portfolio-l)evelopment cases can be compared b detemine
their relative benefits or costs. It assumcs scrubbers are added
to Jim Bridger Udt I in 2022 &Ulit2ir,202l.
I-nit Dcs.riDiion
Rcdrc 2020
Rctire 2046
Colnrip.l Rclirc.2046
CEis I Rel;c 1025
Craig 2 Rehre lol.l
Dave Johnslod I Rctire 2027
Dave Johflston 2 Retir. l0l7
Da!e Johnstofl:l Rctirc 2027
Dare Johnslon 4 Retirc 2027
Gadsby I Rctirc 2012
Gadsby l
Gadsbr, l Retir€ 2012
Ilryden I Retir€:010
Retirc 2030
IImler I Relire:U4l
Humer 2 Retire 2041
Hume. l Relirc 20.11
Hutinston I Rclirc 1036
Huntin,iton 2 Retir.1036
SCR 2022 & Retire 2037
Jim Bridstr 2 sCR 2021 & Relte 2037
Retirc l0-'i7
Jim Bridqcr,l Retirc 2037
Naushton I Retire :029
Naughton 2 Retirc 2029
Naughton l Retirc 2019
Rerir. l0l9
PoR LI NIARY
Swlem Oolimizer PVRR (Sm)$23,191
Resource Po folio
Cumulative changes to thc rcsource ponfolio (new resource
additions to address load service and reliability requirements
and resource retiremcnts), rcpresented as cumulative namcplatc
capacity, are summarized in the tigure below.
Cumulative Nameplate Capacity
]2
z ililillllll" -rrrl
""e
d +',e d "d| C.f,".d +"' d d d d !+ d.rd d d ++
.^4.'!'t..6,0rI
280
Desciplion Year Canocitt
Aeolus Wyoming to lJtah S 2024 I ,700
Go.shen - to Utoh N 2030 800
llolla llalla- to Yakimu 203 2 200
Yqkima- to S. Oregon/California 2037 450
lnitial Fact Sheets
SCR : sclcctiye catalyic reduction
R€tirc 2032 I
lcr'"tt,.r
I cot't'ip I
E"v4r4 ,
Jim B.i4,.cr I
Jim Bridg.. 3
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f
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El-trnrnFO El?aaln|.d',lmi€+v9l x n tr | i ql
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";i;=: ;ii=;::;;:r; :E>tcr o €, rn 6 ;16rro.n6oaFtio - c
lll I n !r r tr 1l rr rr :;EI---hF !l .| 6 !t ca .o .o N ^ F F @ = 5;188833 8193933333333 ;s
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Portfolio: Regional Haze Reference (P-02)
PORTFOLIO ASSUMPTIONS
Retiremenl Assumptbns
Initial portlblio-developmcnt case P-02 is the regional haze
rcl'crences case. and lhe reliremeol assumplions arc
summarized in the lbllowing table.
Descriolion
Case P-02 is thc Rcgional Haze Reference case which adds
scrubbers between 2021 a]od 2021 to Huntcr []nits I & 2 and
Iluntington t,nits I & 2, in addition to the scrubbers in the base
casc [or Jim Bridger Units I & 2, followed by each unit's
expected retirement date. Itr addition, it retircs Cholla (Jnit 4 in
2025 instcad o12020 in thc base case, Colstrip Units 3 & 4 in
2027 instcad of2046 and Craig Unit 2 in 2026 instead of 2034.
Unit
abotla I
Colstrip i
Craig 2 R.lire l0:6
Rctirc l0:7
Dale Johnston 2 Rclirc 2027
Dave Johnstofl 3 Rctir.2027
Rctire 2027
Gldsb) l Rctire 2012
Gadsb) l Rctirc 2O32
Cadsby 3
Hayden t Retir€ 2030
Hrr"den 2 Rcrire 2030
HuntLr I
IILnld l SCR 2022 Retire 2042
Hunter 3
Huntinslon I SCR 2022 Rctirc 2036
Huntingtor 2 S( R 2023 Relir 2036
Jiln BridEer I
Jnn Bridscr l
Jim Brideer l
Jim Bridcer 4
Nsushton I
Rctire 2029
Rctirc 2019
Incrementol
Resource Porlfolio
Cumulativc changes to the resource portfolio ([ew resource
additions to address load service and reliability requircmcnts
and rcyrurcc rctircments), represented as nameplate capacity,
are summarized in the hgure below.SCR = selective catalytic reduction
Cumulative Nameplate Capacity
;:I,
E ruilililllll
Iil
lto rrrrl
r" dCPC d ddd ddddde'd.p'd d d
.i,Edrbi...l.l!il
282
I)cscriolion Year Canscitv
leolu.v WY to Utah S, Erpansion 2024 1,700
Goshen - lo Utah N, Expansion 2030 800
Wolla Walla to Yakima, Ewansion 2032 200
Yakimo - lo - S. Orego,t/Califomia 2037 450
Initial Portfolio-Develonment Fact Sheets
PORTFOLIo SUMMARY
Swtem 0otimizer PVRR 6d $23.191
Rcrirc 1025
RctirE 2027ffi
I Crarg I I Rctir. 2025
Retirc 2ol2
S( R:02.1 RcliE )042
Rchrc 2042
ffi
st R rrrrt R.ri* )otr I
Prh.. rnlr Iffi
Rcxrc 2019 I
SCR 2024 Retire 2039
Narehron t
I
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t
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=
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Portfolio: Regional Haze Intertemporal (P-03)
PORTFOLIO ASSUMPTIONS
Descriolbn
Similar to P-02, P-03 has all ofthe same retLement dates
without the addition ofthe scrubbers on Huntcr Units I & 2,
Huntington trnils I & 2 and Jim Bridger Units I & 2.
Retir e m e nt A s su m p t i o ns
Initial portfolio-developmcnt case P-03 is the regional haze
intenemporal casr. and the rellremenl assumpti()ns arc
sunrmarized in the lbllowing tablc.
PoRTFoLro Suprilrenv
t'nir
Cholla 4 Rclirc 20?5
R€tirs 2027
Retirc 2027
Rcrirc 2025
Crais l Rcrirc 1026
Dave Johrslon I Rclirc 2027
Dale John(on 2 Rctirc 2027
Dave Johnston 4 Retir€ 1027
Rclird l0ll
cadsby 2 Rctirc 20ll
Retirc 20:12
Rctirc 2010
Reiire 2010
Rctirc 2o42
Ih,nler 2 Rctirc 2042
Rctirc 2m2
Ilunliflsto l Rclnc l0-16
Huntingtor :Retire 20:16
Jim Bridser I Retirc 2028
Jim Bridser 2
Jim Bridser 3 Rctire 2017
Jim Brirlccr.l Rctirc 2017
Nrushton I
Nsushton 2
Nauehton l
Rurir.1039
Stslem Optimizer PV'RR (Sm)$21,95 t
Resource Porlfolio
Cumulative changes to the resource portlblio (new revrurce
additions to addre'ss load scrvicc and rcliability requirements
and rcsource rctirements), represented as nameplate capacity,
are sur narized itr the tigure below.
AllRe$urces
ilnrrllllllllo rrrll
C d dppd.d "'o" d d d Pd'dd C d dd.d
..aJ!d..o.,Gx
284
Descrjfuion l'eur (nDocitt'
Aeohts W - lo Utah S, Etpansion 2024 I,700
2030Goshen - to Utah N, Expansion 800
llalla llalla to Yakima, Expansion 2031 200
Yokima to S. Oregon/(-alifomia 20J7 450
Initial Portfolio-Development Fact Sheets
':!
E
m
I Rctic2o29 I
I R.riE 2029 I
lRctirc2olg I
Wyodat
Gadsby I
Hunter l
t (bl"r'i' 3
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Portfolio: Coal Study C-42 (P-04)
PORTFoLIo ASSUMPTIoNS
Retiremml Assamnlions
Initial portfolio-development case P-04 is P-01 with Jim
Brir]ger Units t & 2 and Naughton Units I & 2 retiring in 2022.
Full retircment assumptions are summarized in the lbllowing
table.I)escinthn
Similar lo the P-01 benchnrark. P-04 has the same retirement
assumptions except Jim Bridger Units I & 2 retire in 2022
irstead of2037 and Naughton Units I & 2 also retire in 2022
instead of 2029. In addition, no units have scrubbers added.
Ihla Descriptiotr
Cholla,l Rctirc 2020
Crais 2 R€lire:034
R€tirc l0l7
Dave Johnston 2 Rctirc 2027
Da!e Johnston 3 Rctirc 2027
Dave rohnston 4 Rcrire 2027
cadsby I
cadsby 2
Cadsbv.l
Il.ydefl I Rclirc 2010
IIaydo I Relirc 1030
Hunter I
Hunrer l
tluDtinqton I Rctirc 20:16
Ilunrinsron 2 Retirc 2016
Jim Bridser I
Jim Bridser 2 R€tiE 2022
Jinr Bridg€r l Reiire 2037
Jim Bridger.l Rctirc 2017
Nauahlon I Rctirc 202:
Naushton 2 Rert.1022
Rctirc 2019
Rctirc 20-39
PORTFOLI Sumlreay
Svslem O imipr PVRR (Sml $2 t,720
Trsnsmixion
Resource Po folio
Cumulative changes to the resource portlblio (new resource
additions to address load service and reliability requirements
and resoulce retirements), represented as nameplate capacity,
arc summarizcd in the figurc bclow.
(2.!aot
ilrrlllilllilil--rrhrrilllllllI
.e' .d .p'd"o'Cd d d P.d CPdPdCC tr' d
.'tg.b'.-,8
Desciolion Year Caoucilt'
Aeohts W to {hah S, Etpansion 2021 t,700
Goshen - to - Utah N, Erwnsion 2010 800
Wdllq lYalla - to Yakima, Expansion 20J I 200
Yakimo to S. Oregot/Califomia 2037 450
Initial Portfolio-Development Fact Sheets
I c"xr.in: I Rcri..2M(' I
I c"t.tri" a I Rer'r.2046 I
ftrarg t l Rcrire 2025 I
ffiry
Rcrirc 2032
RdiF 1ll,,
R€iir.2042
I Hunter 3 I Rctnc 2042
Rclirc 2022
I wyodak
286
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Portfolio: Gadsby Alternative Case (P-06)
PORTFOLIO ASSUMPTIoNS
Retirem ent A ssumotion s
Initial portfolio-developmenl case P{6 is Gadsby trnits l-3
altcrnative retircmcnls. Full retiremcnl assumptions arc
sumrnarized in the following table.
Descriotion
Sirnilar to P-04, P-06 has the samc rctircment assumptions
except Colstrip Units 3 & 4 rctire earlier in 2027 instead of
2047, Craig tlnit 2 rctires in 2025 instead of2034, and Gadsby
Units l-3 rctire in 20?0 insread of 2032. In addition. Jim
Bridger Unit 2 retires later, in 2032 instead ol'2022 and
Naughton trnils I & 2 retire in 2029 instead of 2022.
Meanwhilc, Naughton 3 undergoes a larger gas converuion in
2020 followed by retirement in 2029.
I nil
Cholla 4 Rel;rc 2020
Colsrrip.l Relirc 1027
Colslrip,t Retir. 2027
Retirc 2025
Retirc :0:5
Davc Johnston I Retirc 2027
R<rir.l0l7
Retire 2027
R€lirc 2010
G.(l{hr 3 Retirc 2020
Haydcn 2
Reli.. 204:
Hunrcr 2 Relirc 2042
Iluntcr l R.tir. ?042
tluntin8ton I R(tir€ 201]6
Huntrnston 2 Relirc:0.16
Retire 2022
Jim tsridser 2 Rclire 2012
Jim Bridser 3 R{tire 1037
Jim Bridgcr 4 Retirc 2017
Naurhl(nr I
Naushlon 2
Rcrirc 2039
Resource Poftfolio
Cumulative changes to the resource portlblio ([ew resowce
additions to address load service and reliability requirements
and resource rctirements), represented as nameplate capacity,
are summarized in the figure below.
GC = gas conveniion
AllResourcei
;x
i ,H --.,:fitil!!!lll
,!d''.e.d.d"dd p' d d d d d rsld d "d"d..4d "d
.ria./!&-.o..,o5r.
288
Descriolion Year Capacity
Aeoltrs 141 to tlkth S, Expufision 2024 1,700
Goshen - to (ltah N, Ettpansion 2030 800
lValla Walla - to Yahma, Exponsion 20Jt ]00
Yakima b S. Oragon/Califomia 2038 450
Initial Fact Sheets
PORTFOLIo SUMMARY
Svslem Optimizer PVRR 6d $21.9E0
De.criptior
Rctire 2027 l
Retire 20't0**.*-
I RctL.e l0:9
I Renr. :lo)q
I I 8. G( :020 Rcr'E l0:9 ]
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Retire m e nt A s s u m otio n s
Initial portfolio-development casc P-07 is P-06 with Jim
Bridger Unit 2 retiring in 2028. Full retirement assumptions are
summarized in the following table.
PORTFOLIO SUMMARY
I'nl.D($ription
Rctirc 2020
Retire 2027
Rcrirc 2025
Rcrirc 2025
Da\ e Johnston I Rcrirc ?0?7
R€rire 2027
Retire 2017
D{!e Johnston 4 R€lir.2027
(;adsby I Rclirc 2020
Gadsby 2 ReIire 20:0
Gadsby -l Rclire 2020
Retrre 2010
I Iryden 2 Retire 2010
Hurtcr 2
Rctire 2042
Ilunlinslon 2
Jirn Brideer I Relirc 2022
Jim Bridser 2
Jnn Bridcer l
Jill' Bridser 4
Naushton 2 R.lire 2029
N,rughton -3
Rerire 2019
System Oplimizer PVRR ($n)$21,905
Resource Porlfoho
Cumulativc changes to the resource portl'olio (new resouce
additions to address load servicc and reliability requirements
and resource r€tirements), rL?resented as nameplate capacity,
arc summarized in the tigure below.
GC = ga-s conversion
i:
2 :t --..rllll nIlliiirllllI
d d ,P.S d d ddd e'' 'r,e'd.d d "d".r"d dt
..e.,'i..610.1
290
Descriotion Yeor cupsli8
Aeolus WY - to Utah S, L\pansion 2024 1,700
Goshen - lo - Utah N, Exponsion 20J0
Ittalla lValla to Yakimd, Expansion 203 2 200
Yakimo - to S. Oregon/Califonia 2038 450
Portfolio: Gadsby Alternative Case (P-07)
Initial Portfolio-Development Fact Sheets
PoRTFoLIo ASSUMPTIONS
Descriotion
A variant ofcase P-06, P-07 has all of the same retiremenl
assumptions as well as gas conversion plans but tcsts
rctircment ofJim Bridger tlnit 2 in 202ti.
800
I Sel!!!pj .! 202:1 l
Hrorc' r fn.rir. ZOqZr
I Hunringron I I Rcrire 2036 I
Rerire 2036 I
ffiffi
R€tire 20.'17
Naushrq! I I Rclnc2o29
f-g. CC ZoZo nd* :o:q
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lD . ttE$e4.l
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Portfolio: Naughton 3 Small Gas Conversion (P-08)
PORTFOLIO ASSUMPTIoNS
Retircment Assumotions
Initial portt'olio-tlcvelopment case P-0tt is P-03 with Naughton
Unit 3 undergoing small gas convcniion in 2020. Full rctircment
assumptions are summariz.ed in the lbllowing table.
Descriolion
A variant ofcase P-03, P-08 has all of the same retLement
assumptions except tests a small gas conversion on Naughton
Unit 3 in 2022 with rctirement still lbllowcd in 2029.
I Dit Desc.lption
Cholla 4 Retire 2015
Colstrip l Relirc 2027
Colstrip 4 Relirc 2027
CmiE I Rerire 2025
Cmis 2 Relirc 2026
Davc Johnston I Retirc 2027
Dave Johnston 2 Rctirc 2027
Rclirc:027
Davc Johnston 4 Retirc:ol7
Gadsby I R.rnc 2032
Cadsby 2 Relire 2012
(iedsbv :]Retir. 2032
Havdm I
Haydcn 2 Rel;rc 20-10
HuntDr I R€lirc 20.12
Huoter l Rerie 2042
Hunrer -l Retirc 2012
Huntinsron I Retire 2016
Huotirslon 2 Retir.20l6
Jim Bridscr I Retirc 2028
Jim Dridaer 2 Reiirc 2012
Jim Drid,cer 3 Retirc 20.17
Jim Bridser 4 RetirE 2017
Naurhron I Rclirc 2029
Nauqhlon:Rctii.:029
Naushton l Sm. CC 2020 Rcrirc 2029
Retirc 20-]9
es
Resource Po foho
Cumulative chalges to the resource portlblio (new resouce
additions to address load seryicc and reliability requtemcnts
and resource retirements), rcpresented as nameplatc capacity,
are summarized in the ligre below-
.rilrlllliiitltilu
(iC = gas conversion
i'ffi
E l{ -.."11ll
+e d p'd p' C dp.d dd dd,s.e. "d
d d
"d "d.ftl{..
.^,Ed5E r .brorl
I)escriptiut Canacih,
Aeolus W - to UtahS, Expansion 2024 1,700
Goshen - lo Utah N, Lxpansion 2030 800
llqlla Wolla to Yokima, Expansion 203 2 t00
Ydhn a lo - S. Oregon/Califomia 2038 450
292
Initial Fact Sheets
Retir. 2030
PORTFOLIO SUMMARY
System Ontimizet PVRR ($nl $21,979
Year
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Portfolio: Naughton 3 Large Gas Conversion (P-09)
PORTFoLIo ASSUMPTI0NS
Retir e m e n t A s su molio ns
Initial portlblio-developmcnt case P-09 is P-03 with Naughton
Unit 3 undergoing large gas conversion in 2020. Full retirement
assumptions are summarizcd in the following table.
Descrintion
A variant ofcase P-03, P-09 has all of lhe same retirement
assumptfuns cxcept tests a lffge gas convcrsion on Naughton
Unit 3 in 2022 with retirement still lirllowed in 2029.
tltir
Cholla 4 Retire 2025
Colst'ip -l Relirc 2027
Colstrip.l Rerir.20l7
( raig I R.tir.2025
Craie :Retire:026
Reti..20:7
I)avc Johnslon 2 Rrrir.2027
Drvc Johnslon 3 R€lirc 2027
Dnve John.lon 4 R€lire 2027
Gadsby I Retir.1032
Gadsby 2 Rctir.l0l2
Gadsby l Rdir.20.]2
Haydcn I Rctirc 2010
Ilayden 2 Retire 20:10
Ilunter I Retirc 2042
Hunter :Rctire 2042
Hunter l Rctirc 2042
Hunlinglon I Rerirc 2036
lluntinston 2 R€hr€ 20.16
Jim Bridscr l Rernc 2028
Jim Bridqcr:Rerirc 2032
Jrm Bridacr .l Retir.20l7
Jim Bridger.l Retir.:037
Nauqhton I R€lirc 2029
Nauchlon 2 Rctirc 2029
Ls. GC 2020 Retirc 2029
R€tirc 2039
TF LI MMARY
Svstem Oolimizer PVRR (Sml $21.885
rodes
Resoarce Porlfolio
Cumulativc changes to the resource portlblio (new resowce
additiotrs to address load servicc and reliability requirements
and resource retiremcnts), represented as nameplatc capacity,
are summarized in the tigure below.
(iC : gas conversion
o -rrfl ,..,fiillli
d'""dP{+f'dri*'d,+'+''drP{'dit*d'd{,++d.d
294
Descriplion Year Cooacin'
Aeolus llY to Lltdh S, l\pansio 2024 1,700
Goshen to Utah N, kwnsion 2030 800
Walla l{alla to Yakimq, Expansion 2031 200
Yokima to S. Oregon/Califomio 20J6
Initial Portfolio-Development Fact Sheets
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Portfolio: Naughton 3 Large Gas Conversion (P-10)
PORTFOLIO ASSUMPTIoNS
Descriolion
A variant ofcase P-04, P-10 has all ofthe same retirement
assumptions except tcsts a large gas conversion on Naughton
tJnit 3 in 2020 with retirement still followed in 2029.
Retbement AssumDtions
Initial ponfolio-dcvelopment case P-10 is P-04 with Naughton
IInit 3 undergoing large gas conveniion in 2020. lull retirement
assumptions are summarized in the folkrwing table.
I'oit Dercrintion
Rctire 2020
Rclire 2046
Colstrip 4 Rclire 2046
Crais I Rerirc 2025
Crais 2 Rctirc 20-14
Rctir€ 2027
Davc Johnston 2 Rctire 2027
Date Johnston l Rctirc 2027
Rrrrrc 2017
cadsby 3 Retire 2031
Ilaldcn I Rcli,c 2010
llryden 2 Relirc l0l0
Ilunlcr I Rctirc 2042
Hunter 2 R€lire 2042
Hunrer l
Hunlinqton I Rerire 2036
lluntinaton 2 Rclirc 20-16
Jim Brid8er I Relirc 2012
Jim Bridser 2 Rclirc 2022
Jim Brid,{er 3 Rctirc 2037
Jim Bridger 4 Retirc 2037
Rctirc 2022
Nau,ahton 2 R.tire 2022
I.a. GC 2020 Rctire 2029
Rctire 2019
lql Transmission
Resource Portfolio
Cumulative changes to the resource grrtfolio (new resource
additions to address load service and reliability requirements
and res{rurce retiremenis), represented as mmcplate capacity,
are summarizcd in the ligure below.
ffill
(iC = gas conversion
E ; --.+!EI
eedd{ld d"d.dd.dfrdp.ddd.d.dc d
Descriplion Year Cqtacitv
Aeolus W to - Ulah S, Expansion 2024 1,700
Goshen to lhah N, Lxpqnsion 2030
lfallo ll'alla to Ycrkirnt, L,xponsion 2032 200
Yokima to S. Oregon/Califomia 2035 450
Initial Portfolio-Develonment Fact Sheets
PORTFOLIO SUMMARY
Svstem Ootimizer PVRR $d 521.723
.,qirdi..onroll
800
Rctire 2032 I
cadsbv 2 l nct'r.ZOr:
R.lire 2042
G.d"b" t -----
I Naushton I
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Portfolio: Cholla 4 Retirement 2020 e-f f )
PORTFOLIO ASSUMPTIONS
Descriolion
A variant ofcase P-09, P-l I has all ofths same retirement
assumptions except tests retirement of Cholla tJnit 4 in 2020
instead o12025.
R etire m e nl A ss u m o I io ns
Initial 6rrtfolio-development case P-ll is P-09 with Chollallrit 4 retirement accelerated to 2020. Full retirement
assumptions are summarized in the tbllowing table.
Ponrror,Io Sulrlreny
Svslem Ootimizer PVRR (8m)s21,873
trDit Desaripttob
Cholh {Rctir€ 2030
( olsr;n 3 R.t'r.l0l?
( olstrip .t Relire 2027
Crais I Reiire 2025
Crais 2 Rclire 2026
Da\ c Johnslon I Rctire 2027
Dav€ Johnston 2 Rctire 2027
Dave Johnston .l Relire 2027
Rcrire 2Ol7
G.rdsby I Rctire 2032
Cadsby 2 Rciire 2032
Gadsby l Rclne 2012
Havden I Rclire 20-10
HaydcD 2 R€lire 2010
Hunler I Retire 2(X2
Ilunrcr l Rctire 20,1:
I Iuntcr 3 Rctire 2042
Iluntinston I Rctire 2036
HuDtinaton 2 Rctire 2016
lim Bridger I R€lirc 2028
Jim Bridaer 2 Rclire 20-12
,im Bridaer 3 Rctire 2017
Jirn Bridser 4 Rctir€:017
Naushton I Rctire 2029
NauEht(,n l Retire 2029
Nauehton 3 La. CC 2020 Relirc 2029
Retire 2019
Resource Porlfolio
Cumulative changes to the rcsource pontblio (new resource
additions to address load scrvice and reliability requiremcnts
and resource retiremcnts), r€presented as nameplate capacity,
are summarized in the figure below.
AllResourc6
GC = gas conversion
]
!
a
" -rrll rraIII
d,dCd.dd.dnddddd,.o',d,"sdddd.d
.r'4dCci..o-rErr
29{l
Descriolion Year Capolitl
Aeohrs W - to - Lllah S, lipanion 2024 1,700
Goshen to Utah N, Exponsion 2030 800
203 tWolla Walla to Yqkima, Expansion 200
Yakinn to S. Oregon/(it lifo m kt 2036 450
Initial Fact Sheets
r
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Portfolio: Cholla 4 Retirement 2025 (P-12)
PoRTFOLIO ASSUMPTIoNS
Desciotion
A variant olcase P-06, P- l2 has all ol'the salne retircmeot
assumptiom exccpt tests a Cholla Uuit 4 retircment in 2025
instead of2020.
Retiremerrl Assa mplio nE
lnitial porttbliodevelopmcnt case P-12 is P-06 with Cholla
Unit 4 retrring in 2025. Full rellcment assunrptioDs are
summarized in the following table.
Ihit D(srrlptlon
( holh 4 Retirc 2015
Colsrrip 3 Relirc 2017
Coistrip.l Retirc 2027
Crris I Retir€ 2015
Crais :Retirc 2025
Davc Jolnslon I Retirc 2027
Davc Johslon 2 Rc&e 2027
Davc Johnston l Retirc 2027
Retire 1027
cldsby I Retire 2020
cadsby 2 Retirc 2020
Gadsby 3 Retire 2020
I lavdc, I Rerirc 2010
llavdcD 2 Retire 2010
Ilunlcr I Retirc 2(x2
Hunrrr 2 Rcrire 2042
Hunler l Rctirc 2042
Hunlington I Retirc 2036
lluntiflqtofl 2 Rerire 20-'16
Jim Bridser I Retirc 2022
JiE Bridser 2 Relirc 2032
Jim Bridser l Retirc 2037
Jim tsnd,.cr 4 Relire 20-u
Naughtod I Rctire 2029
Retire 2029
Naushlotr 3 Ls. C,C 2020 R€lirE 2029
Retire 2039
Incremenlol
Resource Porlfolio
Cumulative changes to the rcsource portlirlio (new revrurce
additiotrs t() address load service and reliability requirements
and rcsource retirements), representcd as nameplatc capacity,
are summarized in the figure below.
GC : gas conversion
i:
,'t --'.rllll rrffiilliiril1ilil
!
+e d.rdddlddd.d.dd,6ii+.d d.d,f, d d.:-
r^ad$o.3..cr-rolrr
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Descriolion Year Clpgcitt'
Aeolus W to - Lhah S, E:rpansion 2024 1,700
Goshen - to lllah N, Erpdlsion
lValh llalla lo Yakima, Expansion 2032 200
Yo6ma to - S. Oregon/Califomia 2037 450
Initial Portfolio-Development Fact Sheets
PoRTFoLIo SUMMARY
Svstem Ootimizer PVRR ($ml $21.854
2030 800
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Portfolio: Jim Bridger I & 2 SCRS (P-13)
R elireme nl Assu mptio ns
Initial portfolio-development case P-13 is P-ll with Jim
tlridger Units I & 2 converting to SCRs. Full rctirement
assumptions are summarized in thc [ollowing tablc.
PORTFOLIo SUMMARY
l tria De$riplion
('holla I Rerirc 20:0
( otstrip l R€tirc 2027
('olstriD 4 Retire l0:7
Craig I Retire 2025
Craig 2 Retire 1026
Drve Johnston I Relirc 2027
Davc .rohflston 2 R€rire l0l7
Relire 20?7
Rerire 2027
Cadsby I Retire 2032
Relire 20-12
R€lirc l0ll2
HavdeD I Relire l0l0
Havden l Retire 2030
Hurrer I Retire 2041
Iluorer:Retire 2M2
Iluder l Rctire 2042
lhmtrnxhn I Reti.c loi6
Hunnnator 2 Retire:016
J;n Bridscr I Retire 2017
Jim Brids.r 2 Retire 2{)17
Jin Bridser 3 Rclire 2037
Jin Bridscr 4 Rctire 2017
Relire 2029
Retirc:019
Nrushton -l Le. CC 1020 RetirE:029
Reiirc 2039
Swle,n ODtimizer P|'RR (Sml s22,346
Trsnsmission
Resource Po folio
Cumulative changes to the resource portfolio (new resource
additions to addrcss load service and reliability requiremcuts
and resource rethements), represetrted as nameplate capacity,
are summarized in the figure below.
AllResources GC' = gas conversion
;:!
-I ililriilll
til
I" -rII!
.s"Cdd.d "e''ddd.ddC Pde'd"d dC d
DescriDlion l'eor ('apacilt
Aeolus W to lhah S, Expansion 2024 1,700
Go.rhen - to - Utoh N, Erpansion 20J0 800
Wolla llalla to Y.tkima, Erpansion 2031 200
Yakimq - ro S. Oreson/(alifomia 203 7 450
Initial Portfolio-Development Fact Sheets
PORTFOLIO ASSUMPTIONS
Dessiotion
A variant ofcasc P-l l, P-13 has all of the same retiremcnt
assumptions except tests thc addition ofscrubbers to Jim
Itridger Unit I in 2022 followed by retirement in 2037 instcad
of2028, and Jim tlridger Unit 2 in 2022 followed by
rctircment in 2037 instead ol-2032.
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Gadrby 2
I N"*ht"" I J
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PoRTFoLro AssuilrPTro\s
Descriofion
A varianl ofcase P-09. P-14 has all ofthe sane retircmcnt
assumptions except retires Cholla in 2020 instead of2025. all
Jim Bridger Units in 2022 instead oftlnit I in 2028, tlnit 2 in
2032 and Units 3 & 4 in 2017 . [n addition, it rctircs Naughton
Units I & 2 in 2022 instead o12029.
PoRTFoLIo SUMMARY
System Ootimizer PVRR ($m) 521.696
Resouce Portfolio
Cumulative changes to thc resource portfolio (new resource
additions to address load service and reliability requirements
and resource rettements), represeoted as nameplate capacity,
are summarized in the ligure below.
Cumulative Nameplate Capacity
ffi
! ,--...,ffirr!!!ll!lli
.rti.t
.n'ira'.-t.orlrrgra
304
Descriplion Cupacin,
2024 I,700Aeolus W - to - Utah S, Expansion
Goshen to Ulah N, Expdnsion 20J0 800
Walla Walla to Yakima, Expansion 2032 200
Yakima to S. Oreson/Califomia 2038 150
Portfolio: Naughton I & 2 and Jim Bridger l-4 Retirement 2022 (P-14)
Retircmenl Assumolions
Initial portlirliodcve lopmcnt case P-14 is P-l I with Naughton
Units t & 2 and Jim Bridger Units l-4 retiring in 2022. l'ull
retirement assumptions are summarizsd in the following table.
I rnit
R€rire 1027
(raia I
Croig 2 Rcrirc 2016
Rctirc 20:7
Rctire 2027
Davc Jobnston -'l Retire 2027
Rclirc 2017
Gsdsby I Rerirc 2012
Gar.l$by 2 Rctirc 2012
Gadshy I Rctirc 20-32
Rdire l0l0
Ilavdcn 2 Rctire 20:t0
Hunrcr I Rctire 2042
Hunrcr 2 Rctire 2041
Huntcr l Rctirc 2ol2
Ilu.linslon I Rctirc:016
Iluntinpton l Rcrire:036
Jim Bndacr I Rerire 2022
Jim Bndser l Rcrire 2022
,im Bridacr l Retir. :oll
Jim Bridscr 4 Rctir.2022
Naushton I Rctir.:o2l
Nrulrhton 2 Rerirc 2022
Nlushkrn l t,s. tr 2020 R€tir. 2029
Rctirc:019
GC = gas conversion
Initial Portfolio-Development Fact Sheets
eed{rd}p'p.+"dFdr.S"B."dsdd"o'"d""+"dF.dd
ffiColstrip.r I Rctne 2021
Retir.2025
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Dalc rohnston 2
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Portfolio: Retire All Coal by 2030 (P-15)
PoRTFOLIo ASSUMPTIoNS
Rdircment Assumptions
Initial ponfolio-devclopment case P-l5a is P-28 with all coal
relired by 2030. [ull retiremcrt assumptions are summarized in
the lolbwing table.
Descriotion
At stakeholder request, a variant ol case P-2t1, P-15 was
designed to economically rctire all coal by 2030.
I'nit Dercrhttor
('holla 1 Relire 2020
Rclire 2026
Colnrir.l Rerire l0l6
Retir€ 2021
Davc Johnsro. I Retire 2027
Dave Johnsron 2 Retire 2ol7
D!! c Johrston 3 R.tir€ 2027
R€rir! 2027
Gadsby I Retirc 2032
Grdsby 2 R.tire loll
Cndsby l Retirc l0l2
Haydcn I Retire 2025
tlsvden 2 Retire 2024
Hunrcr I Retire 1028
Hunt.r :Retire 2029
Huntcr l Retire:030
HuntinEton 1 Rctirc 202E
IILmlinAton 2 Relirc 2029
Jim Brid8er I Retir.2026
Jim Bridser 2
Jim Bridger l Retire 2021
Jim Bridger 4 Retire 202.1
Naushton I Retire:0:l
Naushton 2 Rclir€ 2022
Naushton l I-8. CC 2020 RelirE 2029
Rerirc 2030
PORTFOLIO SuuNTeRy
Svstem ODtimi:er PVRR ($nt $22,t32
Resource Porlfolio
Cumulative changes to the resource portlblio (new resource
additions to address load servicc and reliability requircments
and resowce retirements), represented as nameplate capacity,
are summarized in the figure below.
Cumulative Nameplale Capaclty
illiii
lilll
GC = gas conversion
7:
t --,.rll
+e.dp'.d..<lp'd,e""d,+.ds4,,+'d+,e'd"e',,e.d,"+
.ha.iba..o-rEra
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Descriolion Year Canacih'
Aeolus W to Utah S, Erpansion 2024 I,700
Goshen to lltdh N, Expqnsion 2030 800
Goshen to fltah N, l:rpdnsion 2030 800
Yahma to - S. Aegon/Califomia 2037
Initial Fact Sheets
450
Retire 2023
R€lire 2025
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Portfolior Jim Bridger I & 2 Retirement 2022, No CO: (P-16)
PORTFOLIO ASSUMPTIONS
R elire m ent A s s a m o I io n s
Initial portfolio-developmenl case P-16 is P-04 with Jim
Bridger tlnit I & 2 Retired in 2022, with no CO: Full
retiremcnt assumptions are summarized in the lbllowing table-
Descriolion
A variant olcase P-04, P-16 has all ofthc same retieme[t
assumptions except was run with a low gas - no COr price
policy scenario through the System Optimizcr and Planning
and Risk.
D(!criDtior
Choll, .l Rctire 2020
Retirc 2046
Rctir.10.16
Retir€ 2025
Rctire 203,1
Dave Johnslon 2
Drvc Johnsron 3 R€tir€ 2027
Dove Johnston ,l R€trr€ 2027
Rltrr€ 2012
Hayd.n I Retire 2030
Hayden ?Rctire 2030
Hunrer I Retire 2042
Rcrirc 1042
HunrtrrAlon l Rerire 2016
IItlnlinrl(nr l R€tirc 2016
Jim Dridacr I Reure 202:
Jim Dridser 2 Rctir.2022
Rclire 2037
R.lirc 20-'l7
Rctirc 2021
Nau,rhlon 2 Relire 2022
Naushton l Rctirc l0l9
Rctire :01]9
PORTFOLIO SUMMARY
Svstem Oolirnizet PVRR ($n)$18,634
Resource PorTfolio
Cumulative changes to the resource porttblio (new resource
additions to addrcss load service and reliability requiremeuts
and rcsource retircments), represe[ted as nameplate capacity,
arc summarized in the tigure bclow.
Cumulative Nemeplate Capecity
!r-...rnrfilllllll
,d d dp,lo.' d ddd.dd ddd.dd,'.t.d d d
.;@,!&..,.o-rcr.
308
Descintion Yeur Capqcity
Goshen to Utah N, Erponsion 2032 800
Yakima to S. Oregon, Expansion 2037 450
Initial Portfolio-Development Fact Sheets
lR.drczo27 I
I Rcdre lo:7 |
I Gadsbv 2 I Rcti.r 2032 I
I caasuy: I RerirE 2032 I
Hu!rcr 3 | Retir€2(x2
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PORTF0LI0 ASSUMPTIONS
Descriolion
A variant ofcase P-15, P-17 has all of the same rettemcnt
assumPtions exccpt was run with a medium gas - high COl
pricc policy scenario through thc System Optimizer and
Plannrng and Risk.
Retiremenl Assamolbns
Initial portfotio-development case P-17 is P-15 with high CO:,
and the relircment assumptions are surnmarized in the
following table.
PORTFOLIO SUMMARY
I nit
Cholla a Retire 20:0
Colstrip 3 Retirc:026
Colsrrip 4 Rclire 2026
Crais I Retire 2023
Crais 2 Rctire 2023
Dave Johnrlon I Retire 20:7
Dave Johnston 2 Retirc 20:7
Davc Johnston 3 Retire 2027
R.rirc 2027
Gadsby I R.tire 2012
Gadsby 2 Rrlire 1032
Gadsby l Relire 2032
H.ydcn I R€lirc 2025
H.ydcn 2 Rclire 2024
lluDrer I Rel;e 1028
Huorcr l Rclirc 2019
Hu erl Retir€:010
Huntingron I Rctir€ 2028
HDntirgloD 2 Retire 2029
Jim Bridser I R€tirc 2026
Jim Brid,aer 2 Relir.2025
Jin Bridqcr l Retire 2021
Jim tsri<lser 4 Rctire:0:.1
Nauqhton I Rctne 2023
Naushton l Rctirc 2021
Nauehton l La. GC 2020 Rctirc 2029
Retire 2010
System OptimiTer PYRR ($n)$22,070
I nc re menlal Tran s mi ssion
Resource Portfolio
Cumulative changes to the resource portlblio (new rexrurce
additions to ad&ess load servicc and reliability requirements
and resource retircments), represented as nameplate capacity,
are summarized in thc ligurc bclow.
Cumulative N.meplate C.pacity (rc = gas conversion
''1 -rrll
C d"o,'opd,'e'dd d.'d d,'o'oendnds'd.d .d
.rrry.i'a..o..rD9s
I l0
Descriolion Year Cap4cilru
Aeolus W - to - (ltah S, Expansion 2024 I,700
Goshen to Utah N, Expansion 2030 800
Walla llalla to Yokima, Erpansion 2033 200
Yakinh to S. Oregon/Califo,rliu 2037 45t)
Portfolio: High CO, (P-17)
Initial Portfolio-Development Fact Sheets
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PORTFOLIO ASSUMPTIoNS
Descriolion
A variant ofcase P- 15, P- 18 has all of the sane retirement
assumptions except was nrn with a medium gas - social cost
oIcarbon pricc policy sce'nario through the Syslem Optimizer
and Planning and Risk.
R eti re m e nl A s su mp tio ns
Initial ;xrrtfolio<Ievelopment case P- 18 is P-15. social cost of
carbon. and the retir€ment assumptions are summa zcd in thc
lirllowing tablc.
PORTFOLIO SUMMARY
Irnlt Desrription
( holla 4 R.tir€ 2020
Colsirip:l Rctir.20l6
Rctir. 1026
Retire 202-l
( rnis 2 Retire 202-l
I)avc Johnston I Retire 2027
Davc Johnston 2
Drve Johnston 3 Retire 2027
Relire 2027
Cadsby I Relirc l0l2
G.dsby 2 Retire 20ll
Retir€ 2012
REtirc 2025
Rctire 202.1
Retire 2028
Hunt.r :
Hunrcr l
Huntinaton I
Ilunlinaton:
Jim Brid*cr I Rerire 20:6
Jim Bridscr 2 Rerirc 2025
Jim Bridc€r 3 Retir€ 2021
Jrnl tsridser 4 Retire 2024
Naushton I
N4u,rh10n 2 Rctirc :022
Lq. CC 2020 R€tire 2029
Retire 2010
Syste oplimizer PVRR ($n)$3t),022
Incrcme lsl Transmission
Resource Porlfolio
Cumulative changes to the resource portfolio (new r(]x)urc(-
additions to address load service and reliability requirements
and resource retirements), represented as [ameplate capacity,
arq summariz.ed in thc figure bclow.
Cu.nulative Nameplat€ Capacity
iiii
llil
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I!'i --IIf ilil1IlllI
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Descriotion Year Csoacin'
Aeolus WY - to - Utah S, Erpaasion 2024 1.700
Goshen - to - Ulah N, Expansion 2030 800
Yakima - to - S. Oregon/('alifomia 2030 450
Portfolio: Social Cost of Carbon (P-18)
Initial Portfolio-Develooment Fact Sheets
m
I RctiE 202s I
I R.riE 7o1o I
I R.rirc 7o7s I
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Portfolio: Low Gas (P-19)
PORTFOLIO ASSI. ]\I PTIO\S
Retir em enl A s su mo lio ns
Initial portfolio{evelopment case P-19 is P-04 wiih low gas.
liull rctirement assumptions are summarized in the following
table.
Descriotion
A variant ofcase P-04, P-19 has all oltht: same rctirement
assumptions except was run with a low gas - medium CO:
price policy scenario through the System Optimizer and
Planning and Risk.
trDn Des(riplion
Cholla.l Relire 1020
Colstnp 3 Retirc 1046
Colstnp 4 Retir.2046
CEis I Relire 2015
CraiB 2 Rclirc 20-14
Dale Johnlton t Rctirc 2017
Dave Jobnstor 2
Dave Johnston l Retire 2027
Retire l0:7
Gadrby I Rctiic l0l0
Oailsby 2 Retire 2020
Cadsby 3 Retire 2010
Retire 2010
Haydes :R€tire l0l0
Hunter I R€tire 20,12
Hunrcr 2 Rclnc:0.11
Hunrer -l Rcrirc l0.ll
lluDringron t RElire 20.'i6
HuDtinston 2 Retire 2016
Jim Bridger I R€tire 2022
Jirl! Bridger 2 Rctirc l0ll
Jim Bridger l Rctirc:037
Jim Bridser 4 Relire 2037
Nsushlotr I Rdlte l0l2
Naushton 2 Rclirc 2022
Nauphlon 3 Retirc 2019
Relire 2039
PORTFoLro St:rrurnv
St'stem Optimiicr PI'RR ($n) 520.882
Resource Porlfolb
Cumulativc changcs to thc rcs(lurcc portlirlio (ncw rcsourcc
additions to address load service and reliabiliry requirements
and rcsource rstircmet.Its). rcprcscnted as nameplate capaciry,
are surrunarizcd ia the figurc bclow.
Cumulative Nameplate Capacity
; ; --==!llll!lliii
3 t4
Descriotion Year L'apacity
2024 I,700Aeolus W to (hah S, llpansion
Goshen to Utah N, Etponsion 2030 800
Initial Portfolio-Development Fact Sheets
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Portfolio: High Gas (P-20)
PORTFOLIO ASSUMPTIONS
Descriolion
A variant ol'c&sc P-07. P-20 has all ofthe same retirernent
assumptions except was run with a high gas - medium CO:
price policy sccnario through thc System Optimizrr and
Planning and Risk.
Retiremenl Assamolions
Initial portfoliodevelopment case P-20 is P-07 with high gas.
lull retirement assumptions are summarizcd in thc folkrwing
table.
I nit Descriptior
Retire l0l0
Colsrrip 3 Retire 2027
Colsrrip 4 Retire 2027
(rais I RerirE 2025
( rais 2 Retire 2015
Dav€ Johnslon I R€lire 2027
D.rc Joh.ston 2 Relire 2027
Retire 2027
Cadsby I Relire l0l0
Cadsby 2 Rclir.ltll0
Gadsb:/ l Retire 20?0
Ilivdd I Retire l0l0
IhYdm l
Iluntcr I Rctire 2041
llunler l ReGe 2042
Hunt.r 3 Relire l0.ll
Hunlinston I Relire 2036
Ilunlinikrn l Retfe 2036
Jim Bridser I Reti.e 2022
Jim Bridccr l Rerirc:018
Jim Bridccr l Relire 2017
Jim Bridccr 4 Reliie:0-17
Naughlon I Retire 2029
NauEhton 2 Retire 2029
Naughton l Ls. G.C 2020 Retir. 2029
Rctire 2019
Incremenlal Trsns
Resource Porlfolio
Cumulative changes to the resource portlblio (new resource
additions to address load servicc and reliability requtements
and resource retirements), represented as nameplate capacity,
are summarizcd in the ligure below-
Cumulalive Nameplate Capacity (iC = gas conversion
]:I5t 'M IITI'1 --.dllil illilililll
CP"o'o'od,'aCCCdddd.'e'd.df'Cd
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Descriolion Year Csoacitt'
Aeolus W to lltah S, Expansion 20t4 1,700
Goshen - to - Utah N, Expansion 2030 800
IVsllq Walla - to Yakima, Expansion 2030 200
Yahmq to - S. Oregon/Califomia 2032 450
Initial Portfolio-Development Fact Sheets
Pontrolro Sunrulnv
Seslem oplimiut PVRR 6mt $22.746 Retire 2027
Rctire 20i0
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Portfolio: Colstrip f, & 4 Retirement 2025 (P-28)
PORTFoLIo ASSUMPTIoNS
Relirumenl Assamplions
Initial portfolio-developm€nt cas€ P-28 is P-l I with Colstrip
Units 3 & 4 rctirement acceleratcd to 2025. Full rctirement
ass[mptions are sumrnarized in the following table-
Desciotion
A yariant ofcase P-l l, P-28 has the same retirEmelt a-rsumptions
except accelemtes retircment ofcolstrip Unis 3 & 4 to 2025 instcad
of 2027.
t nil D(r.riDrlon
Rctir€ 20:0
( olslrip 3 Relirc l0:J
Colstrip 4 R€rir€ 2025
Craip 2 Retrre 2026
Relire 2027
RBt;e 2027
Rctire 2027
rravc Johslon 4
Gadsby I R.rne 20:i:
C dsby 2 Rctirc 2032
Codsby l Retirc 2032
Haydm I Rerire 1030
Hayden 2 RelirE 20-'10
Hunter I R€lire:041
Rclirc l04l
Iluntcr l Rctir. l04l
Hunlinstm I Retirc 2036
Hudnglon:Renre 2036
Jim tsridser I Retire 20:8
Jim Bridper 2 Rc*e 2032
Iim Bridgcr r
Jim Bridse.4 R.tirc 2037
Nau8hton I Rctirc 2029
Nau,rhton 2 Retirc 2029
Naurhton -l
Resoarce Portfolio
Cumulative changes to thc resource porltblio (new resource
additions to addrcss load service and reliability requirements
and resource retirements), r.?resented as nameplate capacity,
are summarized in the figure below.
Cumulative Nameplale Gpacity
-.ilfiiiiiiiiiiiil[ilfl
GC = gas conversion
".IITI
d"d*+"'{r"ddd$dd."dde+ppndddCp
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Descriotion Year Cao.tcily
Aeolus W to - Uqh S, Expansion 2024 I,700
Goshen to lllah N, bcporsion 2030 800
Walla Walla to Yakima, Expansion 203 t 200
Yakima to S. Oregon/Californ ia 2037 450
Initial Portfolio-Development Fact Sheets
PORTFOLIO SUMMARY
Svstem Optimizet PYRR($ml [21,805 I t( (rrrc ir,l-
I Redre ?037 |
I Lg. cc 2020 Rerir€ 2029 )
I wyoaa* | Retire 2039
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Portfolio: Naughton I & 2 Retirement 2022 (P-30)
PORTTOLIO ASSUMPTIONS
R elire m e nl A s sa mo I i o ns
Initial grrtfblio-development case P-30 is P-l I with Naughton
I & 2 Units rctirement acceleratcd to 2022. Full retiremcnt
assumptions are sumrnarized in the following tablc.
Descriotion
A varia[t of case P-l l, P-30 has all of the same retir€ment
assumptioN except accelerates retkcmenl ofNaughton Urits I & 2
from 2029 lo 2022
D(x rintioll
Cholla,l Rctire 2010
( olslrip -1 Rcrirc l0l7
( olstrip 1 R.rir.2027
( roip i R€ft€ 2025
Rctn€ 2026
REtirc 2027
Rllire 2027
Dav€ Johnston 4 Retire 2027
cadsby I Rctire l0ll
Rctirc 2032
R€rir.2030
Rctire 2010
R€tire 10,12
Ilunrer:
I Iuntinpton I Rclire:0-16
Rerire 1036
Jim Bridscr I Retir€ 2028
Jim tsrids€r 2 Retire 2032
Jim B.ideer 3 Rctire 2037
Rctir.2037
Relirc 2022
R.tirc 20-19
Pontrolro Sulrulnv
Syslem Ootimizer PVBB ($ruL 821,708
Resource Porlfolio
Cumulativc chaflges to the resourcc porttblio (new rcsourcc
additions to address load service and reliubility requirements
and resourcc retirements). representcd as nameplate capacity,
arc summarized in the ligure bclow.
Cumulatlve Namcpbte Capaclty
GC = gas conversion
,
It --'.rllllililllII
,dS,'+'pp.o'd""ddt.d.!ddl+d-dd.s'.dd.,"+
tbFl9ldr?..b:B
Descriolion Yesr Capscity
Aeolus llY to Utqh S, Expansion 2024 I,700
Goshen - to UtahN, ltpansion 1030 800
llalla llalla to yqkimq, Expan.sion 2031 200
Yakima to S. Oregon/Calilbmia 2037 45t)
Initial Portfolio-Development Fact Sheets
I Betlrq?s4 I
l cua"uv z l nr!!r ?qt2
Rclr( l0li!1!!!!L3 I Beu!2!a2
Naughroo t lR€tire?022
NaughrodS I L8. CC 2020 RctirE 2029
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Portfolio: Naughton I & 2 Retirement 2025 (P-3f)
PORTFOLIO ASSUMPTIONS
Rdiremenl Assumolbns
lnitial portfolio-devck)pment case P-31 is P- l I with Nauphton
l-2 llnit retirements acceleratcd to 2025. Full rctircment
assumptions are summarizerl in the following table.
Descriotion
A variant ofcase P.l l, P-31 has all ofthe samc retiremeflt
assumplions exccpl accclerates retirement of Naudton Units I & 2
from 2O2g lo 2025
Ihit
Cholla 1 Retire 2010
Colstrip:Relire 2017
Colstrip 4 Rctire 2027
Crais I Retire 2025
Crais 2 Rctirc 2026
Dav€ Johnslotr I Retire:027
Dave Johnsto! 2 Rctrre l0l7
Drvc Johnston 3 Rctire 2027
Dave Jolnston 4 Rclire 2027
Gadsby I Rclirc 2012
Retire 20ll
Rctire 2012
Retire 2010
Ilayilen 2 Rclirc 20.10
IIunt.r I R.lire 2042
Rcrrre lGll
Retire:(Xl
Hunlrnslon l Rctire 2036
Huntinaton 2 Rclire 2036
Jim Bridqer I Retire 2028
Jin Bridgcr 2 Rctne 2032
Jim Bridscr l
Jim Bridgcr 4
Naughton ,
NauPhton l
Nauehlon l t.E. G{ 2020 Rctin 2029
Rclire 2019
Inc
Resource Porlfolio
Cumulativ€ changes to the resource portlirlio (new resource
additiom to address load scrvice and reliflbility requircments
and resource retircmcnts), represented as nameplate capacity,
are summarized in the figure below.
Cumulative Nameplate C.p.city
'lq@
GC : gas conversion
:I TTffifiIIiililil1:t --.r.llll
Cdd.d.P""'.ddC 'a.f &,dC.p'dddd d
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Dcscriplion l'ear Caoqcii-
Aeolus W - to - Iltah S, twpansion 2024 t,700
Goshen to Utuh N, Ecponsion 2030 300
Walla ll'alla to Yahma, Expansion 2031 200
Yakima to S. Oregon/Califomia 2037 450
Initial Portfolio-Development Fact Sheets
Ponrnouo Sunueny
Svslem ootimizer PVRR ($d $23,484
I Rcr,re jo r-
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Portfolio: Naughton I & 2 Retirement 2025 with Gadsby 1-3 Retirement 2032 (P-32)
Relire,n e nl As su mptiqfi s
PORTFOLIo SUMPTIONS
hitial portfolio-development casc P-32 is P-07 with Naughton
tjnits I & 2 retirement accelerated to 2025 and Gadsby l-3
retiring in 2032. Full retirement assumptions are sunmarized in
thc tirllowing table.Desciolion
A variant ofcasc P-07, P-32 has all ofthe same retirement
assumptions excepl Bccelerates rEti.ement ofNaughton Units I & 2
fiofi 2029 to 2022. and slows retirements of cadsbv Units I - I to
2012 from 2020.
Ihh
Retire 2020
Rctire 2027
Colst ip 4 Relirc l0l7
Crris I Relirc:015
Crais 2 R.lrr.l0l5
Rcri.e 2027
Rcrire 2027
Davc Joh,rston 3 Rctire 2027
R€rire 2027
Retire ?012
Rclire 2032
Rc(ire 20-12
HaydcD I R€lire 20-10
R€tire 2010
Ilutcr I Retir€ 204:
Hunrer l Rctir€ 204:
Hunter l Rctire 2042
Huntingron I Rctire 2036
Hunliralon 2 Retirc 2036
Jim Bridqcr I R.rirc:0ll
Jim Brir.lgcr 2 R.lir€ 2028
Jim Bddscr -1 Rctire l0l7
Jim Bridser 4 Rctire 2037
Naushton I Rctire 2025
Naushlon l Retire 20?5
Naushlon 3 Ls. CC 2020 R.tire 2029
RDtire 2039
PORTFoLI Suuu,qnv
Syslem Oolimizer PYRR ($ )$21,763
Resource Porlfolio
Cumulative changes to the resource porlfolio (new resource
additions to address load service and reliability requirements
and rcsource retirements). represented as nameplate capacity,
are sumrnarized in lhe tigurc bclow.
Cumulatlve N.meplate cepacity
!o--,.riltillll
(rc = gas conversion
d'$ d CCC C.s''aC dd d$.dd C .p' d C d
.''4.r8.'.cl.ro5*
324
Descriolion Yeqr Cuttucit"*
Aeolts W - to tltah S, Frpansion 2024 1,700
Goshen to Utqh N, Expansion 8002030
Yqkima to S. Oregon/Califomia 20J7 450
Initial Portfolio-Develooment Fact Sheets
t (1,"11' 4
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PORTFOLIO ASSUMPTIONS
Relircment Assumption$
Initial portfoli*development case P-13 is P-ll wiG Jim
Bridger Units l-2 retirement accclcrated to 2022. Ftlll
retir€mert assumptions are summarized in the tbllowing table.
I)escriotion
A variant ofcase P-l l, P-33 has all of the same retirement
assumptions excepl accelerates retiremcnt o[ Jim l]ridger Unit I frcm
2028 to 2022 and Unil 2 ftoit 2032 to 2022.
t'nn Delrription
Cholla 4 Retirc 2020
( olstriD l R€tire 2027
Retire 1027
Crais I Retlre 2025
Crais ?Retire 2016
Davr Johnston I Rctire 2027
Dave Johnston 2 Rcrire 2017
Relire 201?
Davc Johnston,t Retire 2027
Cadsby I Rerire 2032
Cadsby 2 Retirc 20ll
Rctir. 2032
Retire 1030
Havden 2 Reiire 2tll0
Hunr.r I Relirc llr42
Hunrcr 2 Retire 204:
Hunrcr l Retir. :0.12
IlLnlrnsnnr l Rctir. l0l6
HunrinsloD 2 Retire 2016
Ji Bndser I Relirc 2021
Jim Brideer 2 Relir.2022
Jirn Bridser 3 Relirc 2o-17
Jifl Bridser 4 Rerirc 2037
Naushton I Rclire 2029
Nllushton 2 Rerir€ 2029
Naughton -1 Lq. C,C 2020 R.tirc 2029
Retire 2039
Resource Portfolio
Cumulative changes to the resourcc portfolio (new resource
additions to address krad service and reliability requirements
and resource retirements), represented as nameplate capacity,
are summarized in the tigure below.
Cumulative Nameplate Capacity
, ,fi --..rllE!!!!!!
GC = gas convcrsion
iiI
,ddd"{r"dd.dd,'p'nllp dno'.d'dCd.d.d od
.9C., .$ri.an
.rurat,a.o.rl@.
326
Desciption Yeqr Capacit't'
Aeolus W - to lllah S, Expansion 2024 1,700
Goshen to - Utah N, Etwnsion 2030 u00
Wallo ll/alla to Yakimu, Expansion 2032 200
Yakima to S. Oregon/Cal ifornia 2037 450
Portfolio: Jim Bridger I & 2 Retirement 2022 (P-33)
Initial Portfolio-Development Fact Sheets
PORTFOLIO SUMMARY
Svstem Optimizet PVRR 6m) $21.895
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Portfolio: Jim Bridger I & 2 Retirement 2022 with Gadsby l-3 Retirement 2020 (P-34)
Retirerrcnl A s s u mplio ns
PORTFOLIO ASSUMPTIONS
Initial portlblio-dcvelopment case P-34 is P-l I with Gadsby
Units l-3 retirement accelerdted to 2020 and Jim Bridger UnitsI & 2 retirements accelerated to 2022. Full retiremcnt
assumptions are summarized in thc fbllowing table.Descriolion
A varian( ofcsse P-l l, and a sibling ofP-33, P-34 has all ofthe samc
retirement assumptions except aecclerates retiremqrl of Jim llridger
tlnit ftom 2028 to 2022 and Unit 2 tom 2032 to 2022. In additiorl P-
34 accelerales rctirement ofcadsby Units l- 3 ftom 2032 to 202?.
thit
Cholla a Relirc 2020
Colstrip 3 Relirc l0l7
('olstrip 4 Retir. :027
Crajs I Retre 2025
Crais 2 Retire 1026
Drve Johnston I Rctirr 2027
Dalc Johnston 2 R€rir€ 2027
Dare JohDslon 3 Retirc ltrlT
Retire 1027
Gadsby I Retire 2o:0
Relire 2020
Rerirc l0l0
Hatdcn I Retirc l0l0
Hayd€n 2 Rehre lol0
Hunter I Retire 2042
llunter 2 Retire 2042
tluDler 3 Retir. 2042
Huntin,rt,tr' I R€lirc 2016
Hunriflgton 2 Relire 2036
Jim Bridser I Relirc 2022
Jim Bridser 2 Rctire 2022
Jim Bridscr 3 Rctirc 2037
Jim Bridqcr 4 Retir€ 2037
Redrc lo29
Naushton l Retirc 2029
Ls. GC 2020 Relire 2029
Relire 20-19
Resource Porlfono
Cumulative changes to lhc resource portfolio (new resource
additions to addrcss load service and rsliability requirements
ald resource retirements), represcnted as nameplate capacity,
are summarized in the figrue below.
Cumulative Nameplate Capacity
GC = gas convcrsion
iII.!
" -.II ,ililillllll
d'"ddddddp""d". ,&""dd'ddd.f,tr.d.*'
.A,i!.'.!..cr.'o'I
Descriplion Yeor Cooacitl
Aeolus llY . to - Utqh S, Expansion 2024 t,700
Goshen - to - Ulqh N, F-xpansion 2030 800
llalla lYalla to Yakim.t, Expansion 2031 200
Yokimq - to S. Oreson/Califomia 1038 450
-128
Initial Portfolio-Development Fact Sheets
Pontrouo SunruaRy
Svstem Optirnizet PVRR $m, $21.949
Grdsbv 2
Cadsby I
Naudton I
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Portfolio: Jim Bridger 3-4 Retirement 2022 (P-35)
PoRTFoLIo ASSUMPTIONS
Desoiotion
A variant ofcase P- l l, and a sibling of P-33 & P-34, P-35 has all of
the same retirement assurnptions except accelerates retirement o[Jim
llridger Units 3 & 4 from2037 to2022.
Retircmenl AssumDlions
Initial ponlblio-development case P-35 is P-ll with Jim
Bridger units 3 & 4 retircment acceleratcd to 2022. Full
retircment assumptions are summarized in the Ibllowirt8 table.
PoRTFoLIo SUMMARY
Svslem Oolimizer PVRR ($d $21.732
Dercriptioo
Chollt'4 R.lir€ 2020
Rctire 2027
Colsdp 4 Retire 2027
Crais I Relire 2025
Craic 2 Rclire l016
Rctirc 20:7
Dnvc Johnsron 2 Rcrire 2017
Drvc Joh,rslon 3 Rcti.e 2027
Rctire ?027
RetiE 20-ll
R.lire 2012
Rctire 2032
Ilaydcn I Rclire 2030
ILrydcn 2 Rcrirc 2030
Hunler I R.lirc 2042
Humcr 2 R.tire 2042
Relire:0,12
Huntinston I Reiire ?036
Iluntinston l Rctire:036
Jim Bndcer I Rclire 2028
Jim Ilridqer 2 Rerne 2032
Rcrire 2022
Jim Bridser 4 Rclire 2022
Naushton I Rctire 2019
NauEhton 2 Rctire 2029
Naushton l La. GC 2020 Retin 2029
Rclire 1039
Resource Porlfolio
Cumulative changes to the resource po(lblio (new resouIce
additions to address load service and reliability requirenents
and resource retiremcnts), represented as nameplate capacity,
are summarized in the figure below.
Cumulative Nameplate C.p.city
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Descrinlion Caoacitv
Aeolus W to - Uah S, frpansion 2024 t,700
Goshen to lhah N, Lrpansion 20-10 tJ00
ll/alla lltalla - to Yakima, Exytnsion 200
Yakima - to - S. Oregott/Califomia 2033 450
Initial Portfolio-Develonment Fact Sheets
GC' = gas couversion
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Portfolio: Jim Bridger I Retirement 2023, Jim Bridger 2 Retirement 2028 (P-45)
RTFOLIO AS MPTI
Relircrnenl Assu mp tions
Initial portfolio-dcvclopment case P-45 is P-3t with Jim
Bridger tlnit t retting in 2023, Jim Bridger (Jnit 2 retiring in
202ta. Full retirement assumptions arc summafized in thc
following table.Desciolion
A variant ofcase P-31, P-45 has all ofthe same retiremcnl
assumplions exccpl accclerates retiEment ofJim Ilridger Unit I lR)m
2028 to 2021 and Jim Bridger tJnit 2 ftom 2032 to 2028.
Descrin.lon
( holh 1 Retird 1020
Retirc 2027
Retire 2027
Rcti.e 2025
Rrtirc 2026
Retirc 2027
Retire 2027
Retire 2027
C.dsby I Rcti..:01:
Gldsby 2 Retirc 2032
crdsby l Retire 20.12
Hayden I Relirc:030
Iluntcr I R.tire 2042
Ilunlcr 2 Retirc 2042
Hunrer .)
HuntiDston I
HuntitrAton 2
Jiln Bridser I
Jirn B.idger 2 Rcti.e:02E
Jim Bridser 3 Rctirc:0-t7
Jim a.idser 4 R€lire l0l7
Rerire 2025
Ntru,rhton :Rerirc 2025
Nuushhn l Ls. CC 2020 R.tirE 2029
Retirc 2039
PORTFOLIO SUMMARY
Svstem Opti,nizer PVRR ($ml $21,59-l
tal'lrans
Resource Portfolio
Cumulative changes to the resourcc portfolio (new rcsource
additioos to address load service and reliability requirements
and resource retiremcnts), represeDted as nameplale capacity,
are summarizcd in the tigure bclow.
ilil!ll!llllll
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Descriplion Yesr Candcih,
Aeolus W- to Utah S, Exponsion 1,700
Goshen to Ukh N, Expa sion 2030 ii00
Wolla llalfu to Yakima, E.tpansion )032 200
Yakimq - to - S. Orepo Colifomia 203 7
Initial Fact Sheets
Cumulative N.meplat. Cepaclty
2024
450
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Portfolio: Jim Bridger 3 & 4 Retirement 2025 (P46)
PORTTOLIO ASSUMPTIONS
Descriolion
A variant ofcasc P-31. and a siblirg oiP-45, P-46 has all ofthe samc
retirement assumptions excepl aocelemtes retirement ofJim Bridger
Unirs I & 4 ti.om 2037 to 2025.
PORTFOLIO SUMMARY
lrDit DescriDdon
Choll:t 1 Retire 1020
Colstrip 3 Relire 1027
Colstrip 4 Relire 2027
Retir€ 2025
Retir€ 2026
Daae Johnston I Retir€ 2027
Dave Johnston 2 Reti.e 2027
Dave Johnston l Retire 1027
Relire 2027
Gadsby I Rerire l0l2
Gadsbv 2 Rerirc 1032
Gadsby 3 Reiire 2032
Hayden t Retire 2030
Hayden 2 Rclire 2010
Hunter I Rclire 2012
IIutrtcr l Reiire 20.12
I luntcr -1 Retire lGll
lludtinslon I Rettre 20]6
HuoliDston :Retir.20l6
Retirc 2028
Jim Bridacr 2 Retir€ 2032
Jim Bndscr 3 R€tir€ 2025
Jirn Bridscr 4 R€tir€ 1025
Naughto! I Retire 1025
Naushton 2 Rctire 2015
Naushton l Ls. GC 2020 Rclirr 2029
Rcli..2Ol9
System Oplimizcr PI'RR ($m)$21,419
Resource Porlfolio
Cumulative changes to the resource porttblio (new rcsource
additions to address load servicc and reliability requirements
and resource retircments), represented as nameplate capacity,
are summarizr:d in the figure below.
Cumulative Namepl.te Gpaci!y
ffirrfilllllilll
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a:!i
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CapacitvDescriptionYear
Aeolus W lo (hah S, Expansion 2024 1,700
Goshen to Ulah N, Expansion 2030 800
Wallq Walla - to Yakima, Exponsion 20.12 )00
Yakimq - to - S. Oreson/Californio 2038 450
Initial Portfolio-Development Fact Sheets Ret emenl Assumplions
Initial ponlblio-dcvelopment case P-46 is P-31 with Jim
Bridger tlnits 3 & 4 retiring in 2025. lull retirement
assurnptions are summarized in the lbllowing tablc.
Cmis I
Crais 2 l
Dave Johrlsloo 4
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PoRTFOLIO ASSUMPTIoNS
Desctiotion
A variant ofcase P-31, and a sibling ofP-46, P-53 has all ofthc same
reliremenl assumptio[s except accclcrates retilement oIJim Bridger
[,nit I from 2028 to 2025, Jim Bridgcr Unit 2 from 2032 to 2025, Jim
Bridger t,rit 3 from 2017 to 2028, and Jim Bridger Unit 4 liom 2017
to 2032.
Retiremenl A ssu molio ns
Initial portlblio-developmcnt casc P-53 is P-31 with Jim
Bridger t Inits I & 2 retiring in 2025. Jirn Bridger Unit 3 retiring
in 2028, and Jirn Bridger Unit 4 retiring in 2032. Full retirement
assumptious are summarize'd in the tbllowing table.
TFOLTO sUUUlnv
Irn
aholla 4 Retrre l0:0
Colstrip .1 Retire 2027
Retire 2027
(rais I Re!!re 2025
Crais 2
Dave Johnslon I Retire:0:7
Drvc Johrsl(D 2 Retire 2027
Rerie 2027
Reiire 2012
Retire 2012
Retire 20-12
Halden I Retire 20-10
HaydeD 2 Retire 2010
Retire 2042
Retire 2042
Retire 204:
Ilunlinslon I Retire 2016
Huntington 2 Retire 20.16
Jinl Bridscr I Retire 1025
Jim Bridscr:Relire 2025
Jim Bridqcr 3 Relire 1026
Jim Brid,r,ir 4 Relire 2031
Naushton 2 Retire 2025
Nau,ahnrn l LE. (j(' 2020 Rctirc 2029
Re(ire 2039
.\$te,n O imi-"er P,:RR ($m) $21.1-18
Trans
Resource Porlfolio
Cumulative changes to the resource portlblio (new rcrnurce
additions to address load service and reliability re$tirements
and resource retirements), represented as nameplate capacity,
arc summarized in the figure below.
Cumuletlve Nam€plate Capacity
!:fr-,'.ril[lll
GC = Gas Conversion
ii
lt
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l)escriolion Year (.arracilt'
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Goshen to Utah N, lipansion 2030 800
ll'olla Wallo - to Yekima, Expaniion 2032 200
Yokima to S. Oregon/(it liforn ia 2038 450
Portfolio: Jim Bridger I & 2 Retirement 2025, Jim Bridger 3 Retirement 202E, and Jim Bridger 4
Initial Portfolio-Development Fact Sheets
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Portfolio: Jim Bridger 2 Retirement 2024 (P-54)
Relirem errl As su mt li., ns
PoRTFoLIo ASSUUPTIoNS
Initial portfolio-development case P-54 is P-3t with Jim
Bndger 2 retiring in 2024. Full retLement a*sumplions are
summarizcd in the following tablc.
Descriotion
A variant of case P-l I , P-54 has all of the same rgtirement
assumplions except accclerates rctiEmenl ofJim Bridger Unit 2 from
20121o2024.
trnit
Cholla {Retirc l0l0
Colstnp 3 Retir€ 2027
Colstrip 4 Retire 2027
C.ais I Rctirc 2025
Crai{ 2 Retire 2026
fravc Johnston I Retire 2027
Dar€ Johnsrof, 2 Relire 2027
Da!€ Johnllon 3 Relire 2027
Dav€ Johnslon 4 Retire 2027
Gadsby I Rctirc l0-ll
Gadsby 2 Rctirc l0:l:
Gadsby.l Retire 2032
Hayden I Retr€ 2010
Hayden 2 Retire 2010
Hunler I Retire:042
Hunrcr 2 Relire 20,12
Hurtcr 3 Relire 2042
Huntintaton I Retirc 2036
HuntinJrton 2 Rerne 2036
Jim Bridaer I R.fte 2028
Jim Bridscr 2 Retirc 2024
Jio BfldEer l Rctirc 2037
JnD Bfldscr 4 Rctir.2037
Naushl()n I Retirc 2029
Naushlon 2 Rc1irc lO29
Nauchhn -l Lc. GC 2020 Retir. 2029
R€tire 2039
Inc Tronsmission
Resource Porlfolio
Cumulative changes to thc rcsource ponlblio ([ew resource
additions to address load service and reliability requirements
and resource retirements), rrpresented as nameplatc capacity,
are summarized in the hgure below.
Cumulative Nameplate C.apacity
nrrrrlllllilll
GC = (ias Conversion
':!
a
" -rIlI
..vFdl&r...t.rD!
33ti
Descriolion l'ear Canacitv
Aeolus W to Utdh S, Expansion 2025 t,700
Goshen to lltah N, Lxponsion 2030 800
ll/alla Walla - to Yaki a, Exryusion 2033 )00
Yahma - to - S. Oregon/Califomia 2037 450
Initial Portfolio-Development Fact Sheets
PoRTFoLIo SUMMARY
Svslem Oolimizer PVRR($n) $23.708
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Portfolio: Naughton I & 2 Retirement 2025 (P-3lC)
PORTFOLIo ASSUMPTIoNS
Descriolion
A variant ofP-l l, P-3lC has all of the same retircmenl assumptions
cxccpt was processcd tkough Planning and Risk Dcterminislic runs
for reliability beyond the i tial2023,2030 and 2038 to include 2024
lhrough 2029.
I rnir Des.riptiotr
Chollu 4 Retire 20ltr
( olslrip l Rctir.l027
Cohtrip 4 R.tir.l0:?
R€rirc 2025
Crris 2 Retirc 2026
Reiire 2027
Relir.2027
Dal e Johoston 3 Retirc 2027
Dai c Johnston,l Relire 2027
R€lire 1032
Cadsby 2 R€tire 20:il
cadsbr l Relire 2032
R.tire 2ol0
Hayd.n 2 Rcti.c l0.r0
Rctirc 2M2
lltmrcr 2 Retirc 10.12
Iluntc.3 Retirc:tX2
Retirc 2{136
Huntinstor 2 Retirc 2016
Jim Bridser I Rerirc 2028
Jim Bridser 2 Retire:0.12
Jim Bridscr 3 Retire 2037
Jim Brid,.er 4 Retire 2(u]7
Nruphton I Retire l0:5
Noushton 2 Relire 2025
Nflughton -l Ls. GC 2020 R€tiE 2029
Reti.e 2039
PoRTFOLro S[uuARY
St'slem Ootimizer PI'RR ($m) $21.619
Resource Portfolio
Cumulative changes to the resourcc portl'olio (new resortrce
additions to address load sewicc and reliability requirerncnts
and resource rctircmclts), represented as namcplate capacity,
are summarized in the ligurc below.
Cumul.tive Nemepl.te C.pacity
C(' : gas conversion
E,r{ --...tflil
dC.P'C.fd ddd dd"dp,ed,c.,e'r'd.s
.,6rr'B+.o.,o!r.
Descriolion Yesr Cupocilt
Aeolus W to Utuh S, Erponsion 2024 1,700
Goshen to lltah N, Expansion 2030 800
Yakine to S. Oregon/(hlifonkt 2038
140
C-Cases Portfolio-Development Fact
Sheets
R e li re m e n I A s s u motio n s
A variant ofcase P-l l, P-llC has all ofthe same retirement
assumptions exccpt accelemtcs retirement ofNaughton U ts I & 2
from 2029 to 2025. Full retirement assumptioos are summarized in
the lirlowing table.
450
tc*i8 |
Cadsbv I
Hnyden I
Hunrer I
H*,tt"sdT--_l
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Portfolio: Jim Bridger f & 2 & Naughton l&2 Retiring 2025 (P-36C)
Relircmenl Assumptions
A variant ofcase P-14. P-36C has all oithe same rctircmcnt
assumptions except slows retiremeot ofJim Bridgcr Llnils I-4 and
Naughton tloirs I &2 ftom2022 to 2025. Full retirement
assumptiom are summarized in the following table.
trnlt Dc{ription
( holla 1 Rclire 2020
Colstrip 3 R.tir.2027
tblnrip {Reiire 2027
Cmi* I Relire 20:5
Crni( l R.rir.2026
Dav. Johnston I Retird 1027
Davc Johnston 2 Rctirc l0l7
Davc Johnston l Retir€ 2027
Duvc Johnston 4 Retirc 2027
Cadsby I Rerirc 203:
cadsby 2 Rclirc 2ol2
Gadsbv.l Retirc 2032
Hayd.n I Relire 20.10
Haydcn 2 Relirc 20.'10
Ituntlr I Retire 2042
Hunrcr 2 Rctir') 2042
I Iuntcr .1 Retirc 2042
Hurlinston I Rclirc 2016
Hunlinslon 2 Rclirc 2036
Jim Bridrcr I Relire 20:5
Jim Brids.r l Retir€ 2025
Jim Bridcer 3 Retire 2025
Jtr Bridser 4 Rctirc 2025
Naushton I Retire 2025
Naushton 2 Retirc 2025
Naughton l Ls. CC 2020 Retire 2029
Rctir.l0:19
PoRTFoLIo SUMMARY
Srflem Ootimizer PVRR $ml $21.544
Incrcmental l ransmi ssion
Cumul.tive Nameplatc capacity
GC = gas conversion
't!
" rrrll ililillillilll
,'"e d d d.e' c d "&" "d d d.d d.c d.s d
"d
d
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142
Canatih*Desciolion Year
Aeolus W - to - Lltah S, Expansion 2021 1,700
Goshen - to - Utah N, Etpansion 2030 800
2037 450Yakima to S. Oregon/Califomio
C-Cases Portfolio-Development Fact
Sheets
PoRTFoLIo ASSUMPTIoNS
Descriotion
A variant ofcase P-46, P-36C has all ofthe same letiremenl
assumptions except was processed through Plaru ng and Risk
Detcrministic runs for reliability beyond the initial2023, 2030 and
2018, to hclude 2024 lhrough 2029.
Resource Portfolio
Cumulative changes to the resouncc Frrttblio (new resource
additions to addrcris kxd service and reliability requiremcnts
and rcsource retirements), represented as nameplatc capacity,
arc summarized in lhe figure below.
.r il€Y
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d .'rzat
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Portfolio: Jim Bridger 1 Retirement 2023 and Jim Bridger 2 Retirement 203E (P{sC)
PORTFoLIo ASSUMPTIoNS
Retircmenl Assumplions
A variant ofcase P-31, P-45C has all ofthe same relilcment
asswnptt)ns except accclemtes retireinent ofJim Bridger Uoit I ftom
2028 ro 2023 aIId Udt 2 liom 2032 to 2028. Full retirement
assumpliom are summarized in the following table-
Descriolbn
A variant ofcasc P-31. P-45C has all ofthe same retiremenl
assurnptions cxccpt was processed tlrough Planning and fusk
Deterministic runs for reliability bcyond the initial2023, 2030 and
2038, to include 2024 through 2029.
DescriDaion
Retirc 2020
Retirc 2027
Retirc 20lS
Retirc:0:7
Dave Johnston 2
Dave JohDnod 3
Retirc 2012
Retirc 2010
R.lirc:010
Relire l0.t2
Reiir.204l
Hunie, l Retir. :042
R<(ir. 10.16
HunlinAton 2 R.ti.. 2016
Jim B;dscr l
Jim B;d,aer 2 Rcrirc 2028
Jim Bridger l
Jim Bnds.r.l Rclirc 20-17
Nauqhtoo I Rctirc:025
Nauqhton :
ReriE 20-19
lsl Transmission
Resource Porlfolh
Cumulative changes to the resource portfolio (new resource
additions to address l<md service and reliability requircments
and resource retircmcnts), represented as nameplate capacity,
are summarized in the tigure below.
Cumul.tive Nameplate Capaclty GC : girs conversion
i'3--...rililIl
.S.d "d"S'Sp''d.'+"d "dt"d,'S,o'.d.dd| dd d.d
.^&.x'i.o.rol.
Descriplion Yeor Conacifi'
Aeolus W to Uloh S, Expqnsion 2024 1,700
Goshen to Utah N, Exrynsion 2030
Yqkima - to S. Aegon/Califomia 2036 450
344
C-Cases Portfolio-Development Fact
Sheets
PORTFOLIO SUMMARY
Swlent Optimizet PVRR ($ml $21.537
800
R.rir. 2027
Crais 2 lRciir.2o26
P.rir".nr?
Retir€ 2027
D^" J"h..t"" 1 TR.rn. ,rff
Gztrshv I lR.tic2ol2
Gadsby 2 | R.tirc20l2
Rctir. 201?
I p-';..1n1(
I Ls. GC 2020 Rerirc 2029
I wyoaal
Urtt _-.l
Cholla 4
( olstt,D.l
Colstrip 4
Craig I
Gadsbv I I
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Portfolio: Jim Bridger 3 & 4 Retirement 2025 (P-46C)
PORTFOLIo ASSU}IPTIoNS
Reli re m e nt A s s u mo tio n s
A variant ofcase P-3IC, and a sibling ofP-4sc, P-46C has all ofthc
same relirement assumptions cxcept accelcratcs retirement ofJim
Bridger Units 3 & 4 from 2037 to 2025. I ull retircment
a-ssumptions are summarizcd in the following table.
Descriotion
A variant ofcasc P-31, P-46C has all ofthe same rctircmeot
assumptions excErl was processed through Ptanning aud Risk
Deterministic mns for reliability beyond the initiat 2023,2030 and
2038, to include 2024 tkough 2029.
(holh 4 Retire llll0
Colstrip 3 R€tirc 2027
Colstrip 4
Crais I
Cmis 2 Relire 20:6
Dovc Jobnston I Retre:0:7
Retire 1027
Davc Johnston l Retire 2027
Davc Johnston 4 Retir€ 2027
Retire 2032
Retire 2ol2
Retir.:oll
Hayden I Rctire 2010
Hrydcfl 2 Rclirc 2010
Huntcr I Relirc:0.11
Hunrcr 2
Hunrer l Retire 2042
Hunlinsron I Retire 2016
Huntington 2
Jim Bridser I Relir. 2028
Jim Dntqer -l Rehrc 1025
Jim BridJ{er 4
Naushion I Retire l0l5
Nauqhron 2 Rclirc lol5
Rctir.2ll39
PoRTFoLIo Suunreny
S$lem Oplimi:et PI:RR ($nl $21.131
Ittc
Resource Porlfolio
Cumulative changes to the resource porttblio (new resource
additions to address load service and reliability requiremcnts
and resource rctiremenls), represented as namcplate capacity,
are summarizcd in the ligure below.
Cumulatlve Nemeplate capacity
GC = gas conversion
3tI!
rrI II niltll
ddd/Pd.dded dd ddCd d e'dd d
.'5Ed,.d'...(b,
346
Descriolion Year Cqnucih*
Aeolus W to - Uah S, Erpansion 2024 1,700
Goshen to - Ulqh N, Lrpansion 2030 800
Yqkima to S. Oregon/Califomiu 2037 450
C-Cases Portfolio-Development Fact
Sheets
Retire 2027
-
Rctirc 2042
Retire 20-16 I
lJimBridscr2 | Rert€ 2032
Reti..2O25
ffiozs
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"E- ,: r 3;83=3i
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=
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Portfolio: Jim Bridger 3 & 4 Retirement 2023 (P46J23C)
Retire m e n t A ss u mo li o n s
C-Case ponfulio-development casc P-46J23C is P-46C with
Jim Bridger Units 3-4 retiring in 2023. Full retirement
assumptions are surrunarized in the lbllowing table.
PORTFOLIo ASSUMPTIoNS
Desciotion
A variant ofsibling casc P46C, P-46J23C has all ofthe same
rctirement assumptions except acceleratcs retircment ofJim Bridger
Units 3 & 4 from 2025 to 2021. In addition, it was processed through
Planning and fusk Deterministic ruos for reliability b€yond the initial
2023, 2030 and 2038, to include 2024 through 2029.
thit Descriprior
Cholh a Relir€:010
Colslrrp l Retir. 2027
Rctire 2027
Crais I Retir. 2025
Crais :Rctir. :026
Dave Johnston I R€tirc 2027
Davc Johnslon 2 R€tirc 2027
Dw. Johtrston 3 Relirc 2027
Dai c Johnston 4 Rctirc:027
Cnd\by I RBtirc l0l2
cadsby 2 Retirc 2012
Rctirc:010
Rctirc 2030
Rcrirc 2042
Hunr€r 2 Retire 2042
Hunlcr 3 Retirc 20.12
Huntinston 1 Retire 1036
HuntinB(on 2 Rctire 20-16
Jiln Bridser I Rctirc 20lE
Jim Bridser 2 Relirc 20-12
Jim Bridcer 3 R€tirc :023
Jim Dridqer 4 R€tirc 302.1
Iiaushton I Retirc 2025
Nauchron :Rctirc:025
Lg. G( 2020 Rctirc 2029
Retire l0l9
Resource Portfolio
Cumulative chalges to the rcsource porttblio (new rcsource
additions to address load scrvice and reliability rcquirements
and rcsource retiements), rcpresented as nameplatc capacity,
are sunmarized in thc figure below.
Cumulativ€ Nameplate Capaclty (i(' = gas conversion
]
zr --rttl ilItl
d'" d,e-"dp dddd dd dd,'ed dd'p'd d
148
Desoiolion Year Capucih'
Aeolus W - to - Utah S, Expansion 2024 1,700
Goshen - lo lltah N, Expansion 2030 800
Yqkima - to S. Orcson/Califomia 2037 450
C-Cases Portfolio-Development Fact
Sheets
Ponrrollo Suurranv
Svstem Ootimizer PVRR ($m) $21.3E5
Colstrip 4 l
t N"r"hr".l
I wyode*
tH.'d* r --------
Hivdcn 2 I
Huntcr I
U
\o
E
d
€
tp
ca
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i
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o-
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r.,P E E E.U?C,^LCi,L,r-H(!(!
8trtrtrtrtrtrtr
r\I
ac>;i.o
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=l6r lt € 6 E aal { x r n r n:l.larNNF-
Sto ar cl o 6 0|,l aa Ga aa d d N
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eli 5t'r -'r ; i ? ;." E i'r E'silllrE;5Et:Egi55EEPl= , ] 3; = * ? 3
= = =
3 ' i iNt; r r > > >;; =:;; > > > >;lO o ll o o o !t F. - N e d o 6 o'n
=1ll 6 -.n 6 @ 6 e nr i t \o 6 i or iil|n tr n n€lr o o n.o.o or or H d,n rn N F @ @
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-
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itE
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Z iEEZ 'iIl35==<tar 5 a a o o]338*eeqr r n tr n rEl--N6NE
-to o o o o o
r-E(ECE;
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Portfolio: Jim Bridger 3 & 4 Retirement 2035 (P-47C)
PORTFOLIO ASSUMPTIONS
Retir e m e nt A ssu mo tio ns
C-Case portfolio{eve lopmcnt case P47C is P-45C with Jim
Bridger Units 3-4 rctiring i[ 2035. Full retirement assumptions
are summarizcd in the following table.
Descrinlion
A variant ofcase P-45C, P-47C has all ofthe sarne retirement
assumptions except accelerates rctirement ofJim Bridger tlnits 3 & 4
ftom 2017 to 2035. In addition, it was processed through Planning
and Risk Deterministic runs for reliability beyond the initial 2023,
2030 and 2018, to include 2024 tlrough 2029.
R.tir€ 2020
Coisrflp l Retirc 2027
Colstrip 4 Retrr.l0l?
Crais I R€trr€ 2025
R€rir€ 2026
R.tire2027
Dave Johnston 2
Dave Johston -1 Relire 2017
R€tire 2027
Cadsby I R€fte:032
R.rir.20l0
Rctire ?010
Hunter I Rctirc l0ll
Hudcr 2 Rctire 2042
Hurltcr 3 R.tir.2042
Hmlinslon I
R.lire 2036
J;n Bridser I R.tirE 2021
Jim Brid8.r 2 Relire 2028
Jim BriJscr 3 Rctire 2015
Rctire 2035
Naushlon I Rctrre l0l5
Naushron 2
Lr. Cr 20.10 RerirE 1029
PORTFOLI0 SUMMARY
Ststen Optinizet PYRR ($d $21.167
Resource Po folio
Cumulative changes to the resource porttblio (new res0urce
additions to address load service and reliability requirements
and resource retiremgnts), represented as nameplate capacity,
are summarizcd in the figure below.
Cumulatave Nameplate Cepaclty (iC = gas convcrsion
]
=!
E .....rrilllllllilll
d"6P.'"fd,6rd.6,'.!o'd,!e'"dd.O.ddP-d.6r.s,'d.d
150
Descriplion Yesr Capocitt,
Aeolus W - tct - Utqh S, FJponsion 2024 1,700
Goshen - to Uah N, Expansion )030 iJ00
Yakimd to S. Oratro n/('a lifom ia 2036 450
C-Cases Portfolio-Development Fact
Sheets
Rctirt 2027
l Gd"bv 2 l Rcdre 2032
lcad$y 3 lRdirc2032
Rctir 2036
R.tire 2025
Hunlinglor 2
Jim Bridscr 4
Nsughton il
UEit
Cholla 4
Crtis 2
Davc ,ohtston I
Haydcn 2
()
a-1
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d
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6=€
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t.E ',. sEEEE .:' :5:3' 3r3ri .. iii:ii; !ii*.,rri+ Eir3r5;]I,],r, =]I=ilg-.= = - - t.*. -= tt:::=?lB:Fr f;8F888;itr a r. t. ilF ll ff ri @ !r ts!l x x n { rr 4t \:lrdrr lrii.rdiFolld.{.a.!a j.{r{d .o.n dr dr:l333Ef AARRRRRR
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Illtr ts!3 6 E U 3Z,a -! i t.! = =SEgggEggsIi::sEssEl: > > >; >::;;:; =: E =;la.n o ur lo o vt o F F d d o N o 6lli i ro d H ro !r !? r? !r N @ n| N d rtrIn r r !5la .o.a.o <r' cr' 6 R 6 6 (t rar F a 6 q)
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<lo <t o o o o o o o>lFl 6l ^ d
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Portfolio: Jim Bridger 3 & 4 Retirement 2033 (P-48C)
PORTFOLIO ASSU}IPTIoNS
Retbemenl Assumptions
C-Casc porttblio-developmetrt case P-48C is P-45C with Jim
Bridger Utlits 3-4 rctiring in 2033. Full retirement assumptions
are summarizcd in the following table.
Desciolion
A variant ofcase P-45C, and a sibling to P-47C, P-48C has all of the
same retirement assumptions except accelerates retirenrenl ofJim
Bridger (ints 3 & 4 from 2037 to 2033. In addition, it was proccsscd
lhrough Planning and Risk Dcterministic runs l'or reliability bcyond
thc initial 2021, 2010 and 2038, to include 2024 through 2029.
I'nit Descriptiod
Rcl;rc 2010
Relire ltrlT
Colslrip.l
CEig I Relirc 1025
Crais :Rerire 2026
Rctirc 1027
Dave Johnston 2 Rctirc 2027
Retirc 2027
Gadsby I
Gadsb\' l Relirc 20.12
Cidsby l R€rir€ 2012
I layden I Retire 2030
RetirE 2030
Rclirc 2041
Huter 2 Relir.20{l
Honler 3
Huntington I R€lire 1036
Iluntinston 2 Retire 2036
Jim Arirlecr I
Jim Bridcer 2
Jim Bridger 4 Rcrirc 2033
Naushton I
Naughn,fl 2 Retire 2025
Naushton l Lc. CC 2020 Reti'E 2029
Retirc 1039
PORTFOLIO SUMMARY
Ststem Optimipr PVRR ($d $21.482
lnc
Resource Pofifolio
Cumulativc chrmges to the resource portlblio (ncw resource
additions to address load service and reliability rcquirements
and rcsourcc retirements). represented as nameplatc capacity,
are summarized in the figure below.
Cumularive N.meplalc C.pacity GC : gas conversion
;
!3
a ilililllllo -rIIr
"d
d p
"d,,ed dd"d d."d,.4 ,o*d "&'dJ'd
d
"d
.d
352
Descriplion Year Llopucitt'
Aeolus W to Uah S, Expanion 2024 1,700
2030Goshen - to - Utqh N, Exwnsion 800
Yakimd - to - S. Oregon/Califomia 2036 450
C-Cases Portfolio-Development tr'act
Sheets
Rctirc 2027
Rctin 2032 |
m
lRett.20.2] I
I Rcrirc 2Ul2 |
ro
t ch.n,4
I c"t't';p:
I tlav.len l
I Hunr.r t
-I I
(-)
l
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&
{
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ca
E
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,
t
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T
EE E,3 3aa a
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=ll::>>=iqf$sHE6
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-a LElg si:li 3 +*lE ] >ct ti = or
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= =;3 3 3;: =;;3;lto 6 6 ro o ao 6 A d d h i 6
ql rr n tr tr*l- 6 6 6!lr{ d d doto o o o o o o o o o o o o
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olo a o '5 i: o o o o o c, o o
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--1 .=66==f,86366Fr341!! t i r i t ]s= > > > > > >tlB B P P 8 8Icla d.n 6 n !t q;t n ( tr tr tr
;lo o o o o o o
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Portfolio: Jim Bridger I &2 Retirement 2025, Jim Bridger 3 Retirement 2028, and Jim Bridger 4
Retirement 2032 (P-s3C)
PORTFOLIO ASSUMPTIONS
&fuEsslAsrn@
C-Case portfblio{evelopment case P-53C is P-3lC with Jim
Bridgcr Llnits l-2 rctiring in 2025, Jim Bridger Unit 3 retiring
in 2028, and Jim Bridger Unit 4 retiring in 2032. [ull rettement
assumptions are surnmarized in the tbllowing table.
Descriolion
A varialt ofP-53, P.53C has all of the samc rctircmcnt assumptions
except was processed tlrough Planning and Risk Deterministic runs
for reliability beyond the initial 2023, 2010 and 2038, to include 2024
through 2029.
Ihlt DescrlDtlon
Cholla,l Rctirc 2020
Colstrip l R.tir{ 2017
('olstrip.l Retirc l0l7
( rais I Rctrre l0l5
( rais 2 Renre 2026
D,rve Johnsbn I R.tire 20:7
Dnve Johnston 2 R.tir. 2027
Dnve Johnston -1 Rctirc l0l7
R.lir. 2027
Gadsby I Retir. 20.12
cadsby 2 Rctirc 20.11
Godsby 3 R.tirc :o:]l
Ilnydcn I Rcrirc l0l0
IInyd€n 2 Rclire 20:]0
Hunrcr I R.rir. 20.12
Hunrcr l Rerire :ol:
Ilunrcr 3 Rdlirc 2042
Iluntinrlon I Rcrirc 2016
llunlin,qlon:Rcrire :016
Jim Bndser I Relire 1025
Jrln Undser 2 Rcrire:0:5
,inl Brids.r l Rclir. :0lE
Jim BriJscr 4 Rctire 20-12
N!u,ahl()n I Rctirc 2025
Naushlon 2 Retire:0:5
Nnuphlon 3 Lr. Ca 2019 Retift 2029
Rdlirc 2019
PoRTFoLro Suuunnv
S$tem Oplimi:.et Pa'RR (Sn ) 521.150
Resource Porlfoho
Cumulative changes to thc rcsourcc fxlrtlirio (new rcs{)urcc
additions to address load service and reliability requirements
and resource retiremeots), represented as nameplate capacity.
are summarized in the figure below.
Cumulative Nameplate Capacity
GC = gas conversion
t
!
.E
E o rrtl .,,illlllll
+ed$d,edd"-d.dp'd,S.o'dp-dt,e".dddr
.turE.erir.on?6..
154
Desciption Year ( tpacilt,
Aeofus W to Uah S, Expan.sion )D4 t,7m
Goshen to Utah N, F;ponsion 2030 300
Yq6mq - to - S. Oregon/Califonia 2037 450
C-Cases Portfolio-Development tr'act
Sheets
-(,
ao iri
d9
..r ,=
B&E-t
;:0
.rc0
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.E ^,.. E
o: oa
fi
9
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: > > > 5 >- i. 7 7 a.{EEE:ei€;;Se
=ig3Eg=e==33:=>>=E;;;;>>666OvlOrtF.F.irlO
rrloloF6(^6066N6crooooooooooo
a
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til <t ct o o o o o o o,.r.r d N
O
ta
at
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i i"BEI =o .s
r dui to .(, o 5i rIi! Iffifi! !a!t!la. 5::t:> z<1|,r Irrr o o o,t.i - a rr !t =!91 r lr { r r eEl- !. - N h +e88833 -e
>l.a r{ cl d N d 'oc OJ
=
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a
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Portfolio: Jim Bridger I & 2 Retirement 2023 (P-53J23C)
PORTFOLIo ASSUMPTIoNS
Relircrnenl Assu ptions
C{ase portfoliodcvelopment P-53J23C is P-53 with Jim
Bridger Units I & 2 retiring in 2021. Full retirement
assurnptiotrs are summarized in the following table.
Descriotion
A variant ofsiblirg case P-51, P-53J?3C has all ofthe same
retircment assumptions except accelerates retircmcnl ofJim Bridger
Units I & 2 from 2025 to 2023. In oddition, it was processed through
Planning ard Risk Delerministic runs for reliability beyond lhe initial
2021,2010 aod 2038, (o include 2024 rhrough 2029.
DescdptioD
Cholla.l Relir.2010
Rctire 2027
Crais I Rctirc 2025
Crais 2
Da\'. Johnston 2
Dave Jobnston 3
Dave Johrrton 4 Rcl;c 2017
Rctire 20-12
Cadshy 2 Rctrre l0ll
Gadsby :i Retire 203:
Hayden l Rctirc 2030
Hayden ?Rcti.c 1030
Iluler 2 R.lirc lM2
Uffiter l Retir€ 20,12
Ilutinxton I Refte 20:6
HuntinqtoI1 2 Rctirc 2036
Jim Bridscr I
Jim Brids€r 2
Jim Brirlcer 3 Relire 2028
Rcrire ?012
Nauphli)n I Rctire 2015
Nauphlon 2 Rctire 2025
Naushton l Ls. (X'2019 Retin 202s
Rctire 2019
PORTFOLIO SUMMARY
Svstem Ootimi:er PVRR ($d $21.394
Transmission
Descrioliotr l'atr Cuoocib'
Aeolus W - tct - Utah S, Erpansion 2024 1,700
Goshen to Utuh N, Erpansion 20t0 tJ00
Yakina to S. Orcgon/Cu|i[ornitt 2037 450
Resource Porlfolitt
Cumulative changes to the rcsourcc portlirlio (new resource
additions to addreris load scrvice and reliability requircmcnts
and resource retirements), rcprcscnted as nameplate capacity,
are summariTed irt the figure below.
Cumulative Nameplate Capaci!y
3 lq@
2!
E
" -IIII
'.ddnord.'6rf'n+"ddnd,+'d.p''o'.o'dldp"dd
.,qd'd!l(j.r,6r.
356
C-Cases Portfolio-Development Fact
Sheets
GC : gas conversion
Rctire 2027
Rctire 2026
Rctir.2027
Rctir€ 2027
I nuntcr t I Rerire 2u2
I R.dre 2023 I
I R€rire 2o2l I
I Gadsby I I
Ut
Jim B.idscr 4
C.t",.trt---__-..l
Colstrip 4
II
a-
I
ot-E9
,-J-lr'IE = .. .2.996E;;J_cI_JtnT A E N E E
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Portfolio: Jim Bridger 2 Retirement 2024 (P-54C)
Retir e menl A s s u mp tio ns
C{ase portfolio.development case P-54C is P-31 with Jim
Bridger Unit 2 retiring in 2024. t'ull rctirement assumptioos are
summarized in the following table.
PORTFOLIO ASSUMPTIONS
Descriotion
A variant ofP-54, P-54C has all ofthe samc retirement assumptions
except was processed through Planning and Risk DetermiDislic nrtrs
for reliability beyond the initial 2023, 2030 and 2038, to includc 202d
through 2029-
t nit
( holla 4 Retire 2010
Colstrip l Rerire 2027
Colstrip 4 Retire 2027
CraiP I Relire 2025
Cr.i8 2 Relir.2026
D.v€ JohEslon I Reiire 2027
Dav€ Johnston 2 Rctire 2027
Dare Johnslon 3 Ret;e 2027
Relire 2027
Gadsby I R.lir€ 20.12
Gadsby 2 Rctire l03l
cadsby 3 Rctire 2012
Hayden I Rctire 20-10
Haydefl 2 Rctirc 2010
Hmter I Retirc 2042
Hunler 2 Retire lO42
Hunt€r l Retir€ l04l
Huntinstoo I Rctire 2016
Huntington 2 Relire 20-16
Jin BridBer I Relirc l0l8
J;n Br;drer 2 Retirc 201,1
Jim Briilser l Retire l0l7
Jirn Bridqer J Retire ?0i7
Retire 2029
Relire 2029
Naushlon 3 t.s. GC 2019 Rctirc 2029
Retire 2019
PORTFOLIO SUMMARY
Svstem Oolimizar PVRR($d $21.151)
Resource Portfolio
Cumulative changes to the resourcc portfolio (new resource
additiotrs to address load service and reliability requirements
and resourcc rctircments), represented as nameplatc capacity,
are summarizcd in the figure below.
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Aeolus W to Utah S, Erpan.siott 2024 1,700
Goshen to - Utqh N, Expsnsion 20J0 800
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Portfolio: Jim Bridger & Naughton 1&2 Refiring 2025 (P-J6CP)
PORTFOLIO ASSUMPTIONS
Relbemenl Assumntions
A variant ofcase P-14 and a variant ofP-36, P-36CP has all of
the same retiremcnt assumptions except slows retirement of
Jim llridger Units l-4 and Naughton [Jnits I & 2 tlree years,
from 2022 to 2025. Full retircmenr assumptions are
summarizcd in the following table.
Descriolion
A variant ofcase P-36, P-36CP has all ofthe same retirement
assumplions excepl was proccssed tbrough Planning and Risk
Deterministic runs lbr reliability beyond the C-Cascs' 202-3 through
2030 and 2038, to include 2031 through 2037.
I'nit Descriptiotr
Cholla 1 R.tire 2020
Retirc:02?
Retire 20:7
Relirc 2025
Craiq 2 R€rir.l016
Davc Johnston I
Dnve J0hnsron 2 Retire 2027
Davc Johtrsron .l Retirc 2027
Retirc ?017
G.dsby I Rerir.20:12
Gadsby 2 Rctire 2032
Gadsby 3 Relir. z0l:
Hayd€n I Retirr:1130
Havdd 2 Retire 2030
Hunrer I Retire 1042
Huntington I Retire 20:i6
Huflrinsro! 2 Retirc 2016
Jim Bridcer I Rctirc lo25
Jim Bridqer 2 Retire 2025
Jim Bridser l Rcrir€ 2025
Jim Bridser 4 Rcrirc:o:5
NaushtoD I Retire:025
Nauqhton 2 Relirc 2025
Naushtotr l Lg. CC 2020 Relirc 2029
Retire 2019
PORTFOLI Sunuany
Svstem Ootimizer PVRR l$m) 521.553
mtssron
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Aeolus WY to Utah S, Expansion
Goshen - to - Utah N, I-sparcion 2030
Yakima to - S. Oregtn/California 2037 450
CP-Cases Portfolio-Development Fact
Sheets
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PORTFOLIo ASSUMPTIoNS
Refiremenl Assumplions
CP-Case pontblio-development casc P-45CP is P-31 with Jim
Bridger Unit I retiring in ?023 and Jim Bridger lJnit 2 rctiring
in 2028. Fttll retirement assumptions are summarized in the
tbllowing table .
Descriotion
A varia[t ofcas€ P-45, P-45CP has all ofthe same retirement
assumptions excepl was processed through Planning and Risk
Dcterministic runs for reliability beyond the C-Cases' 2023 through
2030 and 2038, to include 2031 through 2037.
I ni.Dercriptior
Cholla,l Retire l0l0
Colslril, .1 Retire 20:7
ColstriD 4 Retire 2027
( rdq I Retirc 202J
( rflig 2 Rerirc 2026
Retire 2027
Dnvc Johnston 2 Retire 2027
Dave Johnslon 3 Reiire:027
Retire 2027
Cadsby I Relirc 2031
Gadsby 2 Retire 2012
Cadsby 3 Relire 2032
H.ydcn I Relire 20-10
rlayden 2 Relire 20-10
Hunter I Relire 2042
Hunter -l Rclirc 2042
Huntcr l Retire 20.12
Hunlingto l Relire 2016
Huntin*ton 2 Retire 20-16
Jim Bridqer I Rclire 2023
Jim Bridscr 2 Retire 1028
Jim Bridser l Retire 20-17
Jinl Bridccr 4 Retire 2017
R.tire 2025
Naushlon 2 Retire 2025
Naushion l Ls. G(' 2020 Retire 2029
Retire 2019
PORTFOLIo SUMMARY
Svslem Ootimizer PVRR (Sml 521.480
Resource Portfolio
Cumulative changes to the resource pordblio (new rcsource
additions to address load scrvicc and rcliability requirernents
and rcsource retiremetrts), reprcsented as nameplate capacity,
arc surrmarizcd in thc ligurc brr:low,
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Descriolion Year Cooacilt,
Aeolus W - tct - Uoh S, Expansion 2024 1,700
Goshen - to - Ulqh N, Etpansion 2030 800
Yakima to S. Oregon/(irlifomiu 2036 450
CP-Cases Portfolio-Development Fact
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Portfolio: Jim Bridger 3 & 4 Retirement 2025 (P-46CP)
PORTF0LIo AsSU\TPTIoNS
R et i re m ent A s s a m o lio n s
CP-Casc portfolio-developmert case P-46C is P-31 with Jim
Bridger Ilnirs 3 & 4 retiring iu 2025. Full retirement
assumptions are surunadzed in the following tablc.
Descriotion
A variant ofcasc P-46. P-46CP has all ofthe samc rctircment
assumptons excepl was prcrcessed through Planning and Risk
Dcterministic runs lbr reliability beyond the C-Cases' 2023 through
2030 and 2018, to include 2031 lhrcugh 2037.
I nit De!criptiotr
( holla4 Rctirc 2020
Colstrir, 3 R.tire 2027
ColslriF 4 Rctn€ 2027
Crais I Rctire:025
Crais 2 Rclirc 2026
Dave Johnstoo I Relirc:027
Da\e Johnston 2
D:rr c Johnston l Rctirc 2027
Rctirc 2027
Cailsby I Rctirc 20ll
Rctire 2032
Rclirc 20-12
Rctire 2010
Ilunler t Rctire 2ffi2
Hunter 2 Rclire 1042
Hunter l R€lire 2Ol2
Huntington I Rcrire 2016
Ilmlinston l Rclire l0l6
Jim Bridqcr I Rclirc 2028
Jim Bridger 2 Rclirc 2032
Rctir€ 2025
Jim tsrideer 4 Rctnc 2025
Naushton I Rcrn€ 2025
Naushton 2 R.tir.2025
Naushtoo l
Rcrirc 2039
PORTFOLIO SUMMARY
Svstem Optimizet PVRR (8d $21.460
Resource Porlfolio
Cumulative changes to the resource podfolio (new resource
additions to address load service and reliability requiremerts
and rcsource retirements), represented as narneplate capacity,
are summarized in the tigure below.
Cumuladve Nameplate Capaaity (iC = gas conversion
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Goshen - lo - Utoh N, Erpansion 2030 800
2037 450Yakima to S. Oregon/California
CP-Cases Portfolio-Development Fact
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Portfolio: Jim Bridger 3 & 4 Retirement 2023 (P46J23CP)
Relir e m e nt A s s u mn tio ns
CP-Casc portfolio-development case P-46J23C is P-46 with
Jim Bridger Units 3 & 4 retiring in 2023. Full retirement
assumptions arlj summarized in the tbllowing table.
PORTFOLIOASSUMPTIONS
Descriotbn
A variant ofcasc P-46. P-46J23C has all ofthe same retircmen(
assumptions excepl was processed through Planning and fusk
Determitistic runs for reliability beyood thc C-Cases' 2023 through
2030 and 2018, to include 2031 tkough 2037.
IInil Des.riDaiotr
('holla 4 Rerir€ 2020
Colsl.ip.l Retire l0l7
( olslrip 4 Rctire 1027
(rri8 I Rclirc l0l5
Crlic :Retirc 2026
D.vc Johnston I R€tire 2027
Davc Johnston 2 Retire 2027
Drlc Johnslon 3 Rctirc 2017
Rclirc 20:7
Cadsbv I Reriru 2032
Cadsby 2 Retirc 2032
Gadshv -1 Retire 2032
Il8ydn I Rctire 2030
llayd6 2 Rctire 2030
ltunt.r I Rctire 2042
Huntcr 2 Rerire 2042
Huntcr -1 Rerire 2042
lluntington I Relirc l0l6
Iluntinslon l Relire:036
Jim Bridscr I Rctir.:028
Jim Bridger l Rctn.l0.ll
,im Bridcer 3 Retire 2021
Jim Bridqer 4 Rert€ 2021
Naushton I Retire 2025
Ntru,ahton 2 Retire 1025
Naushton l Ls. CC 2020 Retin 2029
Retir€ 2019
PORTFOLIO SUMMARY
Svslem Ootimizer PVRR ($m) $21.402
Resoutce Portfolio
Cumulative changes to the rcsource portfolio (new resource
additions to address load service and reliability requirements
and rcr*rurcc rctirements), represented as mrneplate capacity,
are summarized in the fi$ue below.
Cumulative Nameplete Capaclty (iC = gas conversion
I:!5
E nillllillll:t --...11
"s,".dp"dd"{'-rp""dadfrl+,e','S'o'd,'.f .rd..d
.^,!l.dl6l..o-ro!rr
366
Descrittlion Year Capacitl
Aeolus W - to - Uah S, Erpansion 2024 1,700
Goshen - lo - Utah N, Exponsion 2030 800
Yakima to S. (hegon/Califonia 2037 450
CP-Cases Portfolio-Development Fact
Sheets
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Portfolio: Jim Bridger 3 & 4 Retirement 2035 (P-47CP)
PORTFOLIO ASSUMPTIONS
Retircmml Assumntions
CP-Case ponfolio-development case P47CP is P-45CP with
Jim tlridgcr Units 3-4 retiring in 2035. t'ull retfuement
assumptions are sunmarized in the following table.
Descriotion
A variant ofcasc P-47C. P-47CP has all ofthe same retircmcn(
assunptions excepl was processed through Planning and Risk
Determinislic runs for reliability beyond the C-Cases' 2023 through
2030 and 2018, to ircludc 2031 llrourh 2037.
IInlt Drs(riDtion
( hollx J Relirc 2020
Colstrin -l Retire 2027
ColslriD 4 Reiirc:017
Craia I Rctir.20:J
Crai,r 2 Rcrir.2026
Rctirc 2027
Retir.2027
Drvc Johnston 3 Retirc 2027
Retir€ 2027
G|dsby I Relire 203i1
Gadsby 2 Rctirc 20:l
Gadsby 3 Rciirc 2012
llayd.n I Retir.l0l0
Ilaydm 2 Rclir.20l0
Ilunr.r I Retire:042
IluDrcr :Rclirc 2042
Relirc 2O4l
Hunli,rgtol I Relirc :036
Huntinston 2 Retire 2016
Jim Bridser I Retirc 2023
Jim Bfld8cr 2 Relire l0:8
Jim llridgcr l Rctirc 2035
J,fl Bridrc..l Rerirc 2035
Noushton I Retirl}2025
Nrushion l Rctirc 2025
NauAbton l Ls. CC 2020 RetirE 2029
Rclirt ?0]t9
Cumul.tive Nameplate Capacaty
rt@
1!.!O
GC = gas conversion
]:Ii
g O.TIII
ll5Ol
(1ml
o0@)
S'd,+','d"dd"ddd dd d S dddp"dd "d
I (r8
Descriplion Yesr Caoscitt'
,4eolus W to - {llah S, Expansion 2024 1,700
Goshen to Utah N, Expansion 2030 800
Yakima to S. Oregon/Califomia 2036 450
CP-Cases Portfolio-Development Fact
Sheets
PORTFOLIO SUMMARY
Slstem Oolimiz.er PVRR ($d 521.469
Resoarce Porlfolio
Cumulative changes to the resource f[rtlblio (new resouce
additions to address load service and reliability requirements
and resource retirements), reprcsented as nameplate capacity,
are summarized in thc ligure below.
.*i.4.
.ArsarFr..onrolrl
o.OF.
d.
a
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<tcr ar o o o o o o o o otln .. N d
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Portfolio: Jim Bridger 3 & 4 Retirement 2033 (P-48CP)
Rel emenl Assumntions
CP-Case portlblio-development case P48CP is P-45CP with
Jim Bridger Units 3 & 4 retiring in 2033. Iull retirement
assumptions arr: summarized in the lirllowing table.
PORTFOLIO ASSUMPTIONS
Desciplion
A variant ofcas. P-48C. P-48CP has all ofthe same retiremenl
assumptions .xccpt was processed through Planning and Risk
Delerministic runs lbr rcliability beyond thc C-Cases' 2023 through
2010 and 2018, lo includc 2031 through 2037.
t nit DescriptioD
(hollu 4 Relirc 2020
Colstrip l R.rir.20?7
Retire 1027
Crais I
Crais l Rclirc 1026
Dave Johnston I Rerin 2017
Davc J0hnston 2 R.tirc 2027
Da\ c Johnston l Retirc 2027
Dalc Johnstoo 4 Rclirc 2027
Cadsby I Relirc 20-12
Cadsby 2 R€lire 20:2
Cadsby.l Rerirc l0l2
Hayden I Retire 1030
Hayd.n 2 Retirc 2010
Hunlcr I Rctir. 2M2
Hunler l Reiirc 2u2
Hunt€r 3 Retirc 2012
Htuttinqron I Rctirc 1036
Huntinston 2 Retire 2036
Jinl Bridser I Rctirc 2021
Jim Bridscr 2 Rctirc 2012
Jim Bridse. 3 Retir.2033
Jim Bridacr 4 R€lir.2033
NruFhron I Rcrir.l0l5
Naudlon 2 Retirc 2025
Naushhn l Ls. GC 2020 Retir€ 2029
R€tir€ 2039
PORTFOLIO SUNIMARY
Svslem Ootimizer PVRR($ml $21.457
Resource Portfolio
Cumulalivc changes to the rcsource portlblio (new res{)urce
additions to address load service and reliability rcquirements
and resource retiremcnts), represented as nameplate capacity,
are summarized in thc ligure below.
Cumul.tive Nemplar€ Capaciry
GC = gas conveniion
]I!
E o -rlll m ililltl
ddp''*.od,e" d.'d d d df ddpde'dd d
370
Descriolion Yeor Capacily
Aeolus IVY to Utoh S, Expansion 2024 l,7u)
Goshen to Utah N, Expsnsion 2030 800
Yakima - to S. Oreson,/Califomia 2036 450
CP-Cases Portfolio-Developmetrt tr'act
Sheets
Retirc 2025
.n4l!-r,.o-r0.r.
o-O
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ag
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Portfolio: Jim Bridger I & 2 Retirement 2025, Jim Bridger 3 Retirement 2028, and Jim Bridger 4
Retirement 2032 (P-53CP)
PORTFOLIO ASSUMPTIONS
EstirEaeilltttwtie$
CP-Casc grrtfoliodevelopment case P-53CP is P-31 with Jim
Bridger Units l-2 retiring in 2025, Jim tlridger tlnit 3 rctiring
in 202t1. and Jim Bridger lJnit 4 retiring in 2032. Full retirement
assumptions ffe sumnrarized in the following table.
Descriotion
A variant ofcase P-53C, P-5lCP has all ofthe same retirement
assumptions exccpt was p,rocesscd through Planning and Risk
Delerministic runs l-or reliabilily beyond the C-Cascs' 2023 through
2030 ad 2038, to include 2031 tkough 2037.
t ril Descrirtn,n
Craiq I Rctirc 2025
Crais 2 Rrtirc 2026
R€tirc 2027
Retirc 2027
Rctirc 2027
Rctirc 2012
R€tirc 2012
Rclire 2031
Retire 2010
Haydcn 2
Rctirc 2042
Iluntcr 2 Rrlirc 20.t2
Hunrcr 3 Rclire 2042
Hudinglon I Rcrirc 2016
Rclir. ?036
Jim Bridrcr I Rctirc 2025
Jim Bridqcr 2 Rctirc 2025
Jim Bridscr 3 Rctirc 2028
Jim Eridscr 4 Rcrire l03l
Nruahlon I Rerire 2015
Naughton 2 Rcrir. 2025
Naushton l Lr. GC 2019 RetirE 2029
Rclirc 2039
PoRTFoLIo SUMMARY
Svstem Optimizer PYRR ($n)$2 r,479
lncrcmenlal l'ran
Resoarce Portfolio
Cumulative changes to the resource porttblio (rcw resource
additions to address kud service and reliability requirements
and resource rettements), represented as nameplate capacity,
are summarized in thc figurc below.
Cumulative Namepl.!e c.apaclty
ililrllillllil
GC = gas conversion
" -rllf
+etPd}.(r#'$d.,+"d,6Pp'de',(t+l'"df .'.f dd+t
3',72
Descriolion Yeur C'aoacily
Aeolus llY - to - Utah S, Etpqnsion 2024 I,700
Goshen - to - Utah N, Erpqnsion 2030 80()
Yahma to S. Oregon/Califomia 2037 450
CP-Cases Portfolio-Development Fact
Sheets
:
g
E
.r6r..iGr.o.loirr
( h"tt" 4 I K.1". xjlu
c6l*i.1 l R.tn. )O)7
Colstrip 4 lRcrn€202?
Dsv. JohDstoa 3 I Re!itq2!21 l
Hunter I
Huntington 2
GaJ\b! I I
Gad\bv I
I i,d<hv 1 I
Haydcn I I
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= ;3 il; ;?t..?i g?.tsf..!pi.f..
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;
=iursrE i ?:rr:l .., = 6 69-ZX,866,3 IGGeEss9l' ' i = = =, B ] Bs: r = = > >: > > >llasBSsRSEeB
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Portfolio: P-4SCNW, No New Gas Option (P-29)
R etb e m e nl As su rfi o I i o ns
No (ias-Case portfolio-development case P-29 is P45CNW
with no new gas option. Retirement assumptions are
summarized in the following table.
PoRTFoLIo ASSUMPTIoNS
Desciotion
A variant ofcase P-45CNW, P-29 is a C-Primc case and has all ofthe
same retircment 0ssumptions except was processed through Planning
and fusk De(ermidstic runs for reliability bcyond the C-Cases' 2023
through 2030 and 2038, to include 2031 through 2037. In addition, oo
oew gas resources were allowed.
Ir lt D(rcriDtion
Rclirc l0l0
Relir.2027
Rerir.2027
( railr I Relir.l0l5
Cr&ig 2 Rctire 2026
Davc Johnston I Rctirc 2027
Davc Johnslon 2 Retire 2027
D vc Johnslon l Retirc 2027
Retir€ 2027
Cadsby I Retire 2032
Cadsby 2
Gadsby 3
llayden I R€tir. 1030
Ilayden 2 Rctire 2030
Iluntcr t Retir. 2042
I{unrcr :Rctir.104:
Huntcr .1 Relirc 2042
Retift 2016
Ilunlin,rlon l Rctirc:036
Jim Dridqer I Retirc 2023
Jim Bridgcr l Relirc l028
Jim BridBcr 3 Rctirc:0-17
R.rirc 2037
Relire 2025
Relire 202J
Lc. CC 2020 RetiE 2029
Rerirc 2039
Resource Portfolio
Cumulative changes to the resourcc portfolio (new rcsource
additions to address load service and reliability requircmcnts
and rcsource retirements), represented as nameplate capacity,
are summarized in thc ligure below.
Cumulalive N.meplale Capacity (iC = gas conversion
i
!
5 --...lml
ddsdpdddd "ddd ddddddd d
.4,!'.!E!.(r.r[il
3'.7 4
Descriplion Year Cipacitr
2024 I,700Aeohs l|Y to LIkfi S, Erpansion
2030 tj00Goshen to lltoh N, Expansion
Yahma lo S. (hegon/Califomia 2033 450
No Gas-Cases Portfolio-Development
Sheets
Ponrrolro Suuua.nv
System Optimizer PVRR ($m) $21,798
ffi
I Rcrirc 2Ol2
I nuntington t
T Ji,' u.id* 4
I Naushron l
Cholla 4
Colslrip 3
Colslrip 4
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co
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=>!: ., 3 :6aad.:9:a!v t!lEriiir:l iini;.ltI]: 33333. ,=2=r='-,rl>E>?ls::s8 - 7188888:li16^6ia-/:lnlrn,)0Nel r n n tr tr'l gl n s n tr trtlidn-- I :lrrraidq,
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.i==i== ;i=r:;i=;;==sl888p3= 9183;B;3-^^.->l--;rs!r !lyliNi!l x r r, tr ql n n trtsl- -.6 d ln F :la or (n o o a d N d F N
?tal al o o o o 6to o o o o o o o o o otld d d.! d N r^l ^r d d ^
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Portfolio: P-45CNW No New Gas Option With Pumped Hydro Storage (P-29PS)
PORTFOLIO ASSUMPTIONS
Retbement Assumplions
No Gas-Case portfblio-dcvckpmcnt casc P-29PS is P-45CNW
with no new gas allowed, but adds punped hydro storage.
Retirement assumptions are summarized in thc lirllowing table.
Descrintion
A variant ofcase P-29, and a variant ofP-45CNW, P-29PS is a C-
hime case and har all ol'lie same relrrement assunptions cxccpl was
processed through Planning and Risk Deterministic runs for
reliability bcyond the C-Cases' 2021 through 2030 and 2038, to
include 2031 through 2017. In addition to no new gas resourcc
options allowed. it requircd the addition ofpumped hydro.
t ril DcscriD.iotr
Cbolla.r Relire 2020
( olslrip l Rctire 2027
R€lirc 2027
Crais I Rcliie -1025
Craig 2 R€lire 2026
Dave Johnston I Reli,e 2027
Da!. Johosion 2 Rct;rc 20?7
Dave Jobnslon 3 Rclire:0:7
Davc Johnston 4 R.rire 2017
Gadsbt/ I Retire 20ll
Carlsby 2 Rctirc l0:il
Cadsby -l Rctirc loil
Hayd€n I Retir€ 2010
Haydcn 2 Retir€ 2010
Hunrer I Retire 2042
Hunrcr 2 Rctire 2042
Hunre. :l Rctire 2042
lluntinBton I Rctirc 2036
Huntineton:Relire:0-16
Jmr Bridaer t Relire 2021
Jim B.idger 2 Rerire l0l8
Jim Brid*cr :l Relire l0l7
,im Brid*er 4 Rclire 20-17
Nnushl('n I Rcti.c l0l5
Nauehton 2 R.tire 2025
Nlughton l Le. (r 2020 R.tire 2029
Reti('20.19
PORTFoLI SuvlreRy
Svstem Ootimi:er PVRR($d $21,970
Resoarce Portfolio
Cumulative changes to the lesource portfolio (new resource
additions to address load service and reliability requirements
and res*rurce retirements), rqrrcscnted as namcplatc capacity,
are summarized in the figure below.
Cumul.tiv€ ilameplate Capacity GC = gas conversion
lll!'t--..,1fl11
dds.'f ddddddcdddddddd d
.44.!.'irft.r0'I
Descri ion Yetr Csoacitv
Aeolus W to thah S, Escpansion 2024 1,700
Goshen to Utah N, Erpansion 2030 800
37(t
No Gas-Cases Portfolio-Development Fact
Sheets
o- o\
os
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Portfolio: Energr Gateway Segment D3 (P-22)
T runsmitsion
Transmission path is shown in the map below
CASE ASSUMPTIoNS
Descrbtion
Gateway Study P-22CNW includes Segment D.3 - Populus to
Bridger/Anticline. 'lhis sensitivity is a variant ofthc preferred
portfolio, P45CNW.
PORTFOLIO SUNIMARY
Svslem Ootimizer PYRR ($m) $21.8E6
Resource Porlfofio
Cumulative changes to the resource ponfolio (new resource
additions to address load service and reliability requirements
and resource rettements), represcnted as curnulative nameplate
capacity, are summarized in dre figure below.
Cumul.tiv? Nameplate C.p.caty
E,5
a ffirilillllll" --rll
C.dF +, d f d d.g'C Pd d dC d.d C dC d
..a.'e...(1..,o'!l
"f:."-,.
Descriotion Yeur Cawci4'
2024 t,700Aeofus Wyoming to - Iltah S
Goshen to Utoh N 2030 800
Yakima- to S. Orepon/California 2037 150
Energy Gateway Portfolio-Development
Fact Sheets
I
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Portfolio: Energy Gateway Segment Dl and F (P-2J)
Cesr Assunrpuoxs
Desciolion
Gateway Snrdy P-23CNW includes all gateway options lbr
System Optimizcr to choosc. 'lhis scnsitivity is a variant ol'thc
case P-36C.
Resource Po folio
Cumulative changes to the resource portfolio (new rcsource
additioos to ad&ess load service and reliability requirements
and resource rctircments), rcprcscnted as cumulative nnmeplate
capacity, are summarized in thc figure bckrw.
Cumul.liv! N.m.pl.t. C.p.clty
,illll" -rrll t
C.fdCCCCCC PC/CCCCCC,e' C
..E.br.b,0,..
=
'f:.".-
CuoacityDescriotionYesr
Aeolus Wyominp to - Utah S 2024 1,700
Goshen to U ah N 2030 800
Yahma- to S. Orepon/(alifornia 2037 450
Energy Gateway Portfolio-Development
Fact Sheets
'l|ansmission
Transrnission path is shown in the map below
PORTFOLIO SUUMAR\.
Swtem Optimizer Pl'RR($d S22.l5l
I
380
o-
IL
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t'I,1
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=164t600 6lclooooooo
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Portfolio: Energy Gateway Segment D3, E, and H (P-25)
'l'ransmission
Transrnission path is shown in the map below
CASE ASSUMPTIONS
Desciolion
Gateway Snrdy P-25CNW includes Segment D.3 - Populus to
Bridger/Anticlinc, along with Segment Fl, Hemingway * Cedar
IIill and Seg:rent II, Boardman - Hemingway. This sensitivity
is a variant of the prel'ened portlblio, P-45CNW.
PoRTFoLIo SUMMARY
Svstem Ootimizer PVRR ($ml $22.273
Resource Po folio
Cumulative changes to the resource porttblio (new resource
additions to address load service and rcliability rcquircmcnts
and resource retirements), rcpresentcd a.s cumulativc nameplatc
capacity, are summarized in the figure below.
Cumulative Nemeplate Capacity
:!
3
E nrrilllllll
I
o -rtll
.e'dddC+"'dd.o'dddd,'o'd-"dp'dd"dt
..vi...'{r..on)o,.
3 ti2
\
Descriplion Yeqr Capacity
Aeolus ll'yoming - to - Uteh S 2024 1,700
Goshen - lo - Utah N 2030 800
Yakima- to S. Oregon/California 2018 450
Energy Gateway Portfolio-Development
Fact Sheets
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Portfolio: Energy Gateway Segment H (P-26)
Transmission
'l'ransmission path is shown in the map below
IlIPTIONS
a
Desubfion
Gateway Study P-26CNW includes Segment, Boardman -
Ilemingway. 'l-tris scnsitivity is a variant of the preferred
portfolio, P-45CI.IW.
B.iilo.ra
Resource Portfolio
Cumulative changcs to thc resource ponfolio (new resourcc
additions to address load service and reliability rcquirements
and resource retirerneflts), represented as cumulative nameplate
capacity, arc summarized in the figure below.
Cumul.tlv. N.mcpl.t. c.p:clty
! 't --...lll
C.d +r C d d p'dd.{tp C d dd dt e".d.d.d
.t.l.
..a..!el!o.,''tl
384
A€&. - addC..rA*tllD
De;cnpliott l'car e@s!itt'
Aeolus Wyoming - to - Utah S 2024 t,700
Goshen to I ltah N 2030
Energy Gateway Portfolio-Development
Fact Sheets
PORTFOLIO SUMMARY
Svstem Ootimiur PVRR (8d $2 I .579
trtrtrtrtrtrtrtr
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Sensitivity: Low Load (S-01)
Lood Forecssl
The figure below shows the base system coincident pe'ak load
forecast applicable to this case betbre accounting lbr any
potential conribution lrom DSM alongside Base Case f<rrecast.
Loads include private generation resources.
(:oincidenl Sy"stem Peak l,oad
3:
t.L.,ra
t!o@
rLaq,
tt olD
!l-aL
tL0@
ILaO0
rG0@
t-.00
9.q,o
PORTFoLIo SUMMARY
Swlem Oolimizer PI/RR ($n)s20,617
{EB.1. +Loq L6d
The figure below shows the base encrgy load forecast
applicable to this case bcfore accounting lbr any potential
contribution from DSM alongside Base Case forecast. Loads
include private generation resources.
Resource Po folio
Cumulative chauges to the rcsource portlblio (ncw resource
additions to address load service and reliability requirements
and resource retirements), rsprcsented as cumulativc nameplate
capacity, are summariz-ed in the ligure below-
System EuerSi Lo.d
]Cumul.tivc,{rmeplate c.p.city
i:t
E ililll" --rII +Ar* -.--loq L$d
dC {,'dpd d.o'd .lo1dld'o'dd.ddds' d
.^f.b.,.o.r!,..
186
Descriplion Yeot Capocib,
Aeolus Wyomitg - lo - Utah S 1,700
Goshen - to Utah N 2030 800
llalla llalla- to - Yakima 2037 200
2038Portland N Coast - to - Willameue
Yolley 450
Fact Sheets
CASE ASSUMPTIONS
Desciolion
'I hc low load lbrecast sensitivity reflects pessimistic cconomic
growth assumptions fiom IHS Global Insight and low tltah
and Wyoming industrial loads. The low and high industrial
load forecasts f<rcus o[ increased uncertainty in industrial
loads further out in timc. 'Io capture this uncertainty,
PacifiCorp modeled 1,000 possible annual loads fbr each year
based on the standard enor ofthc medium scenario regression
equation. The low industrial load lbrecast is taken liom 5tr'
pcrcentile. This scnsitivity is a variaut ol the pref'ened
portfolio, P-45CNW.
2024
Sensitivity: High Load (S-02)
Itad Forecast
The figurc below shows the base system coincident pcak load
forecast applicable lo this case before accounting lbr any
potattial contribution from DSM alongside Base Case forccast.
Loads include privatc generation rcsources.
Coiocidcot S;-slem Perk [,oad
]E
u,-a!)
ll\0@
lL.o
r2.oo
-r{D
1l,o(I,
lG.o
m.oq,
9-A
9,0o
PoRTFoLIo SUMMARY
Svstem Oolimizer PVRR ($tu $22,602
----Br* +flid Lnd
'l-tre tigure below shows the base encrgy load lbrecast
applicable to this case betbre accounting tbr any poteotial
contribution liom t)SM alongside Base Case ltrrecast. Loads
includc private generation resources.
S;-slem Euerg'- Load
Cumul.tiv. Nameplate Cipecity
.ilillillllilll
]
,
".rtl
+AE +Hi!h Lod
Cd,e'd,o'dd.aCCddCdd.dCddd
-387 -Sen^sitivity: High Load (S-02)
Descriplion Year Capucitt
Aeolus Wyoming to - thah S 2024 1,700
Gosher - to (hah N 2010 800
Yakima- to - S Oregon/Calilimia 2037 450
Sensitivitv Fact Sheets
CASE ASSUMPTIoNS
Descriolion
The high load fbrecast sensitivity reflects optinislic cconomic
growth assumptions from IHS (ikrbal Insight and low Utah
and Wyoming indusrial loads. The low and high industrial
load lbrecasts frrcus on increased uncertainty in industrial
loads furthcr out in time. To capture this unccrtainty,
PaciliCorp modeled 1.000 possible armual loads for cach year
based on the slandard error ofthe medium scenario regression
equation. lhe high industrial bad forecast is taken f'rom 95'h
percentile. 'l his sensitivity is a variatrt ofthe prelcned
podtblio, P45CNW.
Resource Portfolio
Cumulative changes to the resource portfolio (new rcvrurce
additions to address load scrvice and reliability requirements
and repurcc retirements), rcprcsented as cumulative nameplate
capacity, are summarized in the tigure below.
.^-dre- ro-rotr
Sensitivity: l-in-20 Peak Load (S-03)
CASE ASSUMPTIoNS
Desciotion
't he l-in-20 peak load sensitivity is a fivc percent probability
extreme wcather scenario. Thc I -in-20 year peak wcather is
delined as the year lbr which the peak has lhe chance of
occuring once in 20 years. This sensitivity is based on l-in-20
peak weathcr for July in each state. This semitivity is a variant
of thc prefened ponl'olio. P-45CNW.
Load Forccasl
The figure below shows thc base system coincident peak load
lbrccast applicable to this case before accormting lbr any
potential contribution from DSM alongside Base Case lbrecast.
Loads include private generation resources- Energy load
lbrccast is identical to Base Case.
tlatE
rtooo
lL<{n
lr.aq,
lL.q,
lLim
lL.o
ro,|xl,
9-<Ot
q@o
,
E
Resource Porlfolio
Cumulative chatrges to the resource portfolio (new resource
additions to address load service and reliability rcquircments
and resource rctirements), represented as cumulative nameplate
capacity, are summarized in thc figure below.
'lhe hgure below shows the base cncrgy load forecast
applicablc to this case before accounting lbr any potential
contribution liom DSM alongsidc Base Case forecast. [,oads
includc private generation resources.
( umulrtiv. Nim.pl.r. C.p.citr
lo
9
E
6
5
3
2
I
(r)
(2)
(3)
(4)
IDSM
. Edly R.[r.ment
rFOTs rcdrGG Cor!fisioo oth.r. End ofl.ife Rerircm.
s\\lc[r l]ncrgr l.orrd
388
Descriplion Yeur Capaci4'
Aeolus Wyoming - to - Utah S 2024 1,700
Goshen to Utah N 2030 800
Yakirna- to - S. Ore gon/Calitbmia 2036 450
Sensitivitv Fact Sheets
PORTFOLIO SUMMARY
System Optin izet PVRR (fin,, $21.634
('oincide]lt Svslem Perk Lord
+- Arr {- I i[ ,]0
]
----Brt +t in 'o
Sensitivity: Low Private Generation (S-04)
CASE ASSUMPTIoNS
Load Forecasl'lte figure below shows the base system coincident peak load
forccast applicable to this case belorc accounting for any
potential contribution from DSM alongside Base Case forecast.
l,oads include private generation resources.
Descriolion
Thc low private gcneration sensitivity rellecs reductions in
technology cosls, reduced technology pcrlirrmance levels, and
krwer retail electricity rates, compared to base penchation
levcls incorporating annual reductions in technology costs.
This sensitivity is a variant ofthe prefcned porlfolio, P-
45CNW.
Coiucidenl Svslem Perk Lord
PoRTFoLro Sultuenv '=
ulir@
t.lo@
lL.{n
1LUtr
ll-{lE
rLo@
liLao
rGql,
9*9
9,00
Svslem Ootimizcr PVRR l$m) $21.75E
'l he l-lgure below shows the basc energy load forccast
applicable k) this cas€ before accoulting tbr any potential
contribution l'rom DSM alongside Base Case forecast. Loads
include private genemtion resources.
S!slcm Encr$r' Lord
Cumulativc Nem.plate c.pacity
ilililllllilll
]a 'l
" -rrII
d .c,p','e'C d 4,' dd .dr' dddr-dd.dd P
rFa.f, +Los FO
389
Descriplion Yesr Copacilv
2024 I,700Aeolus Wyominz - to - Uluh S
2030 800Goshen - to Utah N
Yakima- to - S. Oregon/Calitbmia 2036 450
2037 1500
Sensitivity Fact Sheets
Resource Portfolio
Cumulative changes to thc rcsourcc portfblio (new resource
additions to address load service and reliability requirements
and resourcc retilements), rcprcscntcd as cumulative nameplate
capaciry, are summarized in the hgure below-
.,r,..b..o.,E|.
Willanette Vallc - to - S. OR/CA
-.<FBtr. +Lo$ lO
Sensitivity: Low Private Generation (S-04)
Privsle Generution
Scenario private generation pcnetuation by state and year arc
summarized in the frrlkrwing figure.
Prilale Getrrlrlloo Lo$ Penf lrailotr ('lr11r
r.500
r.000
J.100
J,(x)O
:.J00
l.000
l.r@
t.000
!00
o rtttrllll .EIIiEIIE!Ei
.UT r(OR.WA .wt' tD .CA
390
Sensitivity: High Private Generation (S-05)
Cmr AssulrprroNs
Lrad Forccast
The figure below shows the basc system coincident peak load
forccast applicable to this case bcfore accounting lbr any
potenlial contribution liom DSM alongside Base Casc l'orccast.
Loads include private generation rcsources.Dwt!@
The hipdr private generatt n scnsitivity rellecls morc
aggressive technology cost reductiotr assumptions, higher
technology performance levcls, and higher rctail clcctricity
rates, compa.red to basc pencradon levcls incorporating
annual rcductions in tecluology costs. This sensitiviry is a
variant of the preferrcd portlirlio, P45CNW.
('oincident SJ-$lem Peek Load
POnrrOuO SUMMARY
]E
Slstem Ootimizer PVRR (Snl $21.371
+B.t {rlli$ lo
Resource Porlfolio
Cumulative changes to the resource portfolio (new resource
additioru to address load service and reliability requirements
and resource retirements), represcnted as cumulativc nameplate
capacity, are summarized in the ligure betow.
The ligure below shows the basc cnergy load forecast
applicable to this case belbre accounting for auy potential
contribution liom DSM alongside Base Case fbrecast. Loads
includc private generation resouces.
Cumulatlve ilern.pl.ae Capacity
System Etrer$' Lord
ffillO -IIII ,
ddrtf,.'dCddCddCssddCCCC
..@.9'.(br6r.
-.EBre {-HiS PO
.191
Cut ocityl)escriplion
Aeolus llwmins to - [hah S 2024 t,700
Goshen to Utah N 2030 800
Sensitivity Fact Sheets
l|i(rt
11,00
1L(0
llJm
u-.o
lt a0
rq.qF
rGo@
,-qro
tr.qx,Yetr
I
t!
Sensitivity: High Private Generation (S-05)
Prlvrtc GctrcralbD - IlEh Pc[rtrraloD C[la?
6,m0
5.000
.1.000
J.@0
2.000
l.m0 ,..-iiE$EEIIEo ll
a
ttl
UT IOR.WA .WY ID .CA
392
kiysle-Cenerution
Scenario private getreration penetration by state and year are
summarized in the blbwing figure.
Sensitivity: Business Plan (5-06)
CASE AssUMPTIONS
Descriotion
The Business Plan sensitivity complies with the Utah
rcquirement to perform a business plan sensitivity consistent
with the conmission's order in Docket No. l5-035-04. Over
the tirst thee years, resources align with those assumed in
PacifiCorp's December 2018 Business Plan. Beyond the first
lhree years ofthe study period, unit retirement assumptions
are aligued with the prel'erred portfolio. All other resources are
optimized. This sensitivity is a variant of the preferrcd
ponfblio, P-45CNW.
PORTFOLIO SUNINIARY
Sv:;lem Oolimizer PVRR ($nl $21,695
Trans mission
Resource Po fofio
Cumulative changes to lhe resource portfolio (ncw rcsourcc
additions b address load scrvice and reliability requirements
and resource rettements), represetrted as cumulativc namcplate
capacity, are summarized in thc ligure below-
Cumul.tiva Nameplate Capacity
illlililll,'t -....llll
".sdpa+.pp.afd.ddd.dp'dpddd.d.dt.rtdt.d
.a-a!-r'.o-rD{ra
393
Year CapscityDesci ion
Aeolus lyyoming to - Utah S 1024 t,700
Goshen - to - Uldh N 1030 lt00
Yakimo- ro S. OR/CA, Exwnsion 2037 450
Wallo Walla- to - Yakima, Expansion 200
Fact Sheets
2038
r
t
Sensitivity: No Customer Preference (S-07)
CASE ASSUMPTIONS
Customer Preference
The figure below shows the difference between no, base and
high Customer Preference [,oad sccnarios I'or renewable
tesources.
D@
The No Customer Prelerence sensitiviry reflects no renewable
resources specifically assigned to customer preference,
compared to base renewable resource proxy options. This
sensitivity is a variant ofthe prefened portfolio, P-45CNW.
( utlomcr Pmfcno(c l.ord\
1
PORTFoLIo SUMMARY
Sr.slcm ODlimiier PrRR ($n)s2 t.609
+s lt ++ rt+t +iof +r r{ rt C r9 r+ r.} rt ++ +$ ++ +4 oi
Resource Porlfolio
Cumulative changes to the resource portfolio (new resourcc
additions to address load service and reliability requirements
and resouce rct ements), represented as cumulative nameplate
capaciry, are summarized in the ligrue below.
Cumulatlve Nameplate Cepacity
i3*-.1fl1
ttot
ddd{f,cr,'*.d1o""Op..d.d*'d"d.d.e".dp'.d
394
Description Year Cspqcilr
Aeolus Wyomins - to - Utah S 2024 1.700
Goshen - to - Utqh N 2030
Yahma- to - S. Oreeon/Califomia 2037 450
Sensitivitv Fact Sheets
800
a
rt
is
I
I
Sensitivity: High Customer Preference (S-08)
Clss AssuN{prroNS
Castomet Preference
The figure below shows the difference between no, base and
high Customer Pret'erence Load scenarios for renewable
resources.
Desctiplion
The LIigh Custorner Prelerencc sensitivity rellects higher
levels of renewable resource options assigned to customer
prelerence, courpared to base rencwable resource proxy
options. 'l his scnsitivity is a variant ofthe pret'ened ponfblio,
P45CNW.
( u\(r'nr.'r l'r!frr.n(e l-ord\
PORTF OLIO SUMNTARY
Sysrem Ontimizer PVRR ($m) $2l.6Jd
+s d ++ / d y'+" d rs C ic r, +r ++ ++ ++ +* rt ri +t
Resource Po foho
Cumulative changes to the resource portfolio (new resource
additions to address load service and reliability requiremcnts
and resource retirements), represented as cumulativc nameplate
capacity, are summarized in thc figure below.
Cumul.tive Nameplate C.paclty
3E!g
E
rt@
rl50
lq(E
tto ilililllllll" rrrrl
12,56t
Itq
(r,!@
0or@l
{'edPd,'dlao'aoradpbadp'p.$p'p.'cr"d"ddp,'e'
.* rrr .
.An!ra!!r{..O.lotx
I)escriplion Year (uput'ilt'
2024 t,700Aeolu,\ Wyoming to - Lltah S
Goshen - lo - Ulah N 800
2036Yakimr- to - S. OR./CA, Expansion 450
395
Sensitivitv Fact Sheets
2030
PA( rFrCoRP 20l9lRt)APPF:NDrX M- CAsFr lA(-r SHF.F. rs
396
P^crICoRP - 2019 IRP AppENDlx N - CAPACITy CoNTRtuu floN sTUDy
AppsNorx N -Capncrry CoNrrueurroN Sruov
In the 2017 IRP, PacifiCorp calculated peak capacity contribution values for wind and solar
resources using the capacity factor approximation method (CF Method) as outlined in a 2Ol2
report produced by the National Renewable Energy Laboratory (NREL Report)t. The CF Method
calculates a capacity contribution based on a resource's expected availability during periods when
the risk of loss ofload events is highest, based on the loss of load probability (LOLP) in each hour.
At the outset ofthe 2019 IRP, PacifiCorp calculated updated peak capacity contribution values for
an expanded range ofresources in addition to wind and solar, including:
- Energy storage, such as batteries and pumped storage,
- Demand response programs,
- Energy effrciency measures,- Combined wind and battery resources,
- Combined solar and battery resources,
- Natural gas resources.
To better account for the specific characteristics ofthe expanded range of resources considered,
the initial capacity contribution analysis was enhanced from that used in fie 2017 IRP to account
for the following:
Distinct capacity contribution values for the summer and winter peaks;
More granular analysis of LOLP event data to determine capacity contribution values
for duration-limited resources such as energy storage and intemrptible load programs;
The impact of peak-producing temperatwes on the maximum output of natural gas
plants;
Declining capacity contributions from wind and solar as penetration increases.
I Madaeni, S. H.; Sioshansi, R.; and Denholm, P. "Comparison ofCapacity Value Methods for Photovoltaics in the
Westem United Stateri." NREL/l P-6A20-54704. Denvcr, CO: National Renewable linergy Laboratory, July 2Ol2
(NREL Report) al: www.nrel.gov/docs/$ I 2osti/54704. pdf
397
Introduction
The capacity contribution ofa resource is represented as a percentage of that resource's nameplate
or maximum capacity and is a measure of the ability of a resource to reliably meet demand. This
capacity contribution affecs PacifiCorp's resource planning activities, which are intended to
ensure there is suflicient capacity on its system to meet its load obligations inclusive ofa planning
reserve margin. To ensure resource adequacy is maintained over time, all resource portfolios
evaluated in the integrated resource plan (IRP) have sufficient capacity to meet PacifiCorp's
coincident peak load obligation inclusive of a planning reserve margin throughout a 2D-year
planning horizon. Consequently, planning for the coincident peak drives the amount and timing of
new resources, while resource cost and performance metrics among a wide range of different
resource altematives drive the types of resources that can be chosen to minimize portfolio costs
and risks.
PACrr.rCoRP - 2019 IRP AppENDlx N CApACrry CoN rR.BrrTIoN SnDy
Both the CF Method and ECP Method rely on loss of load event data associated with PacifiCorp's
loads and portfolio ofresources. As such, selecting an appropriate portfolio as the basis ofthis data
is important. For the 2019 lRP, the LOLP data used in the initial CF Method is derived from the
same portfolio analysis used to select a planning reserve margin, as discussed in Volume II,
Appendix I (Planning Reserve Margin Study). Specifrcally, the LOLP data starts with the 2030
test year results. Because there are so few events in the winter in this data, their distribution appears
to be driven by random outage events more than the composition of PacifiCorp's portfolio. To
produce a more accurate winter LOLP profile, PacifiCorp replaced the winter events in the 2030
data with the distribution of winter events in the 2036 studies and prorated the results such that the
level ofoutages in the winter season was unchanged.
The ECP Method analysis demonstrates that incremental additions of solar resources have a
declining capacity contribution, and that incremental additions ofwind resources have a declining
capacity contribution. However, these effects do not occur in isolation. For instance, to the extent
the additional solar generation is reducing loss ofload events during times when wind is low, the
remaining loss ofload events may occur during times when wind generation is high, resulting in a
higher capacity contribution for wind. The portfolio impacts are highest for resources whose output
varies across the day and by season, including wind and solar as well as energy efficiency. Portfolio
impacts are also relevant to energy limited resources, including energy storage and demand
response programs. At the extreme, a portfolio with only energy storage resources has no capaciry,
since those resources would be unable to charge. In general, adding more energy resources (e.g.
wind, solar, thermal, or energy effrciency) will increase the capacity contribution of a given
penetration of energy storage resources.
While these portfolio impacts are important, it is not feasible to calculate capacity contribution
values for all resources in all possible portfolio combinations. Capacity contribution values are
intended to identify a resource's ability to avoid loss of load events, but this is just a preliminary
step in the creation of a reliable portfolio. With this outcome in mind, PacifiCorp evaluated the
reliability of every portfolio and ensured that the combination of resources in every portfolio
achieved a targeted level of reliability.
Although every portfolio is reliable, as a result of portfolio effects and reliability adjustrnents the
capacity contributions aftributable to various resource types is uncertain. To help shed light on
this, PacifiCorp conducted an additional CF Method analysis based on a 2030 test year and the P-
45CP portfotio.2 The P-45CP portfolio has significant differences llom the portfolio used in the
initial CF Method results, including additional coal retirements and significantly more wind, solar,
and energy storage resources. This final CF Method analysis provides a reasonable capacity
contribution value so long as the changes relative to the preferred portfolio are small, since in
398
The first three enhancements reflect the CF Method at a more granular level than was considered
previously. The final modification uses much of the same inputs and calculations as the CF
Method, but examines how reliability varies as a function ofchanges in the portfolio ofresources
using a more data-intensive analysis that is comparable to the equivalent conventional power
method (ECP Method) described in the NREL Report. In all cases, capacity contribution values
reflect the expected availability ofresources when the risk of loss of load events is highest.
I'fhe study for the CF Method analysis is lengthy, and there was not time to rcpeat it based on the final prefened
portlblio, which has rclatively slight difl'erences. 'l his additional CF Method analysis was not a factor in final portfblio
selection.
PA( rHCoRP - 2019IRP APPENDIX N _ CA?ACITY COMIRTBTITION STIJDY
effect, the CF Method calculates the marginal capacity contribution ofa one megawatt resource
addition. Note, this is not the same as the average capacity contribution ofeach megawatt ofthat
resource type already included in the portfolio.
The NREL Report summarizes several methods for estimating the capacity value of renewable
resources that are broadly categorized into two classes: l) reliability-based methods that are
computationally intensive; and 2) approximation methods that use simptified calculations to
approximate reliability-based results. The NREL Report references a study from Mitligan and
Parsons that evaluated capacity factor approximation methods, which use capacity factor data
among varying sets of hours, relative to a more computationally intensive reliability-based metric.
As discussed in the NREL Report, the CF Method was found to be the most dependable technique
in deriving capacity contribution values that approximate those developed using a reliability-based
metric.
As described in the NREL Report, the CF Method "considers the capacity factor ofa generator
over a subset ofperiods during which the system faces a high risk ofan outage event." When using
the CF Method, hourly LOLP is calculated and then weighting factors are obtained by dividing
each hour's LOLP by the total LOLP over the period. These weighting factors are then applied to
the contemporaneous hourly capacity factors for a wind or solar resource to produce a weighted
average capacity contribution value.
The weighting factors based on LOLP are defined as:
LOLPiwi= qjo\
where w, is the weight in hour i, LOLP, is lhe LOLP in hour i, and I is the number of hours in the
study period, which is 8,760 hours for the current study. These weights are then used to calculate
the weighted average capacity factor as an approximation of the capacity contribution as:
,U=Z
T
wiCi,
i=1
where (i is the capacity factor ofthe resource in hour i, and ('Zis the weighted capacity value of
the resource .
For fixed profile resources, including wind, solar, and energy efficiency, the average LOLP values
across all iterations are sufficient, as the output ofthese resources is the same in each iteration. To
determine the capacity contribution of fixed profile resources using the CF Method, PacifiCorp
implemented the following three steps:
A 500-iteration hourly Monte Carlo simulation ofPacifiCorp's system was produced using
the Planning and Risk (PaR) model to simulate the dispatch of PacifiCorp's system for the
399
CF Methodolosy
sample year.r This PaR snrdy is based on PacifiCorp's 2019 IRP planning reserve margin
study using a [3 percent target planning reserve margin level and the loss of load event
data reflect PacifiCorp's participation in the Northwest Power Pool (NWPP) reserve
sharing agreement, which allows a participant to receive energy from other panicipants
within the first hour of a contingency event. The LOLP for each hour in the year is
calculated by counting the number ofiterations in which system load could not be met with
available resources and dividing by 500 (the total number ofiterations). For example, if in
hour l9 on December 22nd there are three iterations with Energy Not Served (ENS) out of
a total of500 iterations, then the LOLP for that hour would be 0.6 percent.a
2. Weighting factors were determined based upon the LOLP in each how divided by the sum
of LOLP among all hours within the same summer or winter season. In the example noted
above, the sum ofLOLP among all winter hours is 58 percent.s The weighting factor for
hour l9 on December 22"d would be 1.0417 percent.6 This means that 1.0417 percent of
all winter loss of load events occurred in hour 19 on December 22"n and that a resource
delivering in only in that single hour would have a winter capacity contribution of 1.0417
percent.
3. The hourly weighting factors are then applied to the capacity factors of fixed profile
resources in the corresponding hours to determine the weighted capacity contribution value
in those hours. Extending the example noted, if a resource has a capacity factor of 41.0
percent in hour 19 on December 22'd, its weighted winter capacity contribution for that
hour would be 0.4271 percent.T
For resources which are energy limited, such as energy storage or demand response programs, the
LOLP values in each iteration must be examined independently, to ensure that the available storage
or control hours are sufficient. Continuing the example of December 22'd described above,
consider if hour l8 and hour 19 both have three ENS hours out of500 iterations. lf all six ENS
hours are in different iterations, a l-hour energy storage resource could cover all six hours.
However, ifthe six ENS hours are in the same tkee iterations in hour l8 and hour l9 (i.e. 2 hour
duration events), then a l-hour storage resource could only cover three of the six ENS hours.
The ECP Method identifies how much of a conventional resource can be removed when the
resource being evaluated (typically a renewable resource) is added, while maintaining the same
system reliability level. Unlike the CF Method, which uses the reliability results from a single
study, the ECP Method requires at least two studies. While the CF Method can produce an estimate
for any resource profile and represents a single megawatt ofresource additions, the ECP Method
I Initial CF method results were based on a composite sample year, containing ENS data fiom a 2030 study period for
June through Septernber, and data I'rom a 2036 study period tbr Ochbcr thruugh May. These time periods conespond
with the periods used to determine summcr and winter capacity contribution inputs, respectively.10.6pcrccrt = 3 / 500.
5 For each hour, the hourly LOLP is calculatcd as the numbcr of iterations with ENS divided by the totral of 500
itcrations. Thcrc arc 2tlll winter ENS itcration-hours out of total of 5,832 winter hours. As a rcsult, the sum ofLOLP
for the winter is 288 / 500 = 58 percent. There are 579 summer ENS iteration-hous out of total of 2.928 summer
hourc. As a rcsult, thc sum ofLOLP for the surnmer is 579 / 500 = t t6 percent.
6 1.04 I 7 percent = 0.6 percent / 58 percent. or simply 1.0417 percent = 3 / 2lltt.
7 0.4271 percent = 1.04t7 percent x 41.0 perctnt.
400
PACTTTCoRP - 2019 IRP AppFNr,x N - CApAClry CoNTR.BUfloN SruDy
ECP Methodoloev
P^crFrCoRr - 20 t9 IRP ApprNDx N- CAIACITy CONTRTBUTToN STUDY
produces an estimate for a specific resource profile and a specific megawatt quantity. Just like the
CF Method, the ECP Method is dependent on the composition of the starting po(folio. While the
ECP Method distills a capacity contribution down to a single value, the studies can also be used
with the CF Method to differentiate between periods and resource profiles.
At the outset of the 2019 IRP, PacifiCorp used the ECP method to evaluate wind and solar capacity
contributions in four portfolios with varying wind and solar penetrations. The results of these
studies were used to estimate the capacity contribution of the wind and solar resources in
PacihCorp's initial portfolio, as well as to estimate the capacity contributions of higher
penetrations of wind and solar capacrty.
Table N.l - ECP Method Contribution Values for Wind and Solar
This ECP analysis reflects system-wide results based on the characteristics ofexisting assets, while
capacity contribution is inherently related to the characteristics ofspecific resources. For instance,
the latest wind and solar technology may produce higher capacity factors and higher capacity
conkibutions on a per megawatt basis. To account for this, the ECP-based contribution values are
not applied directly to the future resources. Instead, the CF Method is applied to individual
resources and the results are de-rated by a uniform percentage as successive blocks are reached.
To help limit the modeling complexity. two blocks of capacity conhibution value for wind and
solar were modeled for portfolio selection. The "high" capacity contribution block allowed for up
to 2,000 megawatt (MW) of new wind capacity and 1,000 MW of new solar capacity (roughly a
50 percent increase from the initial portfolio levels). Any additional wind and solar capaciry
beyond the first block was assigned a "low" capacity contribution value, calculated based on an
additional 2,000 MW of new wind capacity and 1,000 MW of new solar capacity.
As ambient temperature rises, the maximum output from many natural gas resources declines. In
previous IRPs, the maximum output of natural gas plants was set on a monthly basis, based on
average ambient conditions at the plant site for each month. In the development of capacity
contribution values for the 20l9lRP, PacifiCorp identified a mismatch between the temperature
401
No wind or solar 0 0
No wind 0 2,2t8
No solar 3.722 0
Initial Portfolio
MW
3,722
852
2.218
955
+1000 Mw
o/o 23y:o
l5o/o
43%
l5o/o
+2000 Mw l2o/o /.-/o
+3000 Mw 60/o 0o/o
+4000 Mw lo/o Oo/o
Natural Gas Resources
Nameplate Capacif (MW)
Study Wind Solar
Capacity Contribution of Initial Portfolio
Capacity Contribution of Incremental Resources
P^crrCoRP - 2019 IRP APPINDIX N - CAPACITY CoNTRBUTION S T.UDY
underlying the maximum output of nahrral gas units and the peak-producing temperatures on the
hottest days in the summer which have the highest risk of loss ofload events and drive capacity
needs-
To better account for the capability ofnatural gas resources during peak conditions, the monthly
maximum output of existing and potential natural gas units was modified during the summer
months of July through September. During these months, the maximum output was calculated
based on peak-producing temperatures, rather than average temperatures. This reduction in the
maximum output of these resources directly impacts their summer capacity contribution, as well
as their ability to provide generation and reserves.
Table N.2 summarizes the capacity contribution inputs used in the portfolio-development process
for stand-alone renewable and storage resources, developed using the methodologies described
above.
Table N.2 - Initial Contribution Values for Solar and Sto
When wind and solar resources are combined with storage, the combined resource has a higher
capacity contribution than the renewable resource on its own. For the purposes ofthe 2019 IRP,
lithium-ion battery storage can be selected with either wind or solar resources. Combined storage
is modeled with a maximum output equal to 25 percent ofthe renewable resource nameplate and
402
Solar Block I Block 2
AYo
60/o
3o/o
sYo
3%
lYo
lo/o
2o/o
lYo
2o/o
Idaho Falls, ID
Lakeview, OR
Milford, UT
Yakima, WA
Rock Springs, WY
28o/o
29%
32o/o
25o/o
3oo/o
60%
6s%
600/o
65Yo
60%
27o/o
360/o
20o/o
35o/o
22o/o
6%
7o/o
l5o/o
4o/o
lOo/o
Block 2WindBlock I
Pocatello, ID
Arlington, OR
Monticello, UT
Goldendale, WA
Medicine Bow, WY
37%
37o/o
29%
37%
44%
4%
9%
3o/o
9Yo
4Yo
60/o
4o/o
4o/o
3%
9%
l6Yo
l2Yo
l60h
l20h
l6Yo
25o/o
l6%
l9o/o
l5o/o
38o/o
Stand-alone Storage
2 hour duration
4 hour duration
t hour duration
67%
9t%
100%
85o/o
99o/o
l00Yo
Portfolio-Development InDuts
Capacity
Factor (7o)Capacity Contribution (%)
IRP:2011 2019 2019 2019 2019
Summer/Winter:Annual Annual S w sw
20%
37o/o
l4o/o
37o/o
t7%
PA.TFICoRI - 2019 IRP AppENDrx N - C'ApACrry CoNTRIBUToN STrDy
a four-hour storage duration. This combined resource is assumed to be limited to the renewable
resource nameplate. Because of this limit to the combined ou9ut, the capacity contribution ofa
renewable and storage is not strictly additive. When renewable resource output exceeds 75 percent
during individual hours with ENS under the CF Method, the addition of the battery can only
increase the combined resource's capacity contribution to 100 percent for that hour. While such
hours are relatively uncommon, the incremental capacity from the combined battery is reduced
relative to a stand-alone battery. Table N.3 summarizes the capacity contribution inputs for
renewable resources combined with storage.
Table N.3 - Initial C Contribution Values for Wind and Solar Combined with Sto
The capacity contribution values described above are entered into the System Optimizer model, as
one ofa variety ofparameters used to select an optimized portfolio ofexpansion resources. Once
this portfolio is produced, PacifiCorp conducts a deterministic reliability assessment to assess the
reliability of the resulting portfolio. Additional details on this process are provided in the
Reliability Study Methodology section of Volume II, Appendix R (Coal Studies).
The deterministic reliability assessment identifies the quantity of incremental resources (if any)
necessary to reliably meet load and all operating reserve requirements. Ifan incremental resource
need is identified, the System Optimizer model is rerun with the abitity to add or accelerate
batteries, energy effrciency, gas peakers, and pumped hydro, relative to the pre-reliability ponfolio.
This process is analogous to the ECP Method described above in that it sets a uniform reliability
target and adds conventional resources to portfolios that do not meet the target.
While the reliability assessment ensures each portfolio is reliable, it does not identifii the individual
contributions of the resources in that portfolio. For details on the effective capacity provided by
the company's existing portfolio and new resources in the preferred portfolio, please refer to
403
Solar & Storage Block 1 Block 2
28%
29o/o
32%
25o/o
3oo/o
Idaho Falls, lD
Lakeview, OR
Milford, UT
Yakima, WA
Rock Springs, WY
48o/o
58%
42o/o
56Vo
44o/o
3lo/o
32%
40Yo
29%
35o/o
26%
27o/o
25o/o
27%
26%
260/0
26%
27%
25o/o
260/o
r ind & Storage Block 2Block I
37o/o
37Yo
29o/o
37%
44%
42o/o
55%
37%
55o/o
39o/o
47o/o
40o/o
44%
39o/o
57o/o
Pocatello, ID
Arlington, OR
\lonticello, UT
Goldendale, WA
Medicine Bow, WY
27%
260/o
260/o
26%
26%
28%
28Vo
29o/o
28%
28%
Reliabilitv Assessment
Capacity
Factor (Yo)Capacity Contribution (7o)
IRP:nla 2019 2019 2019 2019
SummerA inter:Annual S w s w
PACTHCORP - 2019 IRP APPENDIX N - C PACITY CoNTRIBT,TIoN SITIDY
Volume I, Chapter 5 (Resource Needs Assessment). To develop the results in Chapter 5,
PacifiCorp first calculated the final CF Method capacity contribution values described below for
resources other than wind and solar. Since the portfolio as a whole is reliable, the remaining
capacity up to the targeted [eve[ of reliability is attributable to wind and solar. This remaining
capacity was allocated to each wind and solar resource based on the wind and solar penetration
analysis and the final CF Method results.
PacifiCorp conducted an additional CF Method analysis during the final portfolio selection process
based on a 2030 test year and the P-45CP portfolio. The P-45CP portfolio has significant
differences from the portfolio used in the initial CF Method results, including additional coal
retirements and significantly more wind, solar, and energy storage resources. As a result ofthese
portfolio changes, the CF Method results can vary from the initial CF Method results.
The final CF Method results described below provide a reasonable capacity contribution value so
long as the changes relative to the preferred portfolio are small, since in effect, the CF Method
calculates the marginal capacity contribution ofa one megawatt resource addition. Note, this is
not the same as the average capacity contribution ofeach megawatt ofthat resource type already
included in the portfolio.
Table N.4 - Final CF Method Ca Contribution Values for Solar and S
Solar
l3o/oIdaho Falls, ID 28%l2o/o
t4%Lakeview. OR l5o/o
23%Milford. UT l0o/o
to%Yakima, WA 25%t2%
l9o/oRock Springs, WY I lo/o
Wind
l9o/oPocatello, ID 37%
2lo/oArlington, OR 37%57o/o
Monticello, UT 29o/o l8o/o
Goldendale. WA 37o/o 57o/o 21o/o
3s%Medicine Bow, WY 44%t3%
Stand-alone Storage
89o/o2 hour duration 78%
4 hour duration 94%l00o/o
t hor.rr duration 98o/o 100%
404
Final CF Method Results
Capacity Factor (7o)Capacity Contribution (%)
Summer/Winter:Annual s w
290
320
30%
27o/o
Solar & Storage
Idaho Falls, ID 28o/o 33o/o 37o/o
Lakeview, OR 29o/o 3s%390/o
32o/o 3oo/oMilford, UT 48o/o
Yakima, WA 25o/o 33o/o 34o/o
30%3lo/o 43%Rock Springs, WY
Wind & Storage
Pocatello. ID 37%5Oo/o
Arlington, OR 37%44%
29%37o/o 44o/oMonticello. UT
37o/o 7 60/o 44o/oGoldendale, WA
44%320/o 58%Medicine Bow. WY
PACTTTCoRP - 2019 IRP AppFNDLx N- CAPACITy CoN'TRTBUTION SIUDY
Table N.5 - Final CF Method Capacity Contribution Values for Wind and Solar Combined
with S
The CF Method results are derived from a one year study period (2030) and ENS events are
identified separately for every hour in that period. The details of the wind and solar resource
modeling in the study period are important for interpreting fte results. Where available, that study
includes wind and solar shapes that also reflect specific volumes for each hour in the period,
including the eflects ofcalm and cloudy days on resource output. Where data was available, the
modeled generation profiles for proxy resources are derived from calendar year 2017 hourly
generation profiles ofexisting resources, adjusted to align with the expected annual output ofeach
proxy resource- While the use ofa single historical year can produce a reasonable forecast of wind
and solar ouput, including a correlation between the two, additional work is needed in future IRPs
to explore the variation and diversity of solar and wind output, and the relationships with load,
particularly under peak load conditions.
The use of correlated hourly shapes produces variability across each month and a reasonable
correlation between resources in close proximity. It also results in days with higher generation and
days with lower generation in each month. As one would expect, days with lower renewable
generation are more likety to result in ENS events. As a result, basing CF Method capacity
contribution calculations on an average or l2-month by 24-hour forecast ofrenewable generation
will tend to overstate capacity contribution, particularly if there is a significant quantity of
resources of the same type already in the portfolio, or if an appreciable quantity of resource
additions are being contemplated.
405
Capacity Factor (7o)Capacity Contribution (7o)
Summer/Winter:Annual s w
38o/o
77%
ApprNlrxN CApi( rry (1)NrRlrJUTroN S[rDy
406
P^oFrCoRr - 2019 IRP
I'^( IlrCoR? - 2019 lI{P APPENDD( o - PRIVA IE GENERATIoN STUDY
Apps,Norx O - Pntvarr GsNERartoN Sruov
Navigant Consulting, lnc. prepared the Private Ceneration Long-Term Resource Assessment
(2019-2038) for PacifiCorp. A key objective of this research is to assist PacifiCorp in developing
private generation resource penetration forecasts to support its 2019 Integrated Resource Plan. The
purpose of this study is to project the level ofprivate generation resources PacifiCorp's customers
might install over the next twenty years.
407
Introduction
PACIIJICoRP _2OI9IR?APPLNDIX O - PRIV-rrl E GENERATION sTI IDY
408
NAV!GANT
Private Generation Long-Term Resource
Assessment (201 9-2038)
Prepared for:
Pacif iCorp
YF*s!F-!Sg"FP
August 151h,2018
Navigant Consulting, lnc.
1375 Walnut Street, Suite 100
Boulder, CO 80302
415.356.7100
navigant.com
O2018 Navigant Consulling, lnc.
Prepared by:
Jay Paidipati
Shalom Goffri
Andrea Romano
Ryan Auker
NAVIGANT
TABLE OF CONTENTS
Executive Summary..,.,..1
2
6
I
Key Findin9s....................
Report Organization ........
Private Generation Market Penetration Methodology
1.'l Methodology..8
I
I
9
0
1.2 Market Penetration Approach
1.3 Assess Technical Potential
1.5 Payback Acceplance Curves.............
1.6 Market Penetration Curves
'1.7 Key Assumptions...............
.......'10
,.,.',.12
....... 12
....... 19
1.7. 1 Technology Assumptions....................
1.7.2 Scenario Assumptions........
'1.7.3 1ncentives..............................19
1.8 Pacifi Corp Territories..................24
24
26
29
31
34
36
'1.8.1 California
1
1
1
1
1
8
III
3 Oregon.................
4 Utah.."..................
5 Washington..........
6 Wyomin9..............
APPENDIX A Customer Data................A-l
B-3
c-7
APPENDIX B. System Capacity Assumptions
APPENDIX C. Washington high+fficiency cogeneration Levelized Costs...........
C.1 Key Assumptions ........ c-7
c-8
APPENDIX D. Detailed Numeric Results D-9
D.1 Utah . D-9
D-14
D-20
o-25
D-31
D-36
D.3 Washington...
D.4 ldaho
D.5 California
D.6 Wyoming
Private Generation Long-Term Resource Assessment (2019-2038)
O2018 Navigant Consulting, lnc
Page
NAVIGANT
DISCLAIMER
This report was prepared by Navigant Consulting, lnc. (Navigant) for PacifiCorp and/or its affiliates or
subsidiaries. The work presented in this report represents Navigant's professional judgment based on he
infornation available at the tirne this report was prepared. Navigant is not responsible for the reader's use
of, or reliance upon, the report, nor any decisions based on the report.
NAVIGANT MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESSED OR IMPLIED
Readers of the reporl are advised that they assume all liabilities incuned by them, or third parties, as a
result of their reliance on the report, or the data, information, findings and opinions contained in the
report.
August 15fr, 2018
O2018 Navigant Consulling. lnc
Page iii
Private Generation Long-Term Resource Assessrnent (2019-2038)
Navigant Consulting, lnc. (Navigant) prepared this Private Generation LongFterm Resource Assessment
on behalfof Pacifcorp. ln this study privale generation (PG) sources provide custorner-sited (behind the
meter) energy generation and are generally of relatively small size, generating less than the amount of
energy used at a location. The purpose of this study is to suppod PacifiCorp's 2019 lntegrated Resource
Plan (lRP) by projecting the level of private generalion resources Pacificorp's drstomers might install
over the next twenty years under base, low, and high penetration scenarios.
This study builds on NaMgants previous assessments, 1,2 wtrich supported PacifiCorp's 2015 and 2017
lRP, incorporating updated load forecasts, market data, technology cost and perforrnance pro.iections.
Navigant evaluated five private generation tedrnologies in detail in this report:
1 . Photovoltaic (Solar) Systems
2. Small Scale Wind
3. Small Scale Hydro
4. Reciprocating Engines
5. Micrcturbines
Pro.iect sizes were determined based on average custorner load across the comrnercial, irrigation,
industrial and residential customer classes.
Private generation technical potential 3 and expecled rnarket penetration4 for each technology was
estimated for each major cuslomer class in each state in PacifiCorp's service territory. Shown in Figure
1, Pacificorp serves customers in California, ldaho, Oregon, Utah, Washington, and Wyoming.
Naviganl, Distributed Generalion Resource Assessment for Long-Term Planning Study,
htto://www oacif icoro com/contenUdam/Dac fico Sources/lnteqraled Resource Plan/20151RP/2015lRPSludy/Naviaa
Private Generalion Long-Term Resource Assessment (2019-2038)
nt Diskibuted-Gencration-Resource-Sludv 06-09-2014.pdf
' Navigant, Private Generation Long-Tem Resource Assessment (2017-2036),
httpJ^rww.pacificorp.com/contenUdam/pacificorp/doc/Energy_Sources/lntegrated_Re60urce_Plan/2017_lRP/Pacifioorp_lRP_PG_
Resource_Assessment_Final- pdf .
r Total resource potenlial factoring out resources that cannot be accessed due to non-economic reasons (i.e. land use restrictions,
siting conslraints and reguhtory prohibitions), including those specific lo each technology. Technical potential does not vary by
scenario.
i Based on economic potential (technical potentialthat can be developed because it's not more expensive lhan compeling
options). estimates the timeline associated with the diffusion of the technology into the marketplace, considering the technobgfs
relative economica, malurily, and development timelirE.
Page 1
@2018 Navigant Consulting, lnc
NAVIGANT
EXECUTIVE SUMMARY
NAVIGANT
Figure 1 Pacificorp Service Territorys
>Fta
/+
Key Findings
Using Pacificorp-specific information on custorner size and retail rates in each state and public data
sources for technology costs and perforrnance, Naviganl conducted a payback analysis and used Fisher-
Pry6 diftusion curves to determine likely market penetration for PG technologies from 2019 to 2038. This
analysis was performed for typical comrnercial, inigation, indusfial and residential PacifiCorp custorners
in each state.
ln the base scenario, Navigant estimates approximately 1.3 GW AC of PG capacity will be installed an
PacifiCorp's territory from 2019-2038.7 As shown in Figure 2, the low and high scenanos poect a
cumulative installed capacity of 0.6 GW AC and 2.3 GW AC, respectively. The main ditferences between
scenarios indude variation in technology costs, system performance, and electricity rate escalation
assumptions. These assumptions are provided in Table 8.
,..,"'
s http://www-oacificorp.aaE/contenudam/oaci paty Overview/Servlce Arca Nlap.pdf
5 Fisher-Pry are researcher6 who studi6d the oconomics of 'S-curve8', which describe how quickly product8 penetrate the ma*et.
They codified their findings based on payback period, which meagureE ho long it tak6 to recoup initial high lirgt costs with eneroy
savings over time.
7 All capacity numberE acroEs allfive resources are projected in MW-AC. FEure6 lhroughout the report are all in MW-AC.
Page 2
O2018 Naviganl Conslrlting, lnc.
Private Generation Long-Term Resource Assessrnent (2019-2038)
I l: irtuEfrrn
- r.aco.'qd ,rt
v
NAVIGANT
Figure 2 Cumulative Market Penetration Results (MW AC), 2019 - 2038
2500
==
-!
E
2000
1500
1000
500
l
"""t ""tr
pr}.E.S.$,$ re., rS ,""".P.r<P dr d,
"dr.rd) "-"+ r"*.S ,+'
.Base Case i2018
Figure 3 indicates that Utah and Oregon will drive most PG installations over the next two decades,
largely because these two states are PacifiCorp's largest markets in terms of customers and sales8.
Reference APPENDIX A for detailed state-specific customer data. ln both states, PG installations are
also driven by local tax credits and incentives. As displayed in Figure 4, solar represents the highest
expected market penetration across the five technologies examined, with residential solar developrnent
leading the way, followed by non-residential solar (comrnercial, industrial, and inigation). The Results
section of the report contains results by state and technology for the high, base, and low scenarios.
Figure 3 also mmpares this study's results to Navigants 2016 report. The three main factors that
impacted the adoption results from 2016 to 2018 include: electric rate, system cost and policy. Reference
Table 1 for a detailed comparison of the 2016 and 2018 adoption results. ln the short-term, factors
impacting adoption have a dampening effect on the market, yet rnore aggressive reduction in solar PV
system costs longer-term, result in increased adoption over time. ln 2036, the latest year in both studies,
cumulative adoption in the base case is around 1000 MW in the 2018 study and around 1200 MW an the
2016 study.
3 Th€ .eport reflects the regulatory modillcatiom to th€ PG program in Ljtah, as included in Schedule 136 (Utah Docket 'l+035-
114t
Page 3
O2018 Navigant Consulting, lnc-
Private Generation Long-Term Resource Assessrnent (2019-2038)
NAVIGANT
Figure 3 Cumulative Market Penetration Results by State (MW AC), 2019 - 2038, Base Case
'I :'- -
O<1
B
=1
o(!oIEO
0)
IE5E:
200
0
8
6
4
2
00
00
00
00
00
0
UT
-.',i -CA -r..ii
- -:..16
Figure 4 Cumulative Market Penetration Results by Technology (MW AC), 2019 - 2038, Base Case
r400
o
B:
o
-!c
E
(-)
6
I
,d".S.S d d d| rr d "S tr"* "S,S "S "S,S d d d d .,S
.Solar' Non-Residenlia
The main factors that impacted the adoption results from 2016 to 2018 include: relail rates, system cost
and policy. ln general, the rales used in this sudy changed relative to the 2016 study as PacifiCorp's
ability to calculate rnore accurate offset rates has increased. The technologies have not changed
substantially since 2016, except for solar PV, where msts have continued to decline rnore rapidly than
expected with ongoing declines expected in the future. Solar PV polacies in key states (e.9., Califomia,
Oregon, Utah and Washington) have continued to fluctuate with an impact on expected near-term and
long-term adoption. These changes between the 2016 and 2018 analysis are detailed in
Table 1 .
@2018 Navigant Consulting, lnc.
Page 4
Private Generation Long-Term Resource Assessrnent (2019-2038)
0
NAVIGANT
Table 1 Adoption Change from Electric Rate, System Cost and Policy Changes from 2016 to 2018
The impact of these factors, in aggregate, on PG adoption are shown in Figure 5. ln the short-term,
factors impacting adoption have a dampening effect on the market, yet rnore aggressive reduction in
solar PV system costs longer-term, result in increased adoption over time. ln 2036, the latest year in both
studies, cumulative adoplion in lhe base c:lse is around 1,000 lvfw in the 2018 study and around 1,200
tvlw in the 20'16 study.
Figure 5 Cumulative Market Penetration Results by Scenario (MWAC),2018 and 2016 Study
20 i6 Rates lncaeG€ (resdentel, cdrmeacl6l. mdushd)
Sdar PV Cosl D€clrnes m lie der y€ars arB mol. sustained
Pohy tl€* manddory soLr fo. n6r blrdrng is mclud€d in lh€
ID
20lt - Maftel ncreas€d lrom ,10 MW lo 90 MW
pnmenly m th€ resdenld s€ctor
Rrt€s lncroEo (rosd6nllal. cdrvnorcd. mdust d)
Soler PV Cosf Declnes rn li€ Eter years sre moro sustoined
Polrcy tlo cMng€
OR
,0!a - Merkel reman€d r65t\,€t conslsI€nl *lth
dodn)n $ftng lo latsr y€ars wtrh s€€ms
,eason6bb gircn rncontre d€clmes olrsol Dy cosl
d€cln€s m lduro y6arr
R6l€s Decr€os€ (comme.clal, rrngaton)
Sol€r PV Cosl D€clnos rn th€ laler ysars ars mors suslarn€d
Potcy lncefil!€ and cap roduced lor ros'donl€l and CEl.
Rssdonld E n6r9y Tar Cr€dn - sunssl n 2Ol 7
UT
Rat€s Rcduc€d n€l ,rEiafl,B rabs
Solar PV Cosl Doclnos rn tlt€ hlsr yoers aro mote suslan€d
Policy lnconh€ lor rosd€fillal sabr PV r€duced Lqn a2m to
ll6{D 'n
2019 declnrno b 34{D n ZU1 6nd lO bsyond. NEM
r€ducton lo arourld 9096 0l ful ml.s
Th€ r€pon reiocts fi€ r€oublory modficatoos to ti€ PG pmor*n in
uiah as nclrdod n Sci€dul€ 130 rubh Ooctol l4{Xtl la)
m:lc - Markel d€crsas€d frxn 8m MW lo 470 MW
D€cln€ s€€ms reasonatie qrcn ,6'dsnl6l
mc6nb/€ doctnes ad commercd ,at6 dochos
?0l6 Ratss Srial chanq€s d1V
Sobr PV Cosl O€clrlos rn tls Hor yeorc ars rEre suslan€d
Pollcy sobl end $nd FiT rodlr€d lal€ tor an 8 ye6rp€nod
l:r:i,l Rata Smd ch€ng€6 qry
SoLr PV Cod O€clinss rn tll€ Lter year5 tIs moro sudan€d
O20'18 Navigant Consulting, lnc
Privale Generation Long-Term Resource Assessment (2019-2038)
State Estimated Adoption Change Key Adoption Orivers
Page 5
NAVIGANT
2018 Study - Cunenl 2016 Srudy
3
o
z.s
€
o
6
B
o
:
.9?
,rt(r
o 0
.8ase Case I2018)tBage C6se (2C15r
Report Organization
The report is organized as follows:
. Private Generation Market Penelration Methodology
(O2018 Navqant Consulling. lnc.
Private Generation Long-Term Resource Assessment (201 9-2038)
Page 6
NAVIGANT
. Results
. APPENDIX A: Customer Data
. APPENDIX B: System Capacity Assumptions
e APPENDIX C: Detailed Numeric Results
Private Generation Long-Term Resource Assessrnent (2019-2038)
O2018 Navigant Consulting, lnc
Page 7
NAVIGANT
1.1 Methodology
ln assessing the technical and rnarket potontial of each private generation (PG) resource and opportunity
in Pacifcorp's service area, the study considered many key faclors, induding:
. Technology rnaturity, costs, and future cost projections
. lndustry practrces, current and expected
. Net metering policies
. Federal and state tax incentives
. Utility or third-party incentlves
. O&M costs
. Historical perforrnance, and expected performanc€ proiections
r Houdy PG Generation
r Consumer behavior and market penetration
e ln the case of Utah, the Base and High cases for 2019 and 2O2O solar PV installatbns were adjusted to reflect the capacity cap
included within Schedule '136 (Ulah Oocket 14-03$114)
Private Generation Long-Term Resource Assessrnent (2019-2038)
@2018 Navigant Consulting. lnc
Page 8
PRIVATE GENERATION MARKET PENETRATION METHODOLOGY
This section provides a high-level overview of the study methodology.
1.2 Market Penetration Approach
The following fve-step process was used to estimate the rmrket penetration of PG resources in each
scenario:
1 , Assess a Technology's Technical Potential: Technical potential is the arnount of a technology
that can be physically installed without considering economics or other barriers to custorner
adoption. For example, technical potential assurnes that photovoltaic systems are installed on all
suitable residential roofs.
2. Calculat€ Simple Payback Period for Each Year of Analysis: From past work in projecting
the penetation of new technologies, Navigant has found that Simple Payback Period is a key
indicator of custorner uptake. Navigant used all relevant federal, state, and utility incentives in its
calculation of paybacks, incorporating their projected reduction and/or discontinuation over lime,
where appropriate.
3. Project Ultimate Adoption Using Payback Acceptance Curves: Payback Acceptance
Curves estirnate the percentage of a market that will ultimately adopt a technology, but do not
factor in how long adoption will take.
4. Project Market Penetration Using Market Penetration Curves: Market penetration curves
factor in market and technology charaderistics, proiecting the adoptton tirneline.
5. Project Market Penetration under Different Scenarios. ln addilion to the base case scenario,
high and low c€se s@narios were created by varying cost, perforrnance, and retail rate
projections.e
NAVIGANT
These five steps are explained in detail in the following sections.
1.4 Simple Payback
For each customer class (i.e., residential, comrnercial, inigation and industrial), technology, and state,
Navigant calculated the simple payback period using the following formula:
Simple Paybeck Period = (Net lnitial Costs) / (Net Annual Savings)
Net lnitial C.bsts = lnstalled Cost - Federal lncsntives - Capacity-Based lncsntives'(l - Tax Rate)1o
Net Annual Savings = Annual Energy Bills Savings + (Peiomanca Based lncentives - O&M Costs - Fuoi
Costd ' 17 - Tax Rate)1o
Federal tax crediE can be taken against a system's full value if olhet (i.e. utility ot state supplied)
capacity-basod or peiormance-based incentives are consid1red taxable.
Navigant's Market Penetration model calculates lirst year simple payback assuming new
installations fot each year ol analysis.
For electic bills savinqs, Navigant conducted an 8,760-hourly analysis to consider &tual rate
schedules, actual output profiles, and demand charyes. System peiormanco assumptions are
listed in Section 1.3 above. Solar poiormanca and wind Niormance profiles were calcul ed for
representative l@ations within aach state based on the National Renewable Energy Laboratory
(NREL) System Advisory Moctel (SAM). Building lMd profiles were provided by PacifiCorp and
were *aled to match the average elscticity usage for each cuslomer class based on billing data.
i0 Applies to all non-federal incentives reoardle6s if it's comirE from the state or another state+ased entity
@20'18 Navigant Consulting, lnc.
Private Generation Long-Term Resource Assessrnent (2019-2038)
1.3 Assess Technical Potential
Each technology considered has its own characteristics and data sources that influence the technical
potential assessment; the amount of a tecfinology that can be physically installed within PacifiCorp's
service terntory without considering economics or other baniers to custorner adoplion. For this Navigant
used the number of customers, system size, and access factors by technology. Navigant escalated
technical potentials at the same rate Pacificorp proiects its sales will change over tirne. This also does
nol account for the electrical system's ability to integrate private generation.
PaOe 9
NAVIGANT
1.5 Payback Acceptance Curves
For private generation technologies, Navigant used the following payback acceptan@ curyes to model
market penetration of PG sources ftom lhe retail customer's perspective.
Figure 6 Payback Acceptance Curves
c,a
E
(!)c0)I
o
(!
l
E
(!
1000/o
90%
80%
70%
600/6
50o/o
4004
30o/o
20olo
10o/o
0%
-Comrnerclal
-lndust.ial
-Resrdenhal
0 2 68
Simple Payback (Years)
0 12 14
Source: N aviSa nt Con su lting based u pon work for variout utilities, federal Sovern ment organizations, a nd state/lo€a I organ iu ation.. The
curves were developed from customer surveys, mining ofhistoricalprogram deta, and industry interviews.
These payback curves are based upon work for various utilities, federal government organizations, and
state locrl organizations. They uere developed from custorner surveys, mining of historical program
data, and industry interviews.lr Given a calculated payback period, the curve predicts the level of
maximum market penetration. For example, if the technical potential is 100 tvlW, the Syear commercial
payback predicts that 15olo of this technical potential, or 15 MW, will ultimately be achieved over the long
term.
1.6 Market Penetration Curves
To determine the future PG market penetation within PacifiCorp's tenitory, Navigant rnodeled the growth
of Pc technologies from 2019 thru 2038. The model is a Fisher-Pry based technology adoption rnodel
that calculates the market groMh of PG technologies. lt uses a lowesl-mst approach to consumers to
develop expected market groMh cuNes based on rnaximum achievaue market penetration and market
saturation time, as def ned below.12
. Market Penetration - The percentage of a markel that purchases or adopts a specific product
or technology. The Fisher-Pry rnodel estimates the achievable market penetration based on
characteristics of the technology and industry. Market penetration orrves (sometirnes called S-
rr Payback acceptance curvbs are ba66d on a broad set of data from acrosa the United States and may not predict cuslomer
behavix in a lp6cilic marlet (e.0. utah cu6iornart may install sola- at ditreiBnt paybacks than indbated by ihe paybad(
acc€ptance cuves due io market specitic reasons).
12 MichelteHe. and irorin, 'Ove.view of New Ploduct Oifiusion Sales Foroc.cing Models provileg a gummaay of producl difturion
modele, includirl Fisher-Pry. Available:
diffusron-sales-forecastino-models odf
Page 10
O20'18 Naviganl Consultng, lnc
Private Generation Long-Term Resource Assessrnent (2019-2038)
Curves assume'10070 adoption is
never achieved due to unwillingness to
change, mistrustof a new technology,
incompatible building designs, etc
Thrs rs based upon several prior NCI
examinations of programs
4
NAVIGANT
curves) are well established tools for estimating diffusion or penetration of technologies into he
market. Navigant applies the rnarket penetration curve to the payback acceptance curye shown
in Figure 6 Payback Acceptance Curves.
Market Saturation Time - The duration in years for a technology to increase market penetration
from around 10o/o lo 8Oo/o.
The Fisher-Pry model estimates market saturation tirne based on 12 different market input factors; those
with the rnost substantial impact include:
. Payback Period - Years required for the cumulative cost savings to equal or surpass the
incrernental frst cost of equipment.
o Market Risk - Risk associated with uncertainty and instability in the rnarketplace, which can be
due to uncertainty regarding cost, industry viability, or even customer awareness, mnfidence, or
brand reputation. An example of a high market risk environment is a jurisdictron lacking long-
term, stable guarantees for incentives.
. Technology Risk - Measures how well-proven and the availability of the technology. For
example, technologies lhat are completely new to the industry have a higher risk, whereas
technologies that are only new to a specific market (or applicaton) and have been proven
elsewhere have lower risk.
Government Regulation - Measure of govemment involvement in the market. A government-
stated goal is an example of low government involvement, whereas a government mandated
minimum efficiency requirernent is an example of high involvement, having a significant ampact
on the market.
The model uses these factors to determine market growth instead of relying on individual assumptlons
about annual rnarket grovth for each technology or various supply and/or demand curves that may
sometimes be used in market penetration nrodeling. With this approach, the rnodel does not account for
other rnore qualitative limiting market factors, such as the ability to train quality installers or manufacture
equiprnent at a sufficient rate to meet the grolvth rates. Corporate sustainability, and other non-economic
groMh factors, are also not modeled.
The Fisher-Pry market groMh curves have been developed and refined over time based on empirical
adoption data for a wide range of technologies.r3 The rnodel is an imitative model that uses equations
developed from historical penetration rates of real products for over two decades. lt has been validated
in this industry via comparason to historical data for solar photovoltaics, a key focus of this shjdy.
Navigant Consulting has used gathered market data on the adoption of technologies over the past 120
years and fit the datia using Fisher-Pry curves. A key pararneter when using market penetration curves
is the assumed year of intoduction. For the market penetration curves used in this study, Navigant
assumed that the firslyear introduction occuned when the simple payback period was less than 25
years (per the pay-back acceptance curves used, this is the highest pay-back period that has any
adoplion) or when state or local incentives were first introduced.
When the above payback period, market risk, technology risk, and govemment regulation factors above
are analyzed, our general Fisher-Pry based method gives rise to tre following market penetration curves
used in this study:
rr Fisher, J. C. and R. H. Pry, "A Simple Substitution Model of Technologbal Change", Technological
Forecasting and SocialChange, 3 (March 1971), 75-88.
Page 1 1
O2018 Navigant Consulting, lnc
Private Generation Long-Term Resource Assessment (2019-2038)
NAV!GANT
100"/"
9O"/o
N"/"
70"/"
60"/"
il"/,
40"/"
fi"/"
2OY"
tlY,
o%
Figure 7 Market Penetration Curyes la
0510 152025303540
Years Shce lnlmduction
Source: Navi8ant ConsultinE, Novernb€r 2OO8 as taken from Fisher, LC. and R.H. Pry, A Simple Substitution
Model of Iech n ologica I chaiSe, rechnoloqical Forecostiag ond SooolChonqe, vol l, Pager 75 - 99, 1971.
The model is designed to analfze the adoption of a single technology entering a market and assumes
that the PG market penetration analyzed for each technology is additive because the underlying
resources limiting installations (sun, wind, water, high thermal loads) are generally mutually exclusive,
and because curent levels of market penetration are relatively low (plenty of customers exist for each
technology).
1.7 Key Assumptions
The following section details the key technology-specific and base, low and high scenario assumptions.
1 -7. 1 Tech no logy Assum ptions
The following tables sumrnarize cost and perforrmnce assumptions for each technology. System size
assumptions are provided in APPENDIX B,
l. 7. 1 - I Reciprocating Eng ines
A reciprocating engine uses one or more reciprocating pistons to converl pressure into rotating motion
ln a combined heat and power (CHP) application, a small CHP source will bum a fuel (natural gas) to
produce both electricity and heat. In many applications, the heat is transferred to water, and this hot
water is then used to heat a building. ln this study we assume the reciprocating engine generates
electricity by using natural gas as the fuel.
r{ Realized market penetration is applied to the maximum markel penetration (Figure 7) for each technology, cu6tomer payback,
and point in time. For example, a rcsilentialcGtomer with a five-year payback would tEve a matmum maftet penetration of
around 35 percent, as indicated by the residenthl payback acceptance ci.rrve (Figure 6). A technology that was introduced '10 years
ago will have realized about 20 percent of it6 maximum market penekation (Figure 7), having a market penetretion of abo.rl seven
percent of the technical potenthl.
@20'18 Naviganl Consultang, lnc
Page 12
Private Generation Long-Term Resource Assessrnent (2019-2038)
(,
6c
.!
€
!
N
a)
+ Rosidsntial
q- Non-Rosidential
NAVIGANT
Navigant sized the system to rneet the minimum cuslomer load, assuming the reciprocating engine
system \,\ould function to meet the custorner's base load. Based on system size and product availability,
reciprocating engines were assumed a reasonable technology for comrnercial and industrial customers.
Assumptions on system capacity sizes in each state are detailed in APPENDIX B. Table 2 Reciprocatng
Engine Assumptions provides the cost and performance assumptions used in the analysis and the
source for each.
Table 2 Reciprocating Engine Assumptionsl5
1. 7. 1.2 Micro-turbines
lvlicro-turbines use natural gas to start a combustor, which drives a turbine. The turbine in turn drives an
AC generator and @mpressor, and the waste heat is exhausted to the user. The device therefore
produces electrical power from the generator, and waste heat to the user. ln this study we assume lhe
micro-turbine generates electricity by using natural gas as the fuel.
Navigant sized the system to rneet the minimum custorner load, assumang the reoprocating engine
system would function to meet the custorner's base load. Based on system size and product availability,
reciprocating engines were assumed a reasonable technology for commercial and industrial customers.
Assumptions on system capacity sizes in each state are detailed in APPENDIX 8. Table 3 Micro-turbines
Assumptions provides the cost and performance assumptions used in the analysis and the source for
each.
foA Cala og of a HP -ecl.-olog,es.
lCF, Combined Heal and Po/yer Policy Analysis,C-200.201 2 002/CEC-200-20 12-002.pdf
Private Generation Long-Term Resource Assessment (2019-2038)
lnstalled Cost - 100kW $/kw $2,970 EPA, Catabg of CHP Technologies, March 2015, pg. 2-15
Change in Ahnual
ln6talled Cosl 0.40/6
Variable O&M $/tl,llvh 520
Change in AnnualO&M
Co6i
a/o -1.00/6
Fuel Cost PacifCorp
Gas Forecast PacifiCorp Forecast
Electric Heat Rale (HHVI Btu/kWh 12,637 EPA, Catalog ofCHP Technobgies, March 2015, pg 2-10
@20'18 Navigant Consllting, lnc
v/20l2oublicalions/C
Page 13
PG Resource Costs [Jnits 2019
Baseline Sources
ICF lnternational lnc., Combined Heat and Power: Policy
Analysis and 2011-2030 Maftet A$essment, pg. 92
ICF lnlernatjonal lnc-, Combined Heat and Power: Policy
Analysis and 2011-2030 Market Assessment, pg. 92
Navigant Assumption
$/t\,l\^/h
PG Performance Assumptions
NAVIGANT
Table 3 Micro-turbines Assumptionsl6
1.7.1.3 Smatl Hydro
Small hydro is the development of hydroelectric power on a scale serving a small community or industrial
plant. The detailed national small hydro studies conducted by the Department of Energy (DOE) from
20M to 2013,17 formed the basis of Navigant's snnll hydro technical potential estimate. ln the Pacific
Northwest Basan, which covers WA" OR, lD, and WY, a detailed stream-by-stream analysis was
performed in 2013, and DoE provided these data to Navigant direclly. For these states, Navigant
combined detailed GIS Pacif Corp service territory data with detailed GIS data on each stream / water
source. Using this method, Navigant could sum the technical potentials of only those streams located in
PacifiCorp's service tenitory. For the other two states, Utah and Californra, Navigant relied on an older
2006 national analysis, and multiplied the given state figures by the area served by PacifCorp within that
state. Table 4 provides the cost and perforrnance assumptions used in the analysis and the source for
each
EPA, Calalog of CHP Technolog es' :
lCF, Combined Heat and Power Policy Analysis.wlvw.enerqy.ca.qov/20l2publicalions C EC "200-2O12-OO2ICEC-2OO-2O12-002 pdl
rr Navigant used the same methodology and sources as in the 2014 study
Private Generation Long-Term Resource Assessrnent (2019-2038)
s/kw s2.685 EPA, Catalog of CHP Technologies, March 2015, pg. 5-
7lnstalled Cost - 30kW
-0.3v.ICF lnternataonal lnc-, Combined Heat and Power Policy
Anatysis and 2011-2030 Market Assessment, pg. 97
Change in Annual
lnstalled Cost
$/t\4wh $23 ICF lnternational lnc., Combined tleat and Power: Policy
Analysis and 2011-2030 Markel Assessment, pg. 97Variable o&M
Change in Annual O&M
Cost -1.Oo/o
$/N{Wh Pacificorp cas
Forecast PacifiCorp ForecastFuel Cost
15,535 EPA. Catalog of CHP Technologies. March 2015. pg. 5-6Elect,ic Heat Rate (HHV)
o2018 Naviganl Consulting, lnc.
Page 14
PG Resource Costs Units 20't9
Baseline Sources
Naviganl Assumption
PG Performance Assumptions
Btu/kWh
Table 4 Small Hydro Assumptionsls
1. 7. 1.4 Solar Photovo ltaics
Solar photovoltaic (solar) systems convert sunlight to electricity. Navigant applied a 15% discount factor
to account DC to AC conversionls. System size was then multiplied by the number of custorners and the
roof access factor. Assumptions on system capacity sizes in each state are detailed in APPENDIX B and
access factors remained consistent with the 2014 and 2016 studies. Table 5 Solar Assumptions
provides the cost and performance assumptions used in the analysis and the source for each.
'a Note: No change fro.n 20'14 sfudy.
1e Navigart used a 15olo di6count facbr to account Ior Dc to AC conversion in PV systefi8. Thi6 value is consistert with industry
standards and curr€nt Eyslem design.
Private Generalion Long-Term Resource Assessrnent (2019-2038)
lnstalled cost $/kw $4.000
Double average plant costs in'Quantifying lhe Value ol
Hydropower in the Electric Grid: Plant Cost Elemenls." Electric
Power Research lnstitute, November 2011; this accourfs for
pemitting/project costs
Change in Annual
lnstalled CoGt %0.000/"Malure technology, consistenl with olher mature technologies
in the lRP.
S/kW-yr $s2
Change in Annual OtM
Cost va -1.00k Naviganl Assumption
Capacity Factor 50'k lsok Average capacily Iaclor vaiance willbe refected in the low
and high penetralion scenarios.
O20'18 Navigant Consulting, lnc.
Page 15
NAVIGANT
PG Resource
Costs Units 2019
Baseline Sources
Fixed O&M
Renewable Energy Technologies: Cost Analysis Series.
"Hydropower." lnternational Renewable EnergyAgency, June
20't2.
PG Performance Assumptions
NAVIGANT
Table 5 Solar Assumptions
As shown in Figure 8 and Figure 9, the rapid decline in solar costs over the past decade has driven
private solar adoption across the country for all custorner classes. ln the past, these cost declines were
primarily due to reduction in the cost of equipment (e.9. panels, inverters and balance of system
components) driven by economies of scale and improvements in efficiency. Solar costs are expecled to
continue to dedine over the next decade as system efficiencies continue to increase, although these
declines are expected to occur at a slower rate than what occuned in recent years. ln the long term,
Navigant expects price reductions to decline as the industry matures and efficiency gains become harder
to achieve.
Navigant's nalional solar cost forecast indudes a low, base and high forecast. For this proiect, Navigant
developed a PacifiCorp forecast lvhich is the average between the national base and high forecast.
Navigant decided to use this forecast for California, ldaho, Oregon, Washangton and Wyoming, as all
those slates currently have srnall solar markets in PacifiCorp tenitory, resulting in less competition and
economies of scale to drive down local solar costs. For Utah, Navigant used the base cost forecasl, as
Utah has a larger and more mature private solar market.
$/KW DC UT: -$2,500
other: $2,750lnstalled cost - R€s
lhstalled Cost - Non-Res $/kw Dc All Markets:
-$1.900
-2.8ol" (Res)
-2.570 (Non-Res)
Navigant Forecasl validated by NREL, U.S.
Photovollaic Prices and Cosl Breakdownsi Q1
2017 Eenchmarks for Residential, Commercial
and Utility-Scale Systems
average ch.nge in Annual
lnstalled Cosr (2015-2034)
Fixed O&M - Res S/kW-yr National Renewable Energy Laboralory, u.S.
Residenlial Photovoltaic (PV) System Prices, Q4
m17 Benchmarks: Cash Purchase, Fair l,4arket
Value. and Prepaid Leaae Transaction Prices,
Ocl. 2014: National Renewable Energy
Laboratory, Oi6lribuled Generatbn Renewable
Energy Estimale of cosls, Accessed February 1,
20't 6
Fixed O&M - Non-Res
-1.00/o Navigant AssumptionChange in AnnoalO&M Cost
085 lndusky SlandardOC to AC Oerate Factor
O2018 Navigant Consulting lnc
Page 16
Private Generation Long-Term Resource Assessment (2019-2038)
PG Resource Costs Units 2019 Baseline Sources
NAVIGANT
Figure 8. Non-Residential Solar System Costs, 2019-2038
oG^
E83*>*O-(n
OEoo
=6ov(gG
4000
3500
3000
2500
2000
1500
1000
500
0
.uo"n&"r,S|"*1"sP"ot}"$r+""$r"tor*teorcin$},
Figure 9 Residential Solar System Costs, 2019-2038
o
E8,!*p{e(!
OL
OE!29
=;o-6c
4000
3500
3000
2500
2000
1500
1000
500
0
,$tne"r4.S"dPr4a,*'",iut$r,sror&tne"r$r$',
-Residential
- UT
-Residnetial
- Otler
The solar capacity factors (Table 5) r/vere caloJlated using NREL'S System Advisory Model for each state
territory.
O2018 Navigant Consulting, lnc.
Page 17
Private Generation Long-Term Resource Assessment (201 9-2038)
NAVIGANT
Table 6 Solar Capacity Factors2o
1.7.1.5 Small Wind
Wind power is the use of air flow through wind turbines to rnechanically power generators for electricity.
Navigant sized the wind systems at 80% of custorner load lo reduce the chance that the wind system will
produce more than the custornefs electric load in a given year. System size was then multiplied by the
number of cuslomers and the access factor. The 2014 and 2016 study access factors were used for this
study.
The following cost and performance assumptions were used in the analysis.
Table 7 Wind Assumptions
:o Navigant used a DC lo AC solar PV derate factor of 85yo.
UT 16 3%
16.80/d
14.0%
CA 16.6vo
ID 16.0'/"
Capacity
Factor
OR 12.40/o
lnstalled Cost - Res
(2.5.r okw)$/kw
s6.000lnatall.d Cost - com
(r 1-100kw)
Department of Energy, 2014 Distributed Wind Market
Report, August 2015
change in Annual
lnatalled Cost 0.0%I\lalure technology, consistent wiih olher mature
technologies in lhe lRP.
s40Fixed o&M Depanment of Energy, 2014 Distributed Wind Market
Repod, August 2015
CharEe in Annual OEI{
Cost -1.ovo Navigant Assumption
Capacity Factor zOVr (2013) -
25o/o (2034)
Small s.ale wind hub heiohts are lower, with shorter
lurbine blades, relalive lo 30% capacity factor large
scale turbines.
@2018 Navigant Consulting, lnc.
Performance Assumptions
(kw-oc/kwh ac)
Private Generalion Long-Term Resource Assessment (2019-2038)
PG Resource Costs lJnits 2019 Baseline Sources
s7.200
s/kw
PG Performance Assumptions
Page '18
1 .7.2 Scenario Assumpt ors
Navigant used the market penetration rnodel to analyze three scenarios, capturing the impact of major
changes that could affect market penetration. For lhe low and high penetration cases, Navigant varied
technology costs, system performance, and electricity rate assumptions.
Table 8 Scenario Variable Modifications
Technology cost reduction is the variable with the largest impact on rnarket penetration over the next 20
years. Average technology perforrnance assumptions are relatively constanl across states and sites.
Changes in electricity rates are modeled conservatively, reflecting the long-term stability of elecficity
rates in the United States. Navigant expects short{erm volatility for all variables but when averaged over
the 20-year IRP period, long{erm trends show less variation.
1.7.3 lncentives
Federal and state incentives are a very important PG market penetration driver, as they can reduce a
custorneis payback period signifi cantly.
The Federal Business Energy lnvestment Tax Credit (lTC) allows the owner of the system to claim a tax
credit for a certain percentage of the installed PG system price.2l The lTC, originally set to expire in 2016
for residential solar systems and reduce to 107o for commercial solar systens, was extended for solar
PV systems in December 2015 through the end of 2021, with step dowrs occurring in 2020 through
2022. The table below details how the ITC applies to the technologies evaluated in this study, however,
this schedule may change in the future.
_ Business Energy lnvestment Tax Credit,bllg.lClelqy qcvrlsaytnqs/business-enerqy-investmenltax-cred il itc
Page 19
Private Generation Long-Term Resource Assessrnent (2019-2038)
Cases Technology Cosls Performance Eleclncity Rates Other
re..ass,rr.ne20L
Asgri.s t}l ftl dELrng c.9
6 rch.!,fi! Soh. P1/ dorfi
,o.ecad ws aqd.{ n 2019a{ 2020 to llllecl rhs
. ldodoo n d oltEr Frs 6
b6.d on cuslo.rE cco.onlcs
. Assrrl.s dfams n bed
m crrsbrlr.cdrofiEsto. d. Pl/ Y!-s l-!0 SrE -
d..tE E 25!a bw lt5
lalrFbgl.s Sam 6
. Pv S.E 6 B.!.C...
0 aflyE bt.r llar
. Ft Ylrs l-r0 Srrcrs
. YEs !1. .& d&<tr
E 6Ot lttlE thrl t€s.
I! lnobiE S..E c
Rlciro.e! EnlrE 0 5!t DGlEr
lften lir. aa !.ng
rlto 5ta b.ll6 (rdi.dng *tdc
p.rtormiE! d!rtt&.r m!rr-ry)
F/Jrll(l l!( ballt (rcl5rat m&r!)
0 all,tlr hlat , lirr AssrY'es UE .'.i m.!ed{ cap
E art6,€d S.lr PV adorton
h.cc.s *6.*t'ted . U{19
. ,rb9to. n d odn rrs 6
b.s.d or custom.r .ro.ffrcs
NAVIGANT
Scenarios
8as
Cas e
Low
Attractivene!s
H€h
Atlractiveness
1.7.3.1Federal
O2018 Naviganl Consulling, lnc.
NAVIGANT
Table 9 Federal Tax lncentives
10%
10%
0%
26%
26%
0%
260/r
't0%
10o/.
00/o
22%
22%
0%
22%
0%
0%
0%
10%
0%
OYo
22%
0%
0%
o%
10%
0%
0%
0%
1.7.3.2 State
State incentives drive the local market and are an important aspect promoting PG market penetration.
Currently, all states evaluated have full retail rate net energy metering (NEM) in place for all customer
classes considered in this analysis. The study assurnes that NEM policy rernains constant, although
future uncertainty exisls sunounding NEM policy. Longer-term uncertainty also exists regarding other
state incentives. ldaho also has a local state residential personal tax deduclion for solar and wind
proiects. Currenuy, state incenlives do not exist in Califomia22 orWyoming.
The report reflects the regulatory rnodifications to the PG program in Utah, as induded in Schedule
13623. The value of generated energy takes into mnsideration the reduced compensation for exported
energy included in the tariff as well as the capacity cap (see section 1.8.4 for more detail).
The following tables detail the assumptions made regardang local state incentives.
2? ln 2007, Calitumia launched th€ Califomia Sohr lnitiative, howeve., ince. ives no longer remain in most utility tenilori€3,
htlp: csftflqqer com .
:r Utah Docket 14-03$114
O20'18 Navigant Consulting, lnc.
Page 20
Private Generation Long-Term Resource Assessment (2019-2038)
Technology 2019 2O2O 2021 2022 2023 >2023
Recip. Engines
Micro Turbines
Small Hydro
PV - Com
PV - Res
Wind - Com
Wind - Res
10%
10%
o%
30%
30v,
'12%
30%
0%
0%
0%
100/o
0o/r
0o/.
0%
NAVIGANT
Table 10 Oregon lncentives
Recip. Engines 0 U 0 0 0 0
Micro Turbines 0 0 0 0 0
Small Hydro 0 0 0 0 0 0
PV - Com ($/w)$0.50-
$0.20/w
s0.s0-
$0.2olw
$0.50-
$0.20/w
$0.s0-
$0.20/w
PV- Res ($/w) $0.55/w $0.5s/w $0.55rw $0.55/w $0.55/w $0.55/w
Wind - Com
(t/kwh)0 0 0 0 0
Wind - Res ($) 0 0
, Enersy Trust ot oreson Solar lncentive hipjf,liratts}flr,"# for resrdential).
10 10 10 10 10 10
10 10 't0 10 10 10
10 10 10 10 10 10
10 10 10 10 10 '10
$1,600 $1,600 $1,500 $1,200 $800 $400 $o
10 10 10 10 10 10 10
$0 $0 $0 $o
'Renewable Energy Systems Tax Credit, Program Cap: Residentialcap = $2,000; commercial systems <660kW,
no limit
Private Generation Long-Term Resource Assessment (2019-2038)
Technology 2019 2020 2021 2022 2023 >2023
Technolog
v
>2024201920202021202220232023
O2018 Navigant Consulting, lnc
Page 21
$0.50-
$0.20/w
30.s0-
$0.20/W
0
0 000
Recip.
Engines
v4
Micro
Turbines
(/.1
Small
Hydro (%)
PV - Com
$t
PV - Res
($r
Wind -
Com (%)
Wind -
Res ($).$1,200 $800 9400
10
't0
10
10
NAVIGANT
Table 12 Washington lncentives
Recip.
Engines 0 0 0 0 0 0
Micro
Turbines
n 0 0 0 0
Small
Hydro 0 0 0 0 0
PV - Com
(s/kwhr
$0.04
(+$0.04)
$0.02
(+$0.03)
$0.02
(+$0.02)0 0
PV - Res
($/kwh)'
$0.14
(+$0.04)
$0.12
(+$0.03)
90.10
(+$0.02)U 0 0
Wind -
Com
($/kwhr
$0.04
(+$0.04)
$0.02
(+$0.03)
$0.02
(+$0.02)0 0
Wind -
Res
($/kwhr
$0.14
(+$0.04)
$0.12
(+s0.03)
$0.10
(+$0.02)0 0 0
' Feed-in Tariff: $/kWh for allkWh generated through mid-2020: annually capped at $5,000/year,
http://programs.dslreusa. org/sy6tem/program/detaiU5698
2020
O2018 Navigant Consulting, lnc.
Technology 2019 2021 2022 2023 >2023
Private Generaton Long-Term Resource Assessrnent (2019-2038)
0
0
0
Page 22
NAVIGANT
Table 13 ldaho lncentives
Recip.
Engines 0 0 0 0 0 0
Micro
Turbines 0 0 0 0 0 0
Small
Hydro
PV - Com
0
0
0
0
0
0
0
0
0
0
0
0
PV - Res$t'40,20,20,20 40,20,20,20 10,20,20,20 40,20,20,20 10,20,20,20 10,20.20,20
Wind -
Com 0 0 0 0 0
Wind -
Res (%)-10,20,20,20 4,20,20,20 10,20,20,20 10,20,20,20 40,20,20,20 10,20,20,20
' Resllential Allernatave Energy lncome Tax Deduclion: 40olo in the firsl year and 20% for the next thr€e years,
htlpJ/programs.dsireus€.or!/system/program/detail/1 37.
Privale Generation Long-Term Resource Assessrnent (2019-2038)
Technolog
v
>202320222023
O2018 Naviqant Consulting, lnc
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2019 2020 2021
0
NAVTGANT
Navigant estimates approximately 1.3 GW of PG capacity will be installed in PacifiCorp's territory from
2019-2038 in the base case scenario. As shown in Figure 10, the low and high scenarios pro.iect a
cumulative installed capacity of 0.60 GW and 2.3 GW by 2038, respectively. The main ddvers between
the different scenanos include variation in technology costs, system performance, and electricity rate
assumptions.
Figure 10. Cumulative Market Penetration Results (MW AC), 2019 - 2038
2500
(J
B
=
o-
o
s
E
()
2000
1500
r000
500
0.s "o "\!$' "|.ov .Lsv
,.t/
as","t?^h ^b "6 .tr ^s ^q ^saoe aov asv asv .Ls, .Loe .Lo,.Lo'JL .O "-!+o' as' to'"!,ao'"d"$ dP
iBase Case (2018 )
1 .8 PacifiCorp Territories
The following sections report the results by state, providing high, base and low scenario installation
projections. Results for each scenario are also broken out by technology- The solar sector exhibits the
highest adoplion across all states. Generally non-residential solar adoption is less sensitive to high and
low scenario adjustrnents when compared to the residential sector. This is because the residential
custorner payback is more sensitlve to scenario changes (e.9. technology msts, performance, electricity
rates) when compared lo non-rcsidential sectors.
1 .8.1 California
PacifiCorp's customers in northem Califomia are projected to install about 48 lvfw of capacity over the
next two decades in the base case, averaging about 2.4 NfW, annually. California does not currenty
have any state incentives prornoting the installation of PG and the ratchetang down of the Federal ITC
lrom 2020 lo 2022 has a negative impact on annual capacity installations after 2020. The main driver of
PG in California is its high electricity rates relative to other states. Over tirne, the increase in PG
installation capacity is driven by escalating electricity rates (benchmarked to inflation) and declining
technology costs. Both residential and non-residential solar installations are responsible forthe marority
of PG groMh over the horizon of this study.
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Private Generation Long-Term Resource Assessrnent (2019-2038)
RESULTS
NAVIGANT
While the low and high scenarios follow similar rnarket trends as the base case, the cumulative
installations over the planning horizon differ significantly, as shown in Figure 11. The 48 MW from the
base case decreases by 350/o to 31 MW in the low case and increases by 40o/o lo 67 MW in the high
case.
Figure 1 1 . Cumulative Capacity lnstallations by Scenario (MW AC), California
o
=
!<)(!o-oo
o
'a(!
=E
=o
80
70
60
50
40
30
20
't0
0
,Sr*orQsPrsPr$dl?ro"rt$r*or*tne"r$n$
. Low Case (2018) r Base Case (2018) r High Case (2018)
Figure 12. Cumulative Capacity lnstallations by Technology (MW AC), California Base Case
3
6oooO
q)
(E
fEf(-)
40
30
20
0
0
not+orotrcrlncProrlror9rot"nodr+$nifre"r$nc9n$r<*n$re6r$re$
a
I
a
I
I
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Private Generation Long-Term Resource Assessrnent (2019-2038)
NAVIGANT
Figure '13. Cumulatave Gapacity lnstallations by Technology (MW AC), California High Case
^80o
E3
6oo-oo
o
gaE:,o
70
60
50
40
30
20
1 0
0
"s ^s ^\ ^1, ^t ^u ^6 ^6 ;1 ^t ^g ^O A Xl, "S ^.0. "1, ^6 A ^$.rs' .rov asv.!ov .rsP aov .}ov .rov aov ao,.Lov as' as' as' .ro' .Ls' .ro' ao' as' .ro'
a
a
ll
a
!
Figure 14. Cumulative Capacity lnstallations by Technology (MW AC), California Low Case
o
3
=
6(6o(go
o
.g
=Efo
2E
30
25
20
'15
10
5
0 F- @ O, (f - Crl <, t lO (O F- @ O) O - N (, S rO (O F- @F F - C{ C\t N (rl N N a! c\r 6l a{ (t at (., (V, (') a,) (., (t (Y,ooooooooooooooooooooooN 6l a! N 6t (\t N (\t a\r N (v (\t N N N a{ N N 6l Gl N N
t r Recip Engines
rPV-Non-Residential
.Wind - Residential
r Micro Tu rbrnes
! PV - Residen tial
a
I
1.8.2 ldaho
PacifiCorp's ldaho custorners are pro.iected to install about 108 MW of capacity over the next two
decades in the base case, averaging about 5.4 MW annually. ldaho currenUy has a Residential
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Private Generation Long-Term Resource Assessment (2019-2038)
NAVIGANT
Alternative Energy lncome Tax Deduction for residential solar and wind installations24, although this
incentive seerns lo have had minirnal impact on the market, as non-residential solar installations are
responsible for lhe maiority of PG grolvth in he early years due to a mmbination of technical potential
and escalating electric rates. The ratcheting down of the Federal ITC from 2020 to 2022 has a negative
impact on annual capacity installations in the sho( term and overtirne the increase in PG installatlon
capacity is driven by escalating electricity rates (benchmarked to inflation) and declining technology
costs.
Figure 15. Cumulative Capacity lnstallations by Scenario (MW AC), ldaho
't60o
B
to(so-(to
0)
(!
f
Efo
140
120
100
80
60
40
20
0
n$"ol,or$rcPo$r$rdtott$r*or*""+or$
r Low Case (2018) r Base Case (20 18) r High Case (2018)
1 Residential Altemative Energy lncome Tax Deduclion: 40% in the first year and 200,6 for the next three years,
htto J/oroorams.dsi reusa.o /sYslem/proqram/detai, 1 37
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Private Generation Long-Term Resource Assessment (2019-2038)
While the lowand high scenarios follow simalar market trends as the base case, the cumulative
inslallations over the planning horizon differ significantly, as shown in Figure 15. The 108 MW from the
base case decreases by 340/o to 71 MW in the low case and increases by 32o/o lo 143 MW in the high
case.
NAVIGANT
Figure 16. Cumulative Capacity lnstallations by Technology (MW AC), ldaho Base Case
o
=
zo(E6-6o
o,
F
-gfEa()
IU
00
80
50
40
20
0
,+qr&or$r$rSrS"r$r&6r$"r&s"r&qreord\ffi 1,S
. Recip Engines t Micro Tuhines
r Solar - Non-Residential . Solar - Residential
r Wind - Residential
a
I
Figure 17. Cumulative Capacaty lnstallations by Technology (MW AC), ldaho High Case
o
B
=
5(o
CL(uo
(D
(U
fElo
160
140
120
100
80
60
40
20
0
,.frotonotrol''rotro"|ro.9ro"uonSnottn"tqreor$r.SprSrda$.r&6rSr*9$
r Recip Engines . Micro Turbines
r Solar - N on-Residential . Solar - Residential
rWind - Residential
a
I
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Private Generation Long-Term Resource Assessment (2019-2038)
NAVIGANT
Figure 18. Cumulative Capacity lnstallations by Technology (MW AC), ldaho Low Case
6
=
'6
(go(go
o)
.gl
Elo
80
7o
60
50
40
30
20
10
0 f-- @ O, O - a{ o \' r() (O F @ O) O - c! (') <t lO (O N @r F r a\ (! N N C! a.l f! N C! a{ (t (' (', (, (Y) (Y, C) (O a,o o o o o o o o o o o o o a a () (f Q€) o o oa! Gl N c.l N c\t 6l a! a.l N N N a! 6t c\l N a\l N c\t N N N
r Recip Engines
t PV - Non-Residential
tWind - Residential
r Micro Tu rbines
r PV - Residential
I
a
1 .8.3 Oregon
PacifiCorp's Oregon customers are projected to install about 435 MW of PG capacity over the next two
decades in the base case, averaging about 21.75 lvTW annually. Solar is responsable for the ma.iority of
PG growth over the horizon of this study, with small growth from CHP reciprocating engines and non-
residential wind. The stronger solar resource in Oregon relative to most of other states in PacifiCorp's
territory and the Energy Trust of Oregon's Solar lncentive drive solar market adoption. The ratcheting
dolvn of the Federal ITC from 2020 lo 2022 results in a relatively flat market in the short term but
overtime the ancrease in solar capacity installation is driven by escalating electracity rates (benchmarked
to inflation) and declining technology costs.
While the low and high scenarios follow similar market trends as the base case, the cumulalive
installations over the planning horizon differ significantly, as shown in Figure 19. The 435 MW from the
base case decreases by 58o/o to 184 MW in the low case and increases by 123% to 968 MW in the high
case.
Private Generation Long-Term Resource Assessrnent (2019-2038)
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NAVIGANT
Figure 19. Cumulative Capacity lnstallations by Scenario (MW AC), Oregon
"Srtt""tr"9"$"{$"+""$"*"*cr-"*e"*$"S,r Low Case (2018) I Base Case (2018) r High Case (2018)
Figure 20. Cumulative Capacity lnstallations by Technology (MW AC), Oregon Base Case
500
450
400
350
300
250
200
150
100
50
0
"Ot"tonof
no*nollnodrot?oottnof n"oor""u"rOooClnClncfrdn$r+t$rS
I
a
I
1200
o<1
=
.=ooo-oo
o).E
o
:l
Efo
000
800
600
400
200
0
o
E
=
:a
o(Eo
(D
-qfE:fo
a
t
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Private Generation Long-Term Resource Assessrnent (2019-2038)
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NAVIGANT
Figure 21. Cumulative Capacity lnstallataons by Technology (MW AC), Oregon High Gase
1200
E
=
,-_(Joo-oO
0)
(u
:lEl()
1000
800
600
400
200
0
,o^t+or{or}rotr{or9ro"u"ro4r""r,or&qa$or$a$
r Recip Engines r Micro Tu rbines
I Solar - Non-Residential ! Solar - Residential
r Wind - Residential
r H ydro
!
Figure 22 Cumulative Capacity lnstallations by Technology (llfw AC), Oregon Low Case
250
o
=
'c,
6CLoo
o
o
E)O
200
150
100
50
0 F- @ q) O F N (Y, { rO (O F @ O) O t_ N (n 3 l.) (O N aalN N C! C! N .\I a! N C{ 6l (9 (t (t (' (.' (t (t (r' (r)o oo o o o o o o o o ooo o c)c) o o o o oN C! '! N N (\J
'! NNC{ C{NNN NNGI 6IN C! N C!
r Recip Engin es
! PV - N on-Residenlial
!Wind - Residential
r Micro Tu rbines
r PV - Residen tial
I
t
1.8.4 Utah
PacifiCorp's Utah customers are projected to install about 560 lvfw of PG capacity over the next two
decades in the base case, averaging 28 MW annually. Solar is responsible for most PG installations over
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Private Generation Long-Term Resource Assessment (2019-2038)
NAV!GANT
the horizon of this study, with reciprocating engines being installed in small numbers in future years.
Utah has the strongest solar resource in PacifiCorp's territory and system costs are lower than in other
states due to Utah's larger and rnore mature market.
The pro,ection in the eady years is dominated by residential custorners adopting solar. The state
Renewable Energy Systems Tax Credit applies to all technologies evaluated and has an impact on solar
adoption. Solar adoption declines drarnatically in 2020 as the ITC ratchets down. ln 2025 pro.iected
capacity installation increases as solar prices continue to decline and utility rates escalate (benchrnarked
to inflation).
The report reflects the regulatory modiflcations to the PG program in Utah, as included in Schedule
136.25 The value of generated energy takes into consideration the recently approved compensation for
exported energy included in the tariff. Additionally, the forecast installations for years 2019 and 2020 in
the base and high case reflects the capacity cap included within Schedule 136, while low case reflects
the assumptions as outlined in Table 1 1.
While the low and high scenarios follow similar market trends as the base case, the cumulative
installations over the planning horizon differ significanty, as shown in Figure 23. The 560 MW from the
base case decreases by 620lo to 2'13 lvlW in the low case and increases by 560/o to 879 lvlW in the high
case.
Fagure 23. Cumulative Capacity lnstallations by Scenario (MW AC), Utah
o
Bg
,6
oo(I,
O
0.)
-s=E)o
1000
900
800
700
600
500
400
300
200
100
0
,oer*or$rcPnsP"srrd"'5r*on$rotorotqrso.!$
r Lo\,! r Ease a i-'iigh
'5 Utah Docket 14-035-114
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Private Generation Long-Term Resource Assessment (2019-2038)
Figure 24. Cumulative Capacity lnstallations by Technology (MW AC), Utah Base Case
600o
=
6(5o.C'
il)
(E)
EaO
500
400
300
200
100
0
.g ^s ^\ ^.t ;5^u^b^6A^$^g^oaJt"s^!^6^6a^$
ao' aov as! aov .Lov ase asv a$e ase asv aoe as' as' .ro' .ra' ao' ao' ao' ao' ao'
r Recip Engines t Micro Turbines
rSolar- Non-Residenlial aSolar - Residential
r Wind - Residential
a
I
Figure 25. Cumulative Capacity lnstallations byTechnology (MW AC), Utah High Case
o
ts
=q
(uo
o
=(E
l
Efo
1000
900
800
700
600
500
400
300
200
100
0
"g ^o ^\ ^'t ;5 ^u ^6 ^6 ;\ "$ ^g ^S A J, "5.! ^6 ^6 A ^$as' a$v .!sv asv asv .rov aor asv asv asv .tsv .rs' ao' ao' as' a$' .!s' a$' ao' as'
r Recip Engines ! lvlicro Tu rbines
. Solar - N on-Residential . Solar - Residential
r Wind - Residential
a
I
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NAVIGANT Private Generation Long-Term Resource Assessrnent (2019-2038)
NAVIGANT
Figure 26. Cumulative Capacity lnstallations by Technology (MW AC), Utah Low Case
250()
B
=(Eo(go
o)
(,
f
El
200
150
100
50
0
,Ot""tonotrCulr"ooror|rc,*"r&todrot$"otqreor$r,Spr.Spro+a$a$trSa&$
a
a
I
a
I
1.8.5 Washington
PacifiCorp's Washington customers are expected to install about 59.6 NIW of PG capacity over the next
two decades in the base case, averaging 2.98 MW annually. Solar is responsible for most PG
installations over the horizon of this study, wih reciprocating engines being installed in small numbers in
future years. Washington does not have a very strong solar resource, yet the Iucralive Feed-ln-Tariff in
Washington, which extends through2021, should drive he solar rnarket in the near term. The solar
market is driven by non-residential solar anstallations, rnost likely due to the lower mst of installing larger
systems. Solar adoption declines dramatically in 2020 as the ITC ratchets down. ln 2025, installation
capacity increases as solar prices continue to decline and utility rates escalate (benchmarked to
inflation).
While the low and high scenarios follow similar market trends as the base case, the cumulative
installations over the planning horizon differ signifcantly, as shown in Figure 27. The 59.6 MW from the
base case decreases by 35olo to 38.5 MW in the low case and increases by 83% to 109 MW in the high
case.
Private Generation Long-Term Resource Assessrnent (2019-2038)
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NAVIGANT
Figure 27. Cumulative Capacity lnstallations by Scenario (MW AC), Washington
120o
=
=o(!o-(Eo
0).:
ol
E
=o
100
80
60
40
20
0
n+teon$neln&on&!c,*a"&"r$*e"r&*neor$r$
rLow Case (20'18) rBase Case (2018) rHigh Case (2018)
Figure 28. Cumulative Capacity lnstallations by Technology (MW AC), Washington Base Case
^70o<60
=
6(Eo-(E()
c)
-ql
Efo
50
40
30
20
0
0
"s ^o ^\ aa ^5 nu J? "() ;\ "$ "9 ^o a Jt "5 "! "b ^6 a ^$ao' asP lrov a$v.Lov.rs" asv.rsv.!$v asv.rsv ao, as, .rs, 1s' ao' .ro' .rs' ao, ,1s,
r Recip Engines a Micro Tu.bines
rSolar- Non-Residential tSolar- Residential
tWind - Residential
I
a
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Private Generation Long-Term Resource Assessnent (2019-2038)
NAVIGANT
Figure 29. Cumulative Capacity lnstallations by Technology (MW AC), Washington High Case
120
100
o
E
.--
(!o-(E
O
o
(5
El
80
60
40
20
0
,Sroto"$"cPr*orSrSn""uor$"o"uor*t*or$r r*r"
Figure 30. Cumulative Capacity lnstallations by Technology (MW AC), Washington Low Case
r Recip Engines ! Micro Tu rbanes
rSolar - Non-Residential rSolar - Residential
rWind - Residential
a Hydro
I Wnd - Non-Residential
I
=
-_oo-oO
o)
-s-ElO
45
40
35
30
20
15
10
5
0 t- @<t o - 6l(.).c(o (o F @(D o r C\t (, I(o (o l- aoe F - a! a! al a! c! a{ a! N .\r N (', ., (a (, (a (', ..) (', at(, o o oo ooo o o o oo o o o o ooo o oa\r N (\ c{ a! c\a N (\l c.l (\l a! a\i a\l ol N N N N a! (v oJ N
rRecip Engines
r PV - N on-Residental
rWind - Residential
r Micro Tu lbines
r PV - Residen tial
1.8.6 Wyoming
PacifiCorp's Wyoming customers are projected to install about 1 14 MW of capacity over the next two
decades in the base case, averaging about 5.7 MW annually- Solar is responsible for most PG
@2018 Navigant Consulling, lnc.
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Private Generalion Long-Term Resource Assessrnent (2019-2038)
7
777
NAVIGANT
installations over lhe horizon of this study, with reciprocating engines, and small wind being installed in
small numbers in future years. Wyoming does not have any state incentives prornoting the installation of
PG. Similar to other states, the ratcheting down of the Federal ITC from 2020 to 2022 has a negative
impact on annual capacity installations but in 2023 the markel begins to grow at a faster pace, driven by
escalating electricity rates (benchmarked to inflation) and declining technology costs. Both residential
and non-residential solar installations are responsible for the rna.,ority of PG growlh over the horizon of
this study.
While the low and high scenarios followsimilar market trends as the base case, the cumulative
installations over the planning horizon differ significanty, as shown in Figure 31. The 1 14 MW from the
base case decreases by 400/o to 68 MW in the low case and increases by 45% to 165 tvIW in the high
case.
Figure 31. Cumulative Capacity lnstallations by Scenario, Wyoming
o
==
=a(5
(!o
0)'-o
f
Elo
180
160
140
't20
100
80
60
40
20
0
no"n""or"+r*'r$r$r$r""r,tn$r*ono'ute"n$n$l,
t Low Case (2018)r Base Case (2018)t High Case (2018)
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Private Generation Long-Term Resource Assessment (2019-2038)
NAVIGANT
Figure 32. Cumulative Capacity lnstallations by Technology (MW AC), Wyoming Base Case
140
C)
B>'
6(6d(oo
o
=(5
l
Ea
20
100
0
60
40
20
n
^g ^o ^\ ^.1 "1 ^!. ^6 ^6 n ^$ "q ^$ a JL J5 ^.!. "$ ^6 ^1 ^$.ro' .Ls, asv aoe a$v asv.lisv .!se 1s' .!sv ao,1;s' .rs' ao' .rs' as' .ro' as' a$' .Ls'
r Recip Engines lMicroTurbines rHydro
r Solar - Non-Residenlial I Solar - Residential t Wind - Non€esidenlial
rWind - Residential
Figure 33. Cumulative Capacity lnstallations by Technology, Wyoming High Case
' 4..
Q roo
=
=6(!o-(!
O
o
-afE:fo
40
20
00
80
60
40
20
0
,o^t OonodrSPror?rof,or9r"t"ro4rotoror9reorslr reo
!Recip Engines t l\,licro Turbines
rSolar - Non-Residential.Solar - Residential
rWind - Residential
r i,ydro
I Wind - fi on -R eside ntial
Privale Generalion Long-Term Resource Assessrnent (2019-2038)
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NAV!GANT
Figure 34. Cumulative Capacity lnstallataons by Technology (MW AC), Wyoming Low Case
O
=
=(Edo
ID
SIfEfo
80
70
60
50
40
30
20
10
0 |.- co o) o - N (o <t ro (o F- @ o, o - N (.r { (o (o t- @r r F a! N N c\r N N N N N 6r (O (t (a (w, (O (a (, (i (tooooooooooooooooooooooa! N C{ C! N N N 6l N a"l N N N N N (il N 6l N N N 6r
r Recip Engines
.PV - Non-Resident al
rWind - Residential
r Micro Tu rbines
. PV - Residen tial
a
I
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NAVIGANT
Table 14 California
Residential
Commercial
lndustrial
lrrigation
35,741
7 ,262
117
1 ,841
374,836
226,557
57,571
96,201
0.166
0.1 51
0.137
o.'t32
Table 15 ldaho
Residential
Commercial
lndustrial
lrrigation
63,910
8,868
608
5,025
697,043
s17,881
1,712,919
643,3s1
0.132
0.089
0.072
0.091
Table 16 Oregon
Residential
Commercial
lndustrial
lrrigation
507,660
67 ,474
1,540
7 ,725
5,587,970
5,244,915
'1 ,700,386
332.594
0.'101
0.0 91
0.078
0.096
2018
MWh SalesRate Class Avg. Rates ($/kwh)
2018
MWh SalesRate Class # Customers
2018
MWh SalesRate Class
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Private Generation Long-Term Resource Assessrnent (2019-2038)
APPENDIX A. CUSTOMER DATA
# Customers
Avg. Rates (S/kWh)
# Customers Avg. Rates ($/kwh)
NAVIGANT
Table 17 Utah
Residential
Commercial
lndustrial
lrrigation
807,897
87 ,524
4,89?
3,249
6,824,O25
8,766,980
7,725,402
222,757
0.110
0.058
0.065
0.077
Table 18 Washington
Residential
Commercial
lndustrial
lrrigation
109,376
16,021
477
5,057
0.099
0.084
0.072
0,087
Table 19 Wyoming
Residential
Gommercial
lndustrial
lrrigation
1 15.479
23,010
?,064
764
1,016,366
1,382,275
6,878,595
24,544
0.119
0.090
0.066
0.092
Private Generation Long-Term Resource Assessment (2019-2038)
2018
MWh Sales# Customers Avg. Rates ($ikwh)
2018
MWh SalesRate Class Avg. Rates ($/kWh)
2018
MWh SalesRate Class # Customers
Page A-2
Rate Class
# Customers
1,582,882
1,528,895
753,191
160,403
Avg. Rates (t/kwh)
O2018 Navigant Consulirng, lnc
NAVIGANT
Table 20 Access Factors (%)
Recip. Engines
Micro Turbines
Small Hydro
PV - Com
PV - Res
Wind - Com
Wind - Res
N/A
N/A
N/A
42Yo
35o/o
5o/o
5o/o
N/A
N/A
N/A
420k
35o/o
5o/o
5o/o
N/A
N/A
N/A
42%
35%
8o/o
1Yo
N/A N/A
N/A
N/A
42o/o
35o/o
8%
8o/o
N/A
N/A
N/A
42%
35Yo
5'lYo
51o/o
N/A
N/A
3sak
16ak
16%
Table 21 California (kW AC)
2
?
500
18
N/A
10
N/A
N/A
N/A
N/A
29
N/A
16
NiA
N/A
N/A
N/A
N/A
6
N/A
J
28
28
500
212
N/A
113
N/A
Private Generation Long-Term Resource Assessment (2019-2038)
02018 Navigant Consulling, lnc.
Page B-3
APPENDIX B. SYSTEM CAPACITY ASSUMPTIONS
Technology CA ID OR UT WA WY
Technology Commercial lrrigation Residential lndustrial
Recip. Engines
Micro Turbines
Small Hydro
PV - Com
PV - Res
Wind - Com
Wind - Res
NAVIGANT
Table 22ldaho (kW AC)
Recip. Engines
tlicro Turbines
Small Hydro
PV - Com
PV - Res
Wind - Com
Wind - Res
4
4
500
31
N/A
29
N/A
N/A
N/A
N/A
68
N/A
62
N/A
N/A
N/A
N/A
N/A
6
N/A
6
'l8s
185
500
250
N/A
15'15
N/A
Table 23 Oreqon (kW AC)
6
o
500
)q
N/A
30
N/A
N/A
N/A
N/A
32
N/A
17
N/A
N/A
N/A
N/A
N/A
b
N/A
4
110
'110
500
100
N/A
584
N/A
Private Generation Long-Term Resource Assessment (2019-2038)
Technology
O2018 Navigant Consulting, lnc
Page B-4
Commercial lrrigation Residential lndustrial
Technology Commercial lrrigation Residential lndustrial
Recip. Engines
Micro Turbines
Small Hydro
PV - Com
PV - Res
Wind - Com
Wind - Res
NAVIGANT
Recip. Engines
Micro Turbines
Small Hydro
PV - Com
PV - Res
Wind - Com
Wind - Res
Table 24 Utah (kW AC)
7
7
500
58
N/A
56
N/A
N/A
N/A
N/A
39
N/A
N/A
NiA
N/A
N/A
N/A
N/A
5
N/A
5
150
150
500
130
N/A
938
N/A
Technology
Table 25 Washington (kW AC)
Commercial lrrigation Residential lndustrial
Recip. Engines
Micro Turbines
Small Hydro
PV - Com
PV - Res
Wand - Com
Wind - Res
6
6
500
65
N/A
41
N/A
N/A
N/A
N/A
21
N/A
13
N/A
N/A
N/A
N/A
N/A
'10
N/A
b
88
88
500
250
N/A
655
N/A
O2018 Navigant Consulting, lnc
Page 8-5
Private Generation Long-Term Resource Assessment (201 9-2038)
Commercial lrrigation Residential lndustrial
Technology
NAVIGANT
Recip, Engines
Micro Turbines
Small Hydro
PV - Com
PV - Res
Wind - Com
Wind - Res
Table 26 Wyoming (kW AC)
150
150
500
25
N/A
N/A
N/A
N/A
N/A
17
N/A
11
N/A
N/A
N/A
N/A
N/A
5
N/A
Private Generation Long-Term Resource Assessment (201 9-2038)
Technology
02018 Navigant Consulting, lnc
Commercial lrrigation Residential lndustrial
150
150
500
150
N/A
1192
N/A
Page BS
NAVIGANT
Section 480.109.100 of the Washington Administrative Code26 establishes high-efficiency cogeneration
as a form of @nservation that electric utilities must assess when identifying cost-effeclive, reliable, and
feasible conservation for the purpose of establishing 1o-year forecasts and biennial targets. To
supplement the analysis in the main body of this report addressang reliability and feasibility, this appendix,
analfzes the levelized cost of energy (LCOE) of these resour@s, for use in cost-efi-.ctiveness analysis.
Key assumptions for the analysis are presented in Table 27 and Table 28. lt is worth noting that the
LCOE c€lculation is for the electrical generation component only and the mst of the heat recapture and
recovery was taken out of the total installed system mst. Pacificorp provided the natural gas pncing and
the weighted average mst of capital (WACC) assumptions.
C.1 Key Assumptions
Table 27 Reciprocating Engines LCOE - Key Assumptions2T
!€ http://apps.leg.wa.OovMAC/def ault.aBpx?cite=480-1 0$l 00
17 EPA, Catabg of CHP Technologiesr ;
lCF. Combrncd Heat and Power Polrcy Analysis,
Private Generation Long-Term Resource Assessment (2019-2038)
lnstalled
System
cost
$2.67/W $2.77n/J $2 8B,l/v
EPA, Catalog of CHP Technologies, March
2015. pg.2-15
Assumed cosl for e leclrice I g eneration
only, system cost was reduced by 10olo to
exclude heating generalion costs.
Years 25 25
85o/oCapacity
Factot Navigant Assumptaon
Variable
o&M $/MWh s20 s20
ICF lnternetional lnc., Co.nbined Heal and
Power: Policy Analysis and 2011-2030
Market Assessrnent. pg. 92
FuelCost Si MNlBlu Pacilioorp Gas
Forccast
Pacilioorp Gas
Forecast
PacifiCorp Gas
Forecest Provided by Pacificorp
6.570/0wacc6 570/o 6.57%Provided by Pacifioorp
@20'18 Naviganl Consulting, lnc
APPENDIX C. WASHINGTON HIGH-EFFIC!ENCY COGENERATION
LEVELIZED COSTS
DG
Resource
Costs
units 2A19 2028 2038 Notes
Asset Life
85%
Page C-7
NAVIGANT
C.2 Results
The results of the LCOE analysis are presented in Table 29, with levelized costs eslimated to range from
$9ZMWh to $1 1S/lllWh over the forecast period, varying by year and technology.
Table 29 LCOE Results - Electric Component Only
:3 EPA. Catabg of CHP Technolog ies: i
lCF, Combined Heat and Power Policy Analysis,c -2oO -2O 1 2 - 0O 2 t CEC -2OG2O 1 2 -OO2 odl
Private Generation Long-Term Resource Assessrnent (2019-2038)
lnstalled
System
Cost
s2.56/W $2.55^/vsl/v 52 54,ryv
EPA, Catalog of CHP Technologies. March
2015, pg.2-'t5
Assumed cost for electrical generation
only, syslem costwas reduced by 5olo io
exclude heating generation costs.
Assel Life Years 25 Assumption
Capacity
Factor 85%85%Assumplion
Variable
oaM S/MWh $20
ICF lnlernational lnc.. Combined Heat and
Poweri Policy Analysis and 20'l'l-2030
Market Assessment, pg. 92
Fuel Cost s/[,4MBtu PacifiCorp Gas
Forecast
Pacificorp Gas
Folecasl Provided by Pacificorp
wAcc 6.570/o 6.57%
Reciprocating
Engines $/tuwh 91.1 115 0
Microturbines $/t\4wh 92.5 101 8 111.6
www enerov.ca qov/20 l20ublications/CE
Page C-8
Table 28 Micro-turbines LCOE - Key Assumptions2s
Technology U nits 2017 2026 2036
103.4
DG
Resou rce
Costs
Units 2019 2028 2038 Notes
ok
s20
Pacitioorp Ga6
Forecast
6.570/"Provided by Pacifioorp
@2018 Navigant Consulting, lnc.
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PACIFICORP _ 2OI9 IRP APPENDIX O_ PRIVAIE GENTRATION SITIDY
492
PACIFICOR-P _ 20I9 IRP APPENDIX P - R-ENEWABLE REsorJRcEs ASSESSMFNT
AppErvorx P - ReNpwABLE REsouncEs
AsspssvEur
A study on renewable resources and energy storage was commissioned to support PacifiCorp's
2019 Integrated Resource Plan (IRP). The 2018 Renewable Resources Assessment, prepared by
Bums & McDonnell Engineering Company, Inc. (BMcD) is screening-level in nature and includes
a comparison oftechnical capabilities, capital costs, and operations and maintenance costs that are
representative of renewable energy and storage technologies. BMcD evaluated energy storage
options of Pumped Hydro Energy Storage, Compressed Air Energy Storage, Lithium Ion Battery,
Flow Battery, as well as wind and solar and combinations of these resource types.
This report compiles the assumptions and methodologies used by BMcD during the Assessment.
Its purpose is to articulate that the delivered information is in alignment with PacifiCorp's intent
to advance is resource planning initiatives.
493
PACIFICORP _20I9 IRP AppFN'Drx P - RENEWABI-E RESoURCES AssEsstYtENT
494
BURNs\4sDoNNELL.
2o^18 Renewable Resources
Assessment
YPAnTFTCoRP
PacifiCorp
2018 Renewable Resources Assessment
Proiect No.109571
Revision 3
October 2Ol8
2o-18 Renewable Resources
Assessment
prepared for
PacifiCorp
2Ol8 Renewable Resources Assessment
Salt Lake City, Utah
Project No. 109571
Revision 3
October 2Ol8
prepared by
Burns & McDonnell Engineering Company, lnc.
Kansas City, Missouri
COPYRIGHT O 2OI8 BURNS & MCDONNELL ENGINEERING COMPANY, INC.
2018 Renewable Resources Assessment Revision 3 Table of Contents
TABLE OF CONTENTS
Paqe No.
,I.O INTRODUCTION ,|
I
I
2
l.l Evaluated Technologies .LZ AssessmentApproach....
I .3 Statenrent of Limitations
2.0 STUDY BASIS AND ASSUMPTIONS2.1 Scope Basis.......
2.2 CeneralAssurnptions....................
2-',|
2.3
2.4
2.5
EPC Project Indrrect Costs...........
Owner Costs......
Cost Estimate Exclusrons.............
...2-l
...2-l
...2-l
...2-2
7 _''
2.6 Operating and Maintenance Assumptions.........
3.0 SOLAR PHOTOVOLTAIC 3-1
3-l
3-1
3-2
3-2
3.1
JZ
3.3
3.4
PV
PV
PV
PV
General Description
Performance............
Cost Estimates.........
O&M Cost Estimate
4.O oN-sHoRE W|ND.............. .......4-14.1 Wind Energy General Description .................4- I
4.2
4.3
4.4
4.5
Wind Performance ............................
Wind Cost Estimate
Wind Energy O&M Estimates..........
Wind Energy Production Tax Credit
...4-l
...4-2
...4-3
...4-4
5.0 PUMPED HYDRO ENERGY STORAGE5.1 General Description...........................
5 .2 PH ES Cost Estimate ....
5-1
5-l
<t
6.0 COMPRESSED AlR ENERGY STORAGE 6-1
6-l
6-2
6-2
6.1 General Description ....6.2 CAES Cost Estimate..........6.3 CAESEmissionsControl...................
7.O
PacifiCorp Burns & i,4cDonnellI
2018 Renewable Resources Assessment Revision 3 Table of Contents
7.1.-l High Temperature Batteries.,,.,...7-2
7-3
7-3
7-4
7-4
7-5
7.2
7.3
7.4
7.5
7.6
Battery Emissions Controls...............
Battery Storage Performance............
Regulatory Trends.............................
Battery Storage Cost Estimate ..........
Battery Storage O&M Cost Estimate
8.0 coNcLUStoNs 8-l
APPENDlX A -SUMMARY TABLES
APPENDIX B - SOLAR PVSYST MODEL OUTPUT (sMW)
APPENDIX C - SOLAR OUTPUT SUMMARY
APPENDIX D - wlND PERFORMANCE INFORMATION
APPENDIX E - DECLINING COST CURVES
PacifiCorp Burns & l\rcDonnell
2018 Renewable Resources Assessment Revision 3 Study Basis and Assumptions
1.0 INTRODUCTION
PacifiCorp (Owner) retained Bums & McDonncll Engineering Company (BMcD) to evaluate various
rcncwable energy resources in support ofthe dcvelopment ofthe Owner's 2019 Integrated Resource Plan
(lRP) and associated resource acquisition portlolios and/or products. The 2018 Renewable Resources
Assessment (Asscssment) is scrccning-level in nature and includes a comparison oftechlical capabilities,
capital costs, and O&M costs that are representative ofrenewable energy and storage technologies listed
bclow.
It is thc undcrstanding of BMoD that this Assessment will bc used as preliminary information in support
ofthc Owner's long-Ierm power supply planning process. Any technologies ofinterest to the Owner
should be followed by additional detailed studics to funher investigate each tcchnology and its direct
application within the Onner's long-term plans.
't.1 Evaluated Technologies
o Single Axis Tracking Solar
o Onshore Wind
. Energy Storage
o Pumped Hydro Energy Storage (PHES)
o Compressed Air Energy Storage (CAES)
o Lithium Ion Battery
o Flow Battery
. Solar + Energy Storage
o Wind + Energy Storage
1,2 AssessmentApproach
This rcport accompanies thc Rcnewable Resources Assessmcnt spreadsheet files (Summary Tables)
provided by BMcD. Thc Summary Tables are brokcn out into three separate files for Solar, Wind, and
Encrgy Storagc options. The costs are expressed in mid-2018 dollars for a fixed price, tum-kcy resource
implementation. Appendix A includes the Summary Tables.
This report compiles the assumptions and methodologies used by BMcD during the Assessment. Its
pupose is to aniculate that the dclivered information is in alignment with PacifiCorp's intent to advance
its resource planning initiatives.
PaciliCorp 1-1 Bums & l\4cDonnell
2018 Renewable Resources Assessment Revision 3 Study Basis and Assumptions
1.3 Statement of Limitations
Estimates and proiections prepared by BMcD relating to performance, construction costs, and operating
and maintenancc costs are based on experience, qualihcations, andjudgment as a prolessional consultant.
BMcD has no control over weathcr, cost and availability oflabor, matcrial and equipment, labor
productivity, construction contractor's procedures and methods, unavoidable delays, construction
contractor's method of determining prices, economic conditions, govemmcnt regulations and laws
(including interprctation thereof), competitive bidding and market conditions or other faclors affccting
such estimates or projections. Actual rates, costs, perfonnancc ratings, schedules, etc., may vary from thc
data provided.
1-2 Burns & McDonnellPacifrCorp
2,0 STUDY BAS]S AND ASSUMPTIONS
2.1 Scope Basis
Scope and economic assumptions used in developing the Assessment are presented below. Key
assumptions arc listed as footnotes in the summary tables, but the following expands on those with greater
detail for what is assumed for thc various tcchnologics.
. All estimatcs are screening-level in nature, do not reflect guaranteed costs, and are not intended
for budgctary purposes. Estimates concentrate on differential values between options and not
absolute information.
o All information is prcliminary and should not bc used for construction purposcs.
. All capital cost and O&M estimates are stated in mid-20ltl US dollars (USD). Escalation is
cxcludcd.
. Estimates assumc an Enginccr, Procuc, Construct (EPC) fixed price contract for project
execution.
. Unless statcd otherwise, all wind and solar options are based on a generic site with no existing
structurcs or underground utilities and with sufficient area to receive, assemble and temporarily
store construction material. Battery options are assumed to be located on existing Owncr land.
. Sites are assumcd to be flat, with minimal rock and with soils suitable for spread footings.
. Wind and solar technologies were evaluated across five states within Owner's service areas:
Washington, Oregon, Idaho, Utah, and Wyomrng. The specific locations within each state for
potential wind/solar sitcs were determined by Owner.
. All performance estimates assume new and clean equipment. Operating degradation is excluded
o Elcctrical scope is assumed to end at the high side of the generator step up translormer (GSU)
unless otherwisc specilied in the summary table (most notably for CAES and PHES).
. Demolition or removal ofhaiardous materials is not included.
2.3 EPC Project lndirect Costs
The following proiect indircct costs arc includcd in capital cost estimates
o Construction/startup tcchnicalservice
. Engineering and construction management
201 I Renewable Resources Assessment Revision 3 Study Basis and Assumptions
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2.2 GeneralAssumptions
The assumptions below govem the overall approach ofthe Assessment:
201 8 Renewable Resources Assessment Revision 3 Study Basis and Assumptions
. Freight
. Startup spare parts
. EPC fccs & contingcncy
2.4 Owner Costs
Allowances for Owner's costs are included in the pricing estimates. The cost buckets for Owner's costs
varies slightly by technology, but is broken out in the summary tables in Appendix A.
2.5 Cost Estimate Exclusions
The following costs are excluded from all estimates
r Financing fees
o Intcrcst during construction (lDC)
o Escalation
. Pcrformancc and paymcnt bond
. Sales tax
. Property taxes and insurance
. Off-sitcinfrastructure
. Utility dcmand cosls
o Decommissioningcosts
. Salvage values
2.6 Operating and Maintenance Assumptions
Operations and maintenance (O&M) estimates are based on the following assumptions
o O&M costs arc based on a greenfield facility with new and clean equipment.
o O&M costs are in mid-2018 USD.
. Property taxes allowance included for solar and onshore wind options.
. Land lease allowance included for PV and onshore wind options.
. Li-Ion batlcry O&M includes costs for additional cells to be added ovcr time.
PaciriCorp Burns & McDonnell
3.0 SOLAR PHOTOVOLTAIC
This Assessment includes 5 MW, 50 MW, and 2fi) MW singlc axis tracking photovoltaic (PV) options
cvaluated at five locations wilhin the PacifiCorp services area.
3.1 PV General Description
The conversion ofsolar radiation to useful energy in the form ofelectricity is a mature concept with
cxtcnsive commercial expcrience that is continually developing into a diverse mix oftechnological
designs. PV cells consist ofa base matcrial (most commonly silicon), which is manufactured into thin
slices and then layered with positively (i.c. Phosphorus) and negatively (i.e. Boron) charged materials. At
the junction ofthese oppositely charged materials, a "deplction" layer forms. When sunlight strikcs thc
cell, the separation ofcharged particles generates an electric ficld that forces current to flow from thc
negativc material to thc positivc matcrial. This flow ofcurrent is capturcd via wiring connected to an
electrode array on one side ofthe cell and an aluminum back-plate on the other. Approximately I5% of
the solar energy incident on the solar cell can be convcrtcd to electrical energy by a typical silicon solar
ccll. As the cell ages, the conversion efficiency degrades at a ratc olapproximately 2% in the first ycar
and 0.5olo per year thcrcaftcr. At the cnd of a typical 30-year period, the convcrsion efficiency ofthe cell
will still be approximately 80% of its initial cfficicncy.
3.2 PV Performance
BMcD pulled Typical Meteorological Year (TMY) weathcr data for each site to determine expcctcd
hourly irradiance. BMcD then ran simulations ofeach PV option using PVSYST software. The resultant
capacity factors for single axis tracking systems are shown in the Summary Tablcs. Inverter loading ratios
(ILR) for each base plant nominal output al the point ofclcctrical interconnect are indicated in Tablc 3-1.
Table 3-1: lnverter Loading Ratios in Assessment
Nominal Output Single-Axis Tracking
(sAT) Dc/Ac Ratio
5MW 7.32
50 MW t.46
2OO MW t.46
There arc different pancl technologics which may exhibit diflerent perlormancc characteristics depending
on the site. This assessment assumes poly-crystallinc panels. The altemative, thin film tcchnologics, are
typically cheaper per panel, but they are also less energy densc, so it's Iikely that more panels would be
required to achicvc thc samc output. ln addition, the tr.vo technologies respond diffcrently to shaded
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2018 Renewable Resources Assessment Revision 3 Solar Photovoltaic
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201 I Renewable Resources Assessment Revision 3 Solar Photovoltaic
conditions. The nxo technologies are also impacted differently by current solar tariffs which has also
impacted availability of the two.
Appendix B shows the PVSYST model output lor a 5 MW block with the input assumptions, losses, and
output summary. Appendix C shows an additional output summary page uniquc for cach solar option size
and location. TMY data for each sitc as well as PVSYST 8760 ouputs arc provided to accompany this
report outside of the formal rcport appendices.
3.3 PV Cost Estimates
Cost cstimates were developed using in-housc information based on BMcD projcct cxperience as an EPC
contractor as well as an Owner's Engincer lor EPC solar projects. Cost estimatcs assume an EPC projcct
plus typical Owner's costs. A typical solar project cash flow is included in Appendix F.
PV cost estimates for the singlc axis tracking systems are included rn the Summary Tables. Costs arc
based on thc DC/AC ratios in Table 4-l abovc, and $/kW costs, based on the nominal AC output, are
shown in Appendix A. The project scopc assumcs a medium voltage interconncction for the 5 MW
options, and a high voltage interconnection for thc 50 and 2(X) MW options. Owncr's costs include a
switchyard allowance for the larger scalc options, but no transmission upgradc costs or high voltage
transmission interconnect line costs arc included.
PV installed costs have steadily declincd lor years. The main drivers ofcost decrcases include substantial
module price reductions, lowcr inverter prices, and higher modulc cfficiency. However, recent US tariffs
havc had an impact on PV panels and steel imports. Pricing in the summary tablc is based on actual
competitive EPC market quotes since thcse tariffs have been in place to takc into account this impact. Thc
panel tariffs only impact crystalline solar modules, however thc availability of CdTe is limited for the
next couplc years, so it is prudent to assumc similar cost increases for thin film pancls until the impacts of
the tariff are clearer.
The 201ll Assessment excludes land costs from capital and Owner costs. It is assumed that all PV projects
will be on leased land with allowances provided in the O&M costs.
3.4 PV O&M Cost Estimate
O&M costs for thc PV options are shown in the Summary Tablcs. O&M costs are derived from BMcD
project experience and vendor information. Thc 2018 Assessment includes allowanccs for land lease and
property tax costs-
PacifiCorp Burns & McDonnell
The following assumptions and clarifications apply to PV O&M:
o O&M costs assume that the system is remotely opcrated and that all O&M activitics are
performed through a third-party contract. Thereforc, all O&M costs are modeled as fixed costs,
shown in terms of $MM per year.
o Land lcase and propcrty tax allowalces arc included based on in housc data fiom previous
projects.
. Equipment O&M costs are included to account for invertcr maintenance and other routine
equipment inspections.
. BOP cosls are included to account for monitoring & security and site maintcnance (vegetation,
fencing, etc.).
. Panel cleaning and snow removal arc not included in O&M costs.
. The capital replacement allowance is a sinking firnd lor inverter replacements, assuming they will
be replaccd once during the project life. It is a l5-year levelized cost bascd on the current invertcr
capital cost.
The storage system is assumed to be electrically coupled to the PV system on thc AC side, meaning the
PV and storage systems havc separate inverters. However, there are use cascs such as PV clipping that
may bc bctter served by a DC-DC conncction. In a DC coupled sysrem, the storage side would have a
DC-DC voltage converter and conncct to the PV system upstrcam olthe DC-AC invcrters. For a clipping
application, a DC-DC conncction allows the storagc system to caphlre the DC output from the PV
modulcs that may have otherwise been clipped by the inverters. Furthcr study beyond the scope of this
assessment would be required to determine the best electrical design for a particular application or site,
but at this level of study, the capital coss provided are expccted to be suitable for cither AC or DC
coupled systems.
Capital costs are show as add-on costs, brokcn out as proiect and owncr's cosls. These reprcscnt the
additional capital above the PV base cost, intended to capturc modest savings to accounl for shared
system costs such as transformcr(s) and switchgear. In addition, overlapping owner costs are eliminatcd
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2018 Renewable Resources Assessment Revision 3 Solar Photovoltaic
3.5 PV Plus Storage
The PV plus storage options combine the PV technology discussed in section 3.0 with the lithium ion
battcries described in scction 7,0. Thc battery storage size is set at approximately 25% ofthc total
nominal output olthe base solar options, with options for two, four, and eight hours ofstorage duration.
20 1 I Renewable Resources Assessment Solar Photovoltarc
or reduced. Finally, a line for O&M add-on costs is also included which can be added with the base PV
O&M costs to determinc overall facility O&M.
As with the Li-lon battery options, the colocated storagc option assumes an operation profile ofone
cycle per day, which is used for calculating the O&M costs.
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Revision 3
4.0 ONSHORE WIND
4.'l Wind Energy General Description
Wind turbines convcrt thc kincaic cnergy of wind into mechanical cncrgy, which can be used to gencratc
electrical cncrgy that is supplied to the grid. Wind turbine energy conversion is a mature technology and
is generally grouped into two t)?es of configurations:
Over 95 percent of turbines over 100 kW arc horizontal-axis- Subsystems for cithcr configuration
typically include the following: a blade/rotor asscmbly to convert the energy in the wind to rotational
shaft energy; a drive train, usually including a gearbox and a generator; a tower that supports thc rotor and
drivc train; and other equipment, including controls, electrical cablcs, ground support equipment and
interconnection equipment.
Appendix D includes NREL wind resourcc maps for Idaho, Oregon, Utah, Washington, and Wyoming
with the locations ofinterest marked as provided by Owncr.
4.2 Wand Performance
This Assessment includes 200 MW onshore wind gcncrating facilities in Idaho, Oregon, Uoh,
Washington, and Wyoming service areas. BMcD relied on publicly available data and propnetary
computational programs to complete thc nct capacity factor characterization. Ccncric project locations
wcre selected within the area specified by Owner.
The Vestas Vl36-3.6 and GE3.8-137 wind turbine models werc assumed for this analysis. The respective
nameplate capacity, rotor diameter, and a hub hcight are provided in the Table 4- I . Thc maximum tip
height olthis packagc is undcr 500 feet, which means lhere are less likcly to bc conflicts with the Federal
Aviation Administration (FAA) altitudes availablc lor general aircraft. A generic powcr ctrvc at standard
atmospheric conditions for each ofthe sites was assumed for the Vl36-3.6 and GE3.8-t37. Notc that this
turbinc is intended only to bc representative ofa typical Intemational Electrotechnical Commission wind
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2018 Renewable Resources Assessment On-Shore WindRevision 3
. Vcnical-axis wind turbincs, with thc axis ofrotation perpendicular to thc ground.
. Horizontal-axis wind turbines, with thc axis ofrotation parallel to the ground.
Wind turbine capacity is directly related to wind speed and equipment size, particularly to the rotor/blade
diameter. The power generated by a turbine is proportional to the cube of the prevailing wind, that is, if
thc wind speed doubles, the available power will increasc by a factor of eight. Because of this
relationship, proper siting of turbines at locations with the highest possible average wind speeds is vital.
201 I Renewable Resources Assessment Revision 3 On-Shore Wind
turbine. Because this analysis assumes generic site locations, the turbine selection is not optimized for a
specific location or condition. Actual turbine sclcction requires further site-specific analysis.
Table 4-1: Summary of Wind Turbine Model lnformation
Yestas V136-3.6 GE3.&r37
Name Plate Capacity, MW 3.6 3.6
Rotor Diameter, meters 136 tst
Hub Height, meters
Using thc NREL wind resource maps, the mcan annual hub height wind speed at each potential project
location was estimated and then extrapolatcd for the appropriate hub height to determine a represental.ive
wind speed. Using a Raylcigh distribution and power curve for thc turbine technology described above, a
gross annual capacity factor (GCF) was subsequently estimatcd for each site for both turbine types.
Annual losses for a wind cncrgy facility were estimated at approxirnately I7 percent, which is a common
assumption for scrccning level estimates in the wind industry. This loss factor was applied to the gross
capacity factor estimates to dcrive a net annual capacity factor (NCF) for each potential site. Idcally, a
utility-scale generation project should have an NCF of30 pcrcent or better. The NCF cstimates for the
PacifiCorp service areas are shown in the Summary Tables and represent an avcrage of the two evaluated
technologies.
4.3 Wlnd Cost Estimate
The wind energy cost estimatc is shown in the Summary Tablcs. A typical cash flow for a wind project is
included in Appendix F. Cost estimates assume an EPC project plus typical Owncr's costs. Costs are
based on a 200 MW plant with 3.6 MW turbines (56 total turbines) and 80-mcter hub heights.
o Equipment and construction costs are broken down into subcategories per PacifiCorp's request.
These breakouts rcpresent the general scale ofa 200 MW wind project but are not intcnded to
indicate the expected scope for a specific site,
o The EPC scope includes a GSU transformer for interconnection at 230 kV.
o Land costs are excluded from the EPC and Owner's cost. For the 2018 Study, it is assumed that
land is leased, and those costs are incorporated hto the O&M estimate.
PacifiCorp 4-2 Burns & McDonnell
80 ll0
Cost eslimates also exclude escalation, interest during construction, financing fees, off-site
infrastructurc, and transmission.
4.4 Wind Energy O&M Estimates
O&M costs in the Summary Tables are derived from in-home information bascd on BMcD proiect
experience and vcndor information. Wind O&M costs arc modeled as fixed O&M, including all typical
operating cxpcnses including:
o Labor costs
. Turbinc O&M
. BOP O&M and other fixed costs (G&A, insurance, environmental costs, etc.)
. Property taxes
o Land lease payments
An allowance for capital replacement costs is not included within the annual O&M cstimate in the
Summary Tablc. A capital expenditures budget for a wind farm is generally a reserve that is funded over
the tifc of thc project that is dcdicatcd to major component failues. An adequate capital expenditurcs
budget is important for the long-term viability of the proiect, as major componcnt failures are expected to
occur, particularly as the facility ages.
Ifa capital rcplacement allowancc is dcsircd lor planning purposes, Table 4-2 shows indicative budgct
expectations as a percentagc of the total operating cost. As with operating expcnscs, howcvcr, these costs
can vary with the typc, size, or age of the facility, and prolcct-spccific considerations may justify
dcviations in thc budgeted amounts.
Table 4-2: Summary of lndicative Capital Expenditures Budget by Year
Operational Yean Capital Expenditurr Bueet
0-2 None (wananty)
3-5 3o/o 5o/o
6-10 5o/o - l0o/o
ll -20 t0% t5%
2t -30 ts%-20%
3l-40 20%-2s%
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On-Shore Wind
201 I Renewable Resources Assessment Revision 3 On-Shore Wind
4.5 Wind Energy Production Tax Credit
Tax credits such as the production tax credit (PTC) and investment tax credit (ITC) are not factorcd into
thc cost or O&M estimates in this Assessment, but an overview ofthe PTC is included below for
reference.
To incentivize wind energy devclopmcnt, thc PTC for wind was first included in the Energy Policy Act of
1992. [t began as a til5/MWh production credit and has sincc been adjusted for inflation, currently worth
approximately $24lMWh.
The PTC is awarded annually for the first l0 ycars ofa wind facility's operation. Unlike the ITC that rs
common in the solar industry, there is no upfiont incentivc to offset capital costs. Thc PTC valuc is
calculatcd by multiplying the $,MWh credit times the total energy sold during a given tax year. At thc cnd
ofthe tax year, thc total value ofthe PTC is applied to reduce or eliminate taxes that the owners would
normally owe. Ifthe PTC value is greatcr than thc annual tax bill, the excess credits can potentially go
unused unless the owner has a suitable tax equity partncr.
Since 1992, the changing PTC expiration/phascout schcdules have directly impacted market fluchrations,
driving wind industry expansions and contractions. Thc PTC is currently available for projects that bcgin
construction by the end of20l9, but with a phaseout schcdulc that began in 2017. Projccts that sta(cd
construction in 2015 and 2016 will receive the full value ofthe PTC, but those that start(ed) construction
in later ycars will rcceive reduced credits:
o 2017 80% ofthe fulI PTC valuc
o 20[8:60% ofthe fu PTC value
o 2019:40Y, of the full PTC value
o 2020: PTC Expires
To avoid receiving a reduction in the PTC, a "Safe Harbor" clause allowed for developers to avoid the
reduction through an upfront invcstment in wind turbines by the end of20l6. The Safe Harbor clause
allowed for wind proiects to be considered as having bcgun construction by the end of the year if a
minimum of 5olo of the project's total capital cost was incurred before January 1",2017.
Many wind farms werc planned for construction and operation when it was assumed they would receive
I00% ofthe PTC. However, with the reduction in ahc PTC, some ofthese projects are no longer
financially viable for developers to operate. This may result in rencgotiatcd or cancclcd PPAs, or transfcrs
to utilities for operation.
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2018 Renewable Resources Assessment Revision 3 On-Shore Wind
4.6 Wind Plus Storage
The wind plus storage options combine the wind technology discussed in section 4.0 with the lithium ion
batteries described in section 7.0. The battery storage sizc is sct at approximately 25olo of the total
nominal output ofthe base solar options, with options for two. four, and eight hours ofstorage duration.
The storage system is assumed to be electrically coupled to the wind system on the AC side, meaning the
storage system has its own inverter.
Capital costs are shown as add-on costs, brokcn out as projcct and owner's costs. These represent the
additional capital above thc wind base cost, intendcd to capturc modcst savings to account for shared
system costs such as transformer(s) and switchgear. ln addition, ovcrlapping owncr costs are eliminatcd
or reduced. Finally, a line for O&M add-on costs is also included which can be added to the base wind
O&M costs to determine overall facility O&M. As with the Li-lon battery options, the co-located storage
option assumes an operation profile ofonc cyclc pcr day, which is used for calculating the O&M costs.
PacifiCorp Burns & McDonnell4-5
5.0 PUMPED HYDRO ENERGY STORAGE
PHES provides the ability to optimize the system for satisfring monthly or even seasonal encrgy nccds
and PHES can provide spinning reserve capacity with its rapid ramp-up capability. Encrgy stored off-
peak and delivered on-peak can help reduce on-peak prices and is thercfore bcncficial to consumers.
PHES is well suited for markets whcrc thcrc is a high spread in day+ime and nighrtime energy costs,
such that water can be pumped at a low cost and used to generate energy when costs are considerably
higher.
PHES also has the ability to reduce cycling ofexisting generation plants. Additionally, PHES has a dircct
benefit to renewable resources as it is ablc to absorb excess energy that otherwise would need to be
cu(ailed due to transmission constraints. This could increase the percentagc olpower generated by clean
technologies and delivered during pcak hours.
5.2 PHES Cost Estimate
Thc PHES cost cstimatc was bascd on inlormation provided by developers with limited scope definition
We aligned the costs as closely as possible based on the information provided. The reason information
from developers was used versus using a generic site for PHES is due to thc significant importance of
geographical location for this type ofcncrgy storagc. Thc cost cstimatc is shown in the Summary Tables
PHES can see life cycle benefits as their high capital cost is offset by long lifespan ofassets.
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2018 Renewable Resources Assessment Revision 3 Pumped Hydro Energy Storage
5.1 GeneralDescription
Pumped-hydro Energy Storage (PHES) offers a way ofstoring offpeak gcncration that can be dispatched
during peak demand hours. This is accomplishcd using a rcvcrsable pump-turbine generator-motor where
water is pumped lrom a lower rescrvoir [o an uppcr rcscrvoir using surplus off-peak electrical power.
Encrgy is thcn rccapturcd by releasing the water back through the turbine to the lower resewoir during
pcak demand. To utilize PHES, locations need to be identified that have suitablc gcography near high-
voltage transmission lines.
6.1 GeneralDescription
Compressed air energy storage (CAES) oflcrs a way ofstoring offpeak gcncration that can be dispatched
during peak demand hours. CAES is a proven, ulility-scale energy storage technology that has been in
operation globally for over 30 years. To utilize CAES, the proicct nccds a suihble storage sitc, cither
above ground or bclow ground, and availability of tansmission and lucl source. CAES facilities use off-
peak electricity to power a compressor train that compresses air into an undergror.u:d reservoir at
approximately ll50 psig. Energy is then recapturcd by releasing the compresscd air, heating it (tWically)
with narural gas firing, and generating power as thc heated air travels through an cxpander.
This method ofoperation takes advantage of less cxpensive, off-peak power to charge the system to later
be uscd for generation during periods olhigher demand. CAES provides the ability to optimizc the
system for satisfying monthly, or cvcn scasonal, energy needs and CAES can provide spinning rcscrvc
capacity with its rapid ramp-up capability. Energy stored off-peak and dclivcred on-peak can help reduce
on-peak prices and is therefore beneficial to consumers. Additionally, CAES has a dircct benefit to
renewable resources as it is able to absorb excess energy that otherwise would need to bc curtailed due to
transmission constraints. This could incrcase the percentage ofpowcr gcnerated by clean technologics and
delivered during peak hours.
Therc have been two commercial CAES plants built and opcrated in the world. The first plant began
commercial operations in 1978 and was installed near Huntorf, Germany. This 290 MW facility included
major equipment by Brown, Boveri, and Company (BBC)- The second is locatcd ncar Mclntosh,
Alabama and is currently owned and operated by PowcrSouth (originally by Alabama Elcctric
Cooperativc). This I l0 MW facility began commercial operations in I99l and employs Dresser Rand
(DR) equipment. BMcD sewed as the Owncr's engineer for this pro.ject.
"Second generation" CAES designs have rcccntly been developed, but do not havc commercial operating
experiencc. Thc comprcssion-cxpansion portion ofthese designs is similar to "first generation" CAES
designs. The designs differ in that a simplc cyclc gas turbine plant operates in parallel to the compression-
expansion train and the exhaust is used in a recuperator instcad olutilizing a combustor to prchcat thc
stored air.
CAES is well suited for markets where thcre is a high spread in day-time and night-time energy costs,
such that air can be compressed at a low cost and uscd to generate energy when cosls are considerably
higho.
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2018 Renewable Resources Assessment Revision 3 Compressed Air Energy Storage
6.0 COMPRESSED AIR ENERGY STORAGE
20'18 Renewable Resources Assessment Revision 3 Compressed Air Energy Storage
6.2 CAES Cost Estimate
The CAES cost estimatc is shown in the Summary Tablcs. It was developed using gcncric Siemens
information that includes the power island, balancc olplant and reservoir. Cost cstimates assume an EPC
projcct plus typical Owner's costs.
6.3 CAES Emissions Control
A Selectivc Catalytic Reduction (SCR) systcm is utilized in the CAES dcsign along wrth demineralized
water injcction in the combustor to achicvc NOx emissions of2 parts pcr million, volumetric dry
(ppmvd). A carbon monoxidc (CO) catalyst is also used to control CO emissions to 2 ppmvd at the exit of
the stack,
The use olan SCR and a CO catalyst requires additional site infrastructure. An SCR systcm injecs
ammonia into the exhaust gas to absorb and react with thc cxhaust gas to strip out NOx- This requires
onsite ammonia storage and provisions for ammonia unloading and transfer.
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7.0 BATTERY STORAGE TECHNOLOGY
This Assessment includes shndalone battery options for both lithium ion (Li-Ion) and flow battery
tcchnologies. Li-lon options included I MW output with lS-minutc, 2-hour,4-hour, and 8-hour storage
capacities as well as a l5 MW option with 4-hours of storage. A I MW,6-hour flow cell battery option
was also included. Additionally, the solar and wind summary tables include optional costs for adding Li-
Ion battery capaciry of 25% ofthe nominal renewable output to the site with 2, 4, or 8-hours ofstorage.
7.1 GeneralDescription
Electrochemical energy storagc systcms utilize chemical rcactions within a battery cell to facilitate
electron flow, converting clcctrical energy to chemical energy when charging and generating an electric
current when dischargcd. Electrochemical technology is continually developing as one of the leading
cncrgy storage and load following technologies due to its modulanty, ease ofinstallation and opcration,
and relative design maturity. Dcvclopmcnt of electrochcmical batteries has shifted into three categories,
commonly termed "flow," "conventional," and "high temperature" battery designs. Each banery type has
unique features yielding specific advantages compared to one another.
7.1.1 Flow Batteries
Flow batteries utilizc an electrode cell stack with externally stored electrolyte material. Thc flow battery
is comprised ofpositive and ncgativc clectrode cell stacks scparated by a selectively permeable ion
exchange membrane, in which the charge-inducing chemical reaction occurs, and liquid electrolyte
storage tanks, which hold the stored energy until dischargc is rcquired. Various control and pumpcd
circulation systems completc thc IIow battery system in which the cells can be stacked in series to achieve
the desired voltage diffcrcnce.
The battery is charged as thc liquid electrolytes are pumped through the electrode ce[[ stacks, which serve
only as a catalyst and transport medium to the ion-inducing chemical reaction. The excess positivc ions at
the anode are allowed through tle ion-sclcctivc mcmbranc to mainlain electroneutrality at the cathode,
which experienccs a buildup ofnegative iors. The charged clcctrolyte solution is circulated back to
storage tanks until the process is allowcd to repeat in reversc for discharge as necessary.
ln addition to external elcctrolytc storage, flow batteries differ from traditional batteries in that energy
conversion occurs as a direct result of the reduction-oxidation reactions occuning in thc clcctrolytc
solution itsclf. The electrode is not a component ofthc clcctrochcmical fuel and does not participate in the
chemical reaction. Thereforc, thc electrodes are not subiect to the same deterioration that depletes
clcctrical performance oftraditional batteries, resulting in hrgh cycling life ofthc flow battcry. Flow
PacifiCorp 7-1 Burns & McDonnell
201 8 Renewable Resources Assessment Revision 3 Battery Storage Technology
2018 Renewable Resources Assessment Revision 3 Battery Storage Technology
batteries are also scalable such that energy storage capacity is determined by the size of the electrolyte
storage tanks, allowing the system to approach its theoretical energy density. Flow batteries are tlpically
less capital intensive than some conventional batteries but require additional installation and operation
costs associated with balance ofplant equipment.
7 ,1.2 Conventional Batteries
A conventional battrcry contains a cathodic and an anodic elcctrode and an clectrolyte sealed within a cell
container that can be connected in series to increase overall facility storage and output. During charging.
the electrollte is ionized such that when discharged, a reduction-oxidation reaction occurs, which forces
electrons to migrate from the anode to the cathode thereby generating electric current. Batteries are
designated by the electrochemicals utilizcd within thc cell; the most popular convcntional battcries are
lead acid and Li-lon typc battcrics.
Lead acid batteries are the most mature and commercially accessible battery technology, as their dcsign
has undergone considcrablc dcvclopmcnt sincc conccptualizcd in the latc 1800s. Thc Department of
Energy (DOE) estimates there is approximately ll0 MW oflead acid battery storage currently installed
worldwide. Although lead acid batteries require relatively low capital cost, this technology also has
inherently high maintcnance costs and handling issucs associated with toxicity, as well as low cnsrgy
density (yields higher land and civil work requirements). Lead acid batteries also have a relatively short
lifc cycle at 5 to l0 years, espccially whcn uscd in high cycling applications.
Li-lon batteries contain graphite and metal-oxide electrodes and lithium ions dissolved within an organic
electrolyte. The movement of lithium ions during cell charge and discharge generates current. Li-lon
technology has sccn a rcsurgcncc ofdevclopmcnt in recent years due to its high energy density, low self-
discharge, and cycling tolerance. Many Li-lon manufacturers currently offer l5-year warranties or
performance guarantees. Consequently, Li- Ion has gained traction in several markets including the utility
and automotive industrics.
LiJon battery priccs arc Lrcnding downward, and continucd dcvclopmcnt and invcstmcnt by
manufacturers are expected to further rcduce production costs. Whilc thcrc is still a widc range ofproject
cost expectations due to market uncertainty, Li-lon batteries are anticipated to expand their reach in the
utilily markct sector.
7.1.3 High Temperature Batteries
High tompcraturc batterics operate similarly to conventional batteries, but they utilize molten salt
electrodes and carry thc addcd advantagc that high temperatue operation can yield heat for other
PacifiCorp 7-2 Burns & i,4cDonnell
201 8 Renewable Resources Assessment Battery Storage Technology
applications simultaneously. The tcchnology is considered mature with ongoing commercial development
at the grid level. The most popular ard technically developed high temperature option is the Sodium
Sulfur (NaS) battery. Japan-based NGK Insulators, the largest NaS battery manufacturer, installed a 4
MW system in Presidio, Texas in 2010 following opcration of systcms totaling more than I60 MW since
the projcct's inception in thc 1980s.
The NaS battery is typically a hermetically sealed cell that consists ofa molten sulfur electrolyte at the
cathode and molten sodium electrolyte at the anode, separated by a Beta-alumina ceramic membranc and
enclosed in an aluminum casing. The membrane is selectively permeable only to positive sodium ions,
which are created from the oxidation ofsodium metal and pass through to combinc with sullur rcsulting
in thc formation ofsodium polysulfides. As powcr is supplicd to the battery in charging, the sodium ions
are dissociated from the polysulfides and forced back through the membrane to re-form elemental
sodium. The melting points of sodium and sulfur are approximately 98oC and t l3'C, rcspcctivcly. To
maintain the elcctrolytes in liquid form and for optimal performancc, thc NaS battery systems are
typically operated and storcd at around 300'C, which results in a higher self-discharge rate of l4 percent
to lll percent. For this reason, these systems are usually designed for use in high-cycling applications and
longer discharge durations.
NaS systems are expccted to have an operable life ofaround l5 years and are onc o[the most developed
chcmical cncrgy storage technologies. Howcvcr, unlikc othcr battcry types, costs ofNaS systems have
historically held, making othcr options more commercially viable at present.
7.2 Baftery Emissions Controls
No emission controls arc currently required for battery storage facilities. Howevcr, Li-Ion battcrics can
rclcasc largc amounts ofgas during a fire cvcnt. While not currcnlly an issue, there is potential for
increascd scrutiny as more battcry systcms are placed into service.
7.3 Battery Storage Performance
This assessment includcs pcrformance for multiple Li-lon options as well as onc flow battcry option. Li-
Ion systcms can rcspond in seconds and exhibit excellent ramp ratcs and round-trip cycle efficiencies.
Because the technology is rapidly advancing, there is uncertainty regarding estimates for cycle lifc, and
these estimates vary greatly depending on the application and dcpth ofdischargc. The systems in this
Assessment are assumed to pcrlorm onc full cycle per day, and capacity factors are based on the duration
of full discharge for 365 days. OEMs typically have battery products that are designcd to suit diffcrcnt
use-cascs such as high power or high energy applications. Thc powcr to cnergy ratio is commonly shown
PacifiCorp
Revision 3
Burns & McDonnell
Revision 3 Battery Storage Technology
as a C-ratio (for example, a IMW / 4 MWh system would use a 0.25C battery product). However, the 8-
hour battery option is bascd on a 0.25C systcm that is sized for twicc the powcr and discharged for eight
hours instead of four. While the technology continues to advance, commercially available, high energy
batteries for utility scale applications are generally 0.25C and above.
Flow batteries are a maturing technology that is well suited for longer discharge durations (>4 hours, for
example). Flow batteries can provide multiple use cases from the same system and they are not expected
to exhibit performance degradation Iike lithium ion technologies. However, they typically have lower
round trip efficicncy than Li-lon battcrics. Storagc durations arc currcntly limitcd to commercial offerings
fiom select vendors but are expected to broaden over thc ncxt scveral ycars. Performance gu&antees of
20 years are expected with successful commercialization, but there is not necessarily a technical reason
that original equipment manufacturer (OEM) and/or balance ofplant (BOP) designs could not
accommodate 30+ year life.
7.4 Regulatory Trends
Two (2) Federal Energy Regulatory Commission (FERC) Orders released in 20lll are expected to provide
clarity on the role ofstorage in wholesale markets, and potentially dnve continued growth. FERC Order
841 requires RTOs and ISOs to dcvclop clcar rules rcgulating thc participation ofcncrgy storagc systcms
in wholesale energy, capacity, and ancillary services markets. hior to the final release ofFERC 841, the
Catifornia Public Utilitics Commission introduccd I I rulcs to dctcrminc how multi-use storagc products
participate in Califomia Independent System Operator (CAISO). FERC Order 842 addresses
requircmcnts for some generating facilities to provide frequency response, including accommodations for
storage technologies. In addition, thc Intcmal Rcvcnuc Scrvicc (IRS) is considcnng ncw guidance for thc
ITC that will impact proiecs combining storage with renewables.
7.5 Baftery Storage Cost Estimate
Thc cstimatcd costs ofthe Li-lon and flow battery systems are included in the Sumrnary Tables, based on
BMcD experiencc and vcndor corrcspondcncc. Thc kcy cost clcmcnts ola Li-lon battcry systcm arc thc
inverter, the battery cells, the interconnection, and thc installation. Thc capital costs reflect recent trends
for ovcrbuild capacity to account for short term degradation. The battery enclosures include space lor
future augmentation, but thc costs associatcd with augmentation are covcrcd in thc O&M costs. It is
assumed that land is available at an existing PacifiCorp facility and is thcrclorc cxcludcd from thc cost
cstimatc. These options assume the battery interconnects at medium voltage.
PaciflCorp 7-4 Burns & lVcDonnell
201 8 Renewable Resources Assessment
201 8 Renewable Resources Assessment Revision 3 Battery Storage Technology
Flow battery estimatcs for the I MW option are based on zinc-brominc tcchnology with a 6-hour storage
duration. This is a modular design in which the OEM scopc includcs thc stack. clcctrolytc storagc, and
associated pumps and controls in a lactory asscmblcd packagc. Thc EPC scopc includcs the inverters,
switchgear, MV translormcr, and installation.
7.6 Battery Storage O&M Cost Estimate
O&M estimates for the Li-Ion and flow battcry systcms arc shown in thc Summary Tables, based on
BMcD experience and recent market trends. The battery sl.oragc system is assumcd to bc opcratcd
remolcly.
Overbuild and augmentation philosophics can vary bctwccn projccts. Bccausc battery costs are expected
to continue falling, many installers/integrators are aiming for lower initial overbuild percentagcs to reduce
initial capital coss, which mcans guarantccs and scrvicc contracts will rcquirc morc future augmentation
to maintain capacity. Because costs should be lower in the futurc, thc projcct cconomics may lavor this
approach. This asscssment assumes minimal overbuild beyond systcm cfficicncy losscs, and the O&M
estimates include allowanccs for augmcnlation.
Battery storage O&M costs arc modclcd to rcprcscnt the fxed and variable portions ofperformance
guarantees and augmcntation from recent BMcD projcct cxpcricncc. Thc fixcd O&M cost lor thc Li-lon
sysiems includc a nominal fixed cost to administer and maintain the O&M contract with an
OEN,I-lintegrator, plus an allowance lor calendar degradation fees. Calendar degradation represents
performance degradation and subsequent augmcntation cxpcctcd to occur rcgardlcss of thc systcm's
operation profile, even ifthe batteries sit unused. Because calendar degradation is not tied to system
operation or output, it is modeled as part of the fixed O&M.
Variablc O&M cstimates for Li-ion options account for cycling degradation lees. Cycling the batteries
increases performance degradation, so the performance guarantees provided by the OEM and/or
integrator are commonly modclcd to account lor augmcntation bascd on thc cxpcctcd opcrating prohlc.
The variable O&M cstimates in this assessment are based on an operation profile ofone charge/discharge
cycle per day and may not be valid for incrcascd cycling.
PacifiCorp Burns & McDonnell
The technical life ofa Li-lon battery project is expectcd to bc l5 ycars, but battcry perlormancc degrades
over timc, and this degradation is considered in the system design. Systems can be "overbuilt" by
including additional capacity in the initial installation, and they can also be designed for furure
augmentation. Augmentrtion mcans that dcsigns account for thc addition of future capacity to maintain
guaranteed performancc.
2018 Renewable Resources Assessment Revision 3 Battery Storage Technology
Flow battery O&M costs are modelcd around an alnual scrvicc contract from the OEM or a factory
trained third party. Costs are bascd on corrcspondcncc with manulacturers and are subject to change as
the technology achieves greater commercialization and utilization in thc utility scctor. Unlikc Li-lon
technologies, flow batteries generally do not exhibit calendar or cycle degradation, so thcrc is not a
variable O&M component per cycle. There is mechanical equipmcnt that rcquircs scrvicc based on an
OEM recommended schedule, which is modclcd as a lcvclizcd annual cost for thc life ofthe system.
PacifiCorp 7-6 Burns & l\.4cDonnell
Revision 3 Conclusions
8.0 CONCLUSIONS
This Renewable Encrgy Rcsource Technology Asscssmcnt provides information to support PacifiCorp's
power supply planning efforts. lnformation provided in this Asscssment is screening level in nature and is
intended to highlight indicative, differential costs associated with each technology. BMcD recommends
that PacifiCorp usc this inlormation to updatc production cost models for comparison of renewable
resourcc altemativcs and their applicability to futurc rcsource plans. PacifiCorp should pursue additional
engineering studies to define proiect scope, budget, and timclinc for tcchnologies of interest.
Rcncwable options include PV and wind systcms. PV is a proven technology for daytime peaking power
and a viable option to pursue renewable goals. PV capital costs have steadily declined for years, but
recent import tariffs on PV panels and foreign steel may impact market trcnds. Wind energy generation is
a proven technology and turbine costs dropped considerably over the past few years.
Utility-scale battcry storage systems are being installcd in varied applications from frequency response to
arbitrage, and recent cost reduction trends are expectcd to continue. Li-lon technology is achieving the
greatest markct pcnctration, aided in large part by its dominance in the automotive industry, but other
technologies like flow batteries should be monitored, as well.
PacifiCorp's region has scvcral gcological sites that can support large scale storage options including
PHES and CAES. This gives PacifiCorp flexibility in tcrms ofenergy storage. Smaller applications will
be much better suited for battery technologies, but if a larger need is idcntificd PHES or CAES could
provide excellent larger scale altematives. Both of these technologies benefit from economies ofscalc in
regard to their total kWh olstorage, allowing thcm to decrease the overall $/kWh project costs.
PaciflCorp 8-1 Burns & McDonnell
201 I Renewable Resources Assessment
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APPENDTX B - SOLAR PVSYST MODEL OUTPUT (sMW)
31t08t18 Page 1/5
Grid-Connected System: Simulation parameters
Project :
Geographical Site
Situation
Time dellned as
PCI 8-Grid-ldahoFallslD-SAT
ldaho Falls Fanning Field Country USA
43.5'N Longitude 112.1"W
Time zone UT-7 Altitude 1441 m
o.20
TMY - NREL: TMY3 hourly DB (1991-2005)Meteo data:
Latitude
Legal Time
Albedo
ldaho Falls Fanning Field
Simulation variant :PC18_ldahoFalls_Rev3
Simulation date 31/08/18 13h50
Simulataon parameters
Tracking plane, tilted Axis
Rotation Limitalions
Axis Tilt 0'
Minimum Phi -60"
Axis Azimuth 0'
Maximum Phi 60"
Backtracking strategy
lnactive band
Tracker Spacing
Left
5.50 m
0.20 m
Collector width
Right
1.98m
0.20 m
Models used
Horizon
Near Shadings
Diffuse lmported
PV Array Characteristics
PV module Si-poly l,iodel
Manufacturer
Orientation
ln series
Nb. modules
Nominal (STC)
u mpP
Module area
cs3u€40P 1500v
Canadian Solar lnc.#1 TiluAzimuth
26 modules ln parallel19188 Unit Nom. Power
6524 kwp At operating cond-
895 V I mpp
38069 m' Cell area
Number of PV modules
Total number of PV modules
Anay global power
Anay operating characteristics (50"C)
Total area
30Y0'
738 strings
340 Wp
s890 kwp (50'c)
6580 A
33931 m'
lnverter
Characteristics
lnverter pack
Model
lvlanufacturer
Operating Voltage
Nb. of inverters
SMA SC2500 EV Prelimt
SMA
850-1425 V Unit Nom. Power 2500 kWac
5000 kwac2 units Total Power
PV Array loss factors
Array Soiling Losses Feb Mar [.{ay June July Aug.sep Oct.Dec.
2.50k 2 51"2.5%2.OVo 2.50/o 2.50/o 2.50/o 2.50/o
Thermal Loss factor
Wiring Ohmic Loss
LID - Light lnduced Degradation
Module Quality Loss
Module Mismatch Losses
Uc (mnst)
Global array res.
Uv (wind)
Loss Fraction
Loss Fraction
Loss Fraction
Loss Fraction
'1.2 Wrn2K / m/s
1.5 % at STC
2.0 o/o
-o.4%
1.0 o/o at MPP
25.0 Wm'K
2.3 mOhm
Pvsy3r L@.sd ro aume A Mcoonei (USA)
PVSYST v6 3s I
Transposition Perez
Free Horizon
Linear shadings
Jan.Nov.
PVSYST V6.35 s1/08/18 Page 215
Grid-Connected System: Simulation parameters (continued)
lncidence effect, user defined profile 20 30'40 50.60 a0'90
100 100 100 099 0s9 097 092 076 000
System loss factors
Wiring Ohmic Loss Wires 0 m 3x0.0 mm' Loss Fraction 0.0 % at STC
User's needs :Unlimited load (grid)
F,vsFt Li6s6d to Sums e Mcoonnert (USA)
PVSYST V6.35 31108t18 Page 415
Grid-Connected System: Main results
Project :
Simulation variant :
PCI 8€rid-ldahoFallslD-SAT
PC18_ldahoFalls_Rev3
Main system perameters
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
Useds needs
Systemtype crid-Connected
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
0" Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Preliml Pnom2.0 Pnom total
340 Wp
6s24 kwp
2500 kW ac
5000 kW ac
Main simulation resulG
System Production Produced Energy
Performance Ratio PR
11763 Mwhryear Specific prod. 1803 kwh/kwp/year
83.4 Yo
Normalized producrlon3 lper install.d *Wp): Nomlnal power 6524 kwp Performance Ratio PR
f
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J, F.t h. AF M.y i, .t, Al, S.o Clc lbv O-Jn F.O rlts AF Ey r, J'r &c S? OC l{d O..
PC18_ldahoFall3_Rev3
Brlanc.s and maln r€sulla
GbbEN
L. : Cox..r,6 LB (Pv-my h.r.)
Lt : syc. L6 orfr. )
Yl : PN&..d urtur .B!r thrrh.
3.6
623
134.9
170.8
200I
219 3
241.0
203 6
149 5
948
59.9
3t7
-7.63
502
152
a.oT
12 2a
1642
m.60
l9ot
r3 70
66t
0.19
-2 59
789
1914
258 1
2AA 2
323 5
277 6
20/ 5
1*2
835
48.6
415
1a! 6
212 6
!74.8
263 3
1931
12T.A
276
1129
1252
1393
1521
1698
1505
1143
790
499
2ea
210
! ro9
1230
1360
!495
1609
't479
1123
7t5
4q)
242
16 00
16 02
,5 50
14 62
14.18
13 a6
13 7a
14.24
14.69
14 23
15 70
15 56
1564
'15.72
14.36
13.93
r3 02
13 55
1400
1443
14 96
1411
1521
1618 2 694 2160 3 2U2 0 11975 t1763
Hoi2ont l gtob.t d.d..ton
Global incid.nl in 6ll pl.n.
Etrectvo Glob.l, cor rn lAM.nd shadings
E-CrE
Ef.ctve energy at rne ou$ut ot th6 adey
En.Ey rq*ted nlo qnd
Eilc Eout amy / rough are.
E c Eoutsyslem / rough aea
Pvsyll L'cen..d lo Bum3 & Mcooinstt (USA)
31/08/18 Page 5/5
Project :
Simulation variant :
PC1 8-Grid-ldahoFallslD-SAT
PC18_ldahoFalls_Rev3
Main system parameters
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
User's needs
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
0' Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Prelim! Pnom2.0 Pnom total
0'
340 Wp
6524 kWp
2500 kW ac
5000 kW ac
Loss diagram over the whole year
1618 kwh/m':Horizont l global i,radiation
+33.5% Global incident in coll. planc
Near ShadingE: iradiance loss
IAM tactor on global
Soiling los6 factor
Effective irradiance on collectora
Aray nominal energy (at STC eftic.)
PV lo$ due to irradiancs level
PV loss due to temperature
Module quality los6
LID - Light induced degradation
Module array mismalch loss
Ohmic wirino lo3s
Arr.y virtual energy at lriPP
-1.2%
-2.4%
2042 kwh/m: ' 38069 m2 coll
efficiency at STC = 17.15olo
13331 MWh
-0.90/o
+0.4'k
-2.0v"
-1.O%
-1.11o
12276 MWh
-1.1Vo lnverter LosB du.ing operation (efficiency)
lnverter Losg over nominal inv. power
lnverter Loss due to power threshold
lnverter Lo6s over nominal inv. voltage
lnverter Loss due to voltage threshold
Night consumption
Available Energy al l.rverter Ouhul
-2.50/o
o.ook
0.0%
o.ov.
o.ook
0.00k AC ohmic loss
Energy iniected anto grid11763 MWh
PVsFt Lic.n3€d lo Eums & McDonnen (usa)
PVSYST V6.35
Grid-Connected System: Loss diagram
Systemtype Grid4onnected
11763 MWh
PVSYST V6,35 Page 1/5
Grid-Connected System: Simulation parameters
Project :
Geographical Sate
Situation
Time defined as
PC18-LakeviewoR
Lakeview Country United States
42.2'N Longitude '120.4'W
Time zone UT-8 Altitude 1441 m
0.20
TMY - NREL: TMY3 hourly DB (1991-2005)
Latitude
Legal Time
Albedo
kkeview
Simulation variant :PC18-LakeviewOR_Rev2
Simulation date 31/08/18 14h20
Simulation parameters
Tracking plane, tilted Axis
Rotation Limitations
Axis Tilt 0'
Minimum Phi -60'
Tracker Spacing
Left
5.50 m
0.20 m
Collector width
Right
1.98 m
0.20 m
Models used
Horizon
Near Shadings
Transposition
Average Height
Linear shadings
Perez
2.4"
Diffuse lmported
PV Array Characteristics
PV module Si-poly Model
Manufacturer
Orientation
ln series
Nb. modules
Nominal (STC)
U mpp
Module area
CS3U3'OP 1500V
Canadian Solar lnc.#1 TiluAzimuth
26 modules ln parallel'19188 Unit Nom. Power
6524 kwp At operating cond.
895 V I mpp
38059 m'z Cell area
Number of PV modules
Total number of PV modules
Anay global power
Anay operating characteristics (50'C)
Total area
30'/0'
738 strings
340 Wp
5890 kWp (50'c)
6580 A
33931 m'?
lnverter
Characteristics
lnverter pack
Model
Manufacturer
Operating Voltage
Nb. of inverters
SMA SC2500 EV Preliml
SMA
850-1425 V Unit Nom. Power 2500 kwac
5000 kWac2 units Total Power
PV Array loss factors
Array Soiling Losses Jan Feb I\y'a.May June July Aug sep.Oct.Nov Dec.
2.0"/o 2.Oo/d 2.O%2.00k 2.Oo/a 2 la/r 2 5v"2 50k 2.5./o 2.Oo/o 2.0./"
Thermal Loss factor
Wiring Ohmic Loss
LID - Light lnduced Degradation
Module Quality Loss
Module Mismatch Losses
Uc (const)
Global array res.
25.0 Wm'K
2.5 mOhm
Uv (wind)
Loss Fraclion
Loss Fraction
Loss Fraction
Loss Fraction
1.2 Wm'?K / m/s
1.6 o/o at STC
2.0 0k
-O.4 o/o
1 .0 % at N4PP
Pvsyel Llconsed lo Bums A Mcoonnell(USA)
31/08/18 |
Meteo data:
Axis Azimuth 0'
Maximum Phi 60'
Backtracking strategy
lnactive band
31/08/18 Page 215
Grid-Connected System: Simulation parameters (continued)
lncidence effect, user defined profile 10 20 30 50.60'7A-
100 100 r00 099 a93 092 076
System loss factors
Wiring Ohmic Loss
User's needs :Unlimited load (grid)
Pvsr:r Licn!.d lo Bun. & M.Onn.ll (r.rSA)
PVSYST v6.35 |
Wires 0 m 3x0.0 mm'? Loss Fraction 0.0 o/o at STC
I oo'
PVSYST V6,35 31/08/18 Page 3/5
Project:
Simulation variant :
PC'18-LakeviewOR
PC18-LakeviewOR Rev2
Main system parameters
Horizon
System type
Average Height
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
Grid4onnected
2.4"
Near Shadings
PV Field Onentation
PV modules
PV Anay
lnverter
lnverter pack
Useis needs
0'
340 Wp
6524 kWp
2500 kW ac
5000 kW ac
Horizon Average Height
Albedo Factor
2.4'
100 o/o
Heisht [']
Azimuth ["]
3.4
-90
3.4
40
1.4
40
Horizon
75
30
15
-120 -s0
3
4
G
1
2
3
4
5
6
713h
14h10h
16h
18h
th
8h
7h
6h
22lune
22 may - 23 iuly
20 apt - 23 aug
20 mat - 23 sep
21 feb - 23 oct
19 ian - 22 nov
22 december
-60 -30 0
A:imulh [[']l
30 60 90 120
PvsFl Licensed lo Bums & McC,,rnn6ll {USA)
Grid-Connected System: Horizon deflnition
0' Axis Azimuth
CS3U-340P'1500V Pnom19188 Pnom total
SMA SC2500 EV Prelim! Pnom2.0 Pnom total
1.4
90
Diffuse Factor 0.99
Albedo Fraction 0.96
1'th
12h
15h
17h
PVSYST V6.35 31/08/'18 Page 4/5
Grid-Connected System: Main results
Project:
Simulation variant :
PClS-LakeviewOR
PCl8-LakeviewOR_Rev2
Main system parameters
Horizon
System type
Average Height
Linear shadings
kacking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
Grid€onnecied
2.4"
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
Use/s needs
0" Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Prelim! Pnom2.O Pnom total
340 Wp
6524 kWp
2500 kW ac
5000 kW ac
Main simulation results
System Production Produced Energy
Performance Ratio PR
12468 Mwh/year Specific prod. 19'll kWh/kWp/year
83.1 %
Normalt..d productlon3 (per i.3talled kwpl: tlomlnal pow.r c524 kwp Perlormrnc€ Ralio PR
s
i!
!:.
t
.J- F.a r/E rp. ra., Jr, l, Alo s.? o.t N.! o..Ji F- lE rp. M., .t, Jd Ale SC
PC18-Lakevl.woR_R.v2
galanc.! .nd main r.3ult3
E_G,ld EfAnR
52.8
85.1
106.7
1631
209.3
2512
212.7
198.5
167.3
114.2
63.8
49.6
-0.'16
26
442
9.9,r
1612
20.83
't7.f3
691
1.73
{.87
674
119.4
135.6
2134
2716
3ao.r
323.3
271.7
2317
159.8
€9.5
703
62.3
112.0
121 a
202 5
241.2
325..
307.4
258.0
222 3
1506
83.,1
65.0
ao2
717
@2
1193
ra2
lfff
1687
1459
1297
92€
527
a18
15.68
15.f7
15.53
t4.66
14.18
13.72
r3.7r
ta.lt
t4.52
15.26
,5.,t5
15.63
l5 i7
1549
15 24
13 9:t
13 49
13.!8
13 86
112f
14 99
1516
15 33
2117 6 1U6A
GbbEN
IL. c"r*uL*,p'.q'*, oe'rwu*'d.,I r' se- !* ,r-tu ' , o o, r\,v!rw;d.yI vr p;**,;r.*ey r.6d,&cu,5x,wh wdd.,
Horlzonial llobNl iradiston
Glo6al mcid.nl m @ll Plan.
Et cro. Grob.r, @r ,a rAM .nd !h.dng.
E-Gid
PvsystLics3ed ro Bums a Mcoonn€n (usA)
394
7U
faf
1112
i,157
,059
r2134
1275
912
517
410
157 2300 2 126S0
E €cliv€ €.€r!y .t lh. output ol ltr6 anay
E.€ryy lnl€ct€d inlo s.ld
E nc. Eoul .my / @sgh al..
Efic. Eoul !y31.ft / rough at.€
PVSYST V6.35 31t08t18 Page 5/5
Grid-Connected System: Loss diagram
Project :
Simulation variant :
PClS-LakeviewoR
PC18-LakeviewOR-Rev2
Main system parameters
Horizon
System type
Average Height
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
Grid4onnected
Near Shadings
PV Field Orientation
PV modules
PV Array
lnverter
lnverler pack
Usefs needs
0" Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Prelim! Pnom2.0 Pnom total
0'
340 Wp
6524 kwp
2500 kW ac
5000 kW ac
Loss diagram ov€r the whole year
1704 kwhh,Ho.izontal global irradiation
+35.0% Glob.l incident in coll. plane
-o.40/o
-1.70/o
Far Shadings / Horizon
Near Shadings: iradiance lo$s
IAM faclor on global
Soiling loss factor
Eftective irradiance on collectorG
Pv conversion
Aray nominal energy (at STC effic,)
PV loss due to irradiance level
PV lo6s due to tempeEture
Module quality loss
LID - Light induced degradation
Module arlay mismatch los6
Ohmic wiring loss
A.ray virtual energy at ilPP
-2.2o/o
2178 kwh/m':'38069 m': coll
efliciency at STC = 17.15%
14216 t\4wh
-0.8%
-4 oa/a
+0A%
-2.Oo/o
-1.0v.
-1.3%
13019 t4wh
-1.7%
-2.60k
lnverter Loss during operation (effciency)
lnverler Loss over nominal inv. power
lnverler Loss due to power threshold
lnveder Loss over nominal inv. voltage
lnverter Loss due to voltage threshold
Night consumption
Available Energy at lnverter output
0.0%
0.00/"
0.00/o
0.0%
12468 t\,{Wh
AC ohmic loss
Energy injected into grid12468 MWh
o.00/o
PvsysI L'c63€d ro Buro & [e-mail] (I.JSA)
PVSYST V6.35 31/08/18 Page 1/5
Grid-Connected System: Simulation parameters
Project :
Geographical Site
Situation
Time defined as
PCI 8-Grid-MildfordUT-SAT
MilforduT 31 Country United States
38.4'N Longitude 113.0'W
Time zone UT-7 Altitude 1563 m
0.20
TMY - NREL: TMY3 houdy OB (1991-2005)Meteo data:
Latitude
Legal Time
Albedo
MilfordUT NSRDB
Simulation variant :PC18-MilfordUT_Rev0
Simulation date 31lOAl18 14h/.7
Simulation parameters
Tracking plane, tilted Axis
Rotation Limitations
Axis Tilt 0"
Minimum Phi -60"
Axis Azimuth 0"
Maximum Phi 60'
Backtracking strategy
lnactive band
Tracker Spacing
Left
5.50 m
0.20 m
Collector width
Risht
1.98m
0.20 m
Models used
Horizon
Near Shadings
Transposition
Average Height
Linear shadings
Perez
3.0'
Diffuse lmported
PV Array Characteristics
PV module CS3U3.OP 1500V
Canadian Solar lnc.#1 TiluAzimuth
26 modules ln parallel19188 Unit Nom. Power
6524 kWp At operating cond.
895 V I mpp
38069 m' Cell area
Number of PV modules
Total number of PV modules
Anay global power
Anay operating characteristics (50'C)
Total area
738 strings
340 Wp
s890 kwp (so'c)
6580 A
33931 m'?
lnverter
Characteristics
lnverter pack
Model
Manufacturer
Operating Voltage
Nb. of inverters
SMA SC2500 EV Preliml
SMA
850-1425 V Unit Nom. Power 2500 kwac
5000 kWac2 units Total Power
PV Array loss factors
Array Soiling Losses Jan Feb Mar Apr May June July Aug sep Oct Nov Oec.
2.svo 2.syh 2.Oo/o 2 5"/.2.5./o 2.50/o
Thermal Loss factor
Wiring Ohmic Loss
LID - Light lnduced Degradation
Module Quality Loss
Module Mismatch Losses
Uc (const)
Global array res.
25.0 Wm'K
2.3 mohm
Uv (wind)
Loss Fraction
Loss Fraction
Loss Fraction
Loss Fraction
1.2 Wrn':K / m/s
1.5 % at STC
2.0 v,
-0.4 Yo
1.0 o/o at IVIPP
PvsFr Lrc.osed to Bum! & M.Oonnerr(USA)
Si-poly Model
Ma n ufactu rer
Orientation
ln series
Nb. modules
Nominal (STC)
u mpP
Module area
2.5%
31/08/'t8 Page 215
Grid-Connected System: Simulation parameters (continued)
lncidence effect, user defined profile 10.20 30,50'60'8o'90,
100 100 100 099 099 097 092 076 000
System loss factors
Wiring Ohmic Loss Wires 0 m 3x5000.0 mm' Loss Fraction 0.0 % at STC
User's needs :Unlimited load (grid)
Pvlyll Lf,en*d to Bumsa McDdretl (USA)
PVSYST v6.35
|
31/08/18 Page 3i5
Project :
Simulation variant :
PCi 8-Grid-MildfordUT-SAT
PCl8-MilfordUT Rev0
System type
Average Heighl
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
Grid4onnecled
3.0'
0" Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Prelim! Pnom2.0 Pnom total
0'
340 Wp
6524 kWp
2500 kW ac
5000 kW ac
Horizon Average Height
Albedo Factor
3.0'
1OO o/o
Diffuse Factor
Albedo Fraction
0.98
0.94
Heisht [']
Azimuth ['l
3.4
40
1.8
90
75
60
45
30
15
0,120 -90
1
3
5
6
1t 22 june
2: 22 may - 23 jul
3: 20 apr - 23 au
4'. ?0 mat - 23
12h 5, 2'l feb - 23
6: '19 jan - 22 nov
7: 22 dec*mbet
11h 14h
10h
16hth
17hth
7h
6h 19h
-60 -30 0
Azimuth ll'll
90 120
Pvsyst Lr@..d io Bums & r,i.Oo..elt (USA)
PVSYST V6.35
Grid-Connected System. Horizon defi nition
Main system parameters
Horizon
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
Usefs needs
3.4
-90
2.9
40
90
13h
15h
18h
30 60
PVSYST V6.35 31/08/18 Page 4/5
Project :
Simulation variant :
PGI 8-Grid-MildfordUT€AT
PC18-MilfordUT_Rev0
Main system parameters
Horizon
System type
Average Height
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
Grid4onnected
3.0"
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
Use/s needs
0' Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Prelim! Pnom?.O Pnom total
U
340 Wp
6524 kwp
2500 kW ac
5000 kW ac
Main simulation results
System Production Produced Energy
Performance Ratio PR
13645 Mwhlyear Specific prod. 2092 kwh/kwp/year
81.8 o/o
Normrlized productlon. (p.r lnstalled k$rp): tlominal poyr€r 6524 kwp Pedormance Ratio PR
5
I
3
I
t t 6 r- Ar. il.y J6 fi r! s.9 od l{@ o..h Fe Mr ^F Mr L xrr tuc s., G iror o..
PC18-MiltordUT_R€v0
Eal.ncos and main results
GlobE t
Ib cokMLos,P,{@ --,I rs s@h re ,.*tu, , o r r./vltxwnuyI r p*ra *u .* r;tr d,b,n, 5 n rwn vidd.,
'c
E-Grld E(ArR
JUIY
-r 63
096
2.97
156'
1911
2X97
2316
1535
1i.70
,.58
-r.75
115.6
r32 0
2r5 8
246 3
306 7
322 o
301.0
276.7
210 A
r62.9
1219
949
r07.5
124.7
20,r 6
23,10
290 9
306 2
285.9
262.4
22A6
'tf2.2
113 a
476
643
tf2
1206
1315
1563
1607
1493
1423
1237
1020
709
555
15 aO
r563
1128
13.63
13 34
14 26
13 75
15.56
15.66
ta 52
t536
t4 68
ta 03
13.39
13.11
t30a
t3 5i
1a 1t
1a.6!
15.28
15.37
1903.1 2556 6 2117I t38a7 13645 14 02
E Gnd
Ef,SysR
E 6ctiv€ 6n6rgy at lhe out ul oilietnay
En6rgy int6ct6d into grid
Elrc Eout.ray / EUgh.rE
Efic Eoul sysiem / bugh ac.
Pvsyst lrc..r.d b Bums a Mcoon€ll (usA)
Grid-Connected System: Main results
830
972
158.'
184.5
2331
2{3 9
230 2
207 6
175.2
132.0
064
67.4
695
78
1339
1591
1045
1519
1448
1320
1038
722
566
Hniznt l 9loo.l iFad.lio
Glob.l add.nt h coll dan6
Ensclr€ Grobar, ry. lor laM End shdi.gs
PVSYST V6.35 Page 5/5
Grid-Connected System. Loss diagram
Project :
Simulation variant :
PC18-Grid-MildfordUT-SAT
PC18-MilfordUT_Rev0
Main system parameters
Horizon
System type
Average Height
Linear shadings
tracking, tilted axis, Axis Tilt
lvlodel
Nb. of modules
Ivlodel
Nb. of units
Unlimited load (grid)
Grid-Connected
Near Shadings
PV Field Orientation
PV modules
PV Array
lnverter
I nverter pack
Use/s needs
0' Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SIVIA SC2500 EV Prelim! Pnom2.0 Pnom total
0'
340 Wp
6524 kWp
2500 kW ac
5000 kW ac
Loss diagram over the whole year
1903 kwh/m'Horizontal global irradiation
+34.3% Global incid€nt in coll. plane
*[', r*
\-1.6%l\.,,,.
N-r.oru
Far Shadings / Horizon
Near Shadrngs: inadiance loss
IAM factor on global
Soiling loss factor
Eflective irradiance on collectors
Ar.ay nominal energy (at STC etfic.)
PV loss due to irradiance level
PV loss due to temperature
Module quality loss
LID - Light induced degradation
Module aray mismalch loss
Ohmic wiring loss
Array virlual energy at MPP
efficiency at STC = '17.15%
15784 MWh
4.6Yo
-5.2.h
+0.4'/"
-2.Oo/o
-1.ovo
-1.2v"
14307 t\,4wh
-1.70k
-3.07.
lnverter Loss during operation (efltciency)
lnverter Loss over nominal inv. powet
lnverter Loss due to power threshold
lnverter Loss over nominal inv. voltage
lnverter Loss due to vollage threshold
Night consumption
Available Energy at lnverte. Output
o.ook
0.0%
0.0%
o.oo/o
13645 tv{Wh
13645 tVWh
0.0%AC ohmic loss
Energy in ected into grid
Pvsr3r Lr@ned ro Eums& Mcoonen (UsA)
31/08/18
|
2418 kwh/m' ' 38069 m'coll.
PVSYST V6-35 Page 1/5
Grid-Connected System: Simulation parameters
Project:
Geographical Site
Situation
Time delined as
PCI 8-Grid-RockSpri ngsWY-SAT
Rock Springs Arpt Country United Slates
Latatude 41.5"N Longitude 109.4'W
Legal Time Time zone UT-7 Altitude 1000 m
Albedo 0.20
Rock Springs Arpt TMY-NREL: TMY3 hourly DB (1991-2005)Meteo data:
Simulation variant :PCI 8-RockSpringsWY_Rev2
Simulation date 31/08/18 15h16
Simulation parameters
Tracking plane, tilted Axis
Rotation Limitations
Axis Tilt 0"
Minimum Phi -60"
Axis Azimuth 0'
Maximum Phi 60'
Backtracking strategy
lnactive band
Tracker Spacing
Left
5.50 m
0.20 m
Collector width
Right
1.98 m
0.20 m
Models used
Horizon
Near Shadings
Transposition
Average Height
Linear shadings
Perez
4.2"
Diffuse lmpo(ed
PV Array Characteristics
PV module Si-poly l/odel
Manufacturer
Orientation
ln series
Nb. modules
Nominal (STC)
U mpp
Module area
cs3u340P 1500v
Canadian Solar lnc.#1 TiluAzimuth
26 modules ln parallel19188 Unit Nom. Power
6524 kwp At operating cond.
895 V I mpp
38069 m' Cell area
Number of PV modules
Total number of PV modules
Anay global power
Array operating characteristics (50"C)
Total area
30"/0'
738 strings
340 Wp
s890 kwp (50'c)
6580 A
33931 m'
lnverter
Characteristics
lnverter pack
Model
Manufacturer
Operating Voltage
Nb. of inverters
SMA SC25O0 EV Preliml
SIVIA
850-1425 V Unit Nom. Power 2500 kwac
5000 kWac2 units Total Power
PV Array loss factors
Array Soiling Losses Jan Feb [rar Apr May June July Aug sep.Oct.Nov
2.5v"2 50/o 2.Ovo 2.5v.2 5./"2.5%2.5%
Thermal Loss factor
Wiring Ohmic Loss
LID - Light lnduced Degradation
Module Quality Loss
Module Mismatch Losses
Uc (const)
Global array res.
Uv (wind)
Loss Fraction
Loss Fraction
Loss Fraction
Loss Fraction
1.2 Wm'K / m/s
1.5%atSTC
2.0 0k
-0.4 0/o
1.0 7o at MPP
25.0 Wm'?K
2.3 mOhm
PvsFl Llcons€d to BoD! & Mctlonn n (UsA)
31/08/18
J
Oec
2.50/o 2.Oo/o
31/08/'18 Page 215
Grid-Connected System: Simulation parameters (continued)
lncidence effect, user deflned profile 10"20 30"50'60 t0'30
100 100 100 099 099 0s2 075
System loss factors
Wiring Ohmic Loss Wires 0 m 3x5000.0 mm' Loss Fraction 0.0 % at STC
User's needs :Unlimited load (grid)
Pvsysr Li@nsdro Euos & McDonnen {USA)
nvsvsr vo.ss I
90"
31/08/18 Page 3/5
Grid-Connected System: Horizon defi nition
PCI 8-Grid-RockspringsWY€AT
PCI 8-RockspringsWY_Rev2
Main system parameters
Horizon
System type
Average Height
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
l\tlodel
Nb. of units
Unlimited load (grid)
Grid4onnected
4.2"
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
Usefs needs
0'
340 Wp
6524 kwp
2500 kW ac
5000 kW ac
Horizon Diffuse Factor
Albedo Fraction
0.96
0.83
Heisht [']
Azimuth ['l -90
1.5
-40
7.0
40
7,0
90
75
60
30
-120
I
2
3
4
6
1
2
3
4
22 jone
22 may - 23 jul
20 ap. - 23
20 mar - 23 se
5: 2l feb - 23 oct
12h 13h 6: 19 jan - 22 nov
7 : 22 decefibet
14h
15h
th
16h
8h
17h
7h
6h
18h
-60 -30 0
Azimuth ll"ll
30 60 90 120
PVsFr L6en$d to Bums a McDonnen (USAI
PVSYST V6.35
Project :
Simulation variant :
0" Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Prelim! Pnom2.0 Pnom total
Average Height 4.2'
Albedo Factor 100 o/o
11h
10h
15
-90
PVSYST V6.35 31/08/18
Project :
Simulation variant :
Main system parameters
Horizon
System type
Average Height
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
lvlodel
Nb. of units
Unlimited load (grid)
GridConnected
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
Use/s needs
0' Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Preliml Pnom2.O Pnom total
0"
340 Wp
6524 kwp
2500 kW ac
5000 kW ac
Main simulation results
System Production Produced Energy
Performance Ratio PR
12510 MWh/year Specific prod. 1918 kWh/kWp/year
84.5 o/o
No.maliz.d productlons (per installed kwp)r Nominal power 0524 kwp Perlormance Ratio PR
;
,
!
l
E
.n.r F.a Mr Ar. M.r Jr, 'ro S.r ()c irrv O-J- F.! [l, ,!,. Mly .tj Ju A,re S+ Oc N.v O..
PCi 8-RocISp.ing!wY_Rev2
Balances and main resutts
'c
GlobElr E-Gdd
683
{!t I
127.1
156.6
200.6
224.4
2021
1580
1160
72.1
60.8
.410
,3 58
022
'19€10.16
17.24
19 89
r8 73
12 A4
161
-0.85
-5.3S
93.6
112.0
164 6
206 T
261.6
297 0
296.9
2TO.2
2181
160 1
975
a6a
856
103 5
157 3
1941
244 2
28? I
2414
255 6
20,19
119 2
497
565
681
1001
1198
1416
15€2
1564
1?20
921
540
523
15.86
15.96
15 59
1523
14 21
1387
14 29
'11T9
15 t1
15 63
15 84
1557
1567
t5.32
14.96
13.96
13 76
13 63
1405
14.5r
14.8r1
1531l
15 ari
1693 5 649 2269 3 1273a 12514 1a 48
GbbET
I L. 6r*mLog,ov.&r,.'g' os7\wmwodnI * ir*Eili:ffi ,1"-,***,1$s*t*il
Hdi26ial gbb.l lradr.ion
Globalrrctdtn @ll ple.
Etective Glob.l, cdr.lor IAM and shadlnga
E-GNd
EngysR
PvsFt Lts.ld lo Bom3 A !bD6n6ll (USA)
Page 4/5
Grid-Connected System: Main results
PC1 8-Grid-RockSpringsWY€AT
PCI 8-RockSpri n gsWY_Rev2
I
_t
664
943
1177
1555
1541
1445
120f
905
570
514
E bdjre asoy .l th. or]tFd ol me -ryEn loy hie.tod hlo,nd
Eitc Eqn .my / rDuon .r.6
Eftc. Eour !y!,Lm / rougn €rsa
PVSYST V6.35 31/08/18 Page 5/5
Grid-Connected System: Loss diagram
Project :
Simulation variant :
PC I 8-Grid-RockSpri ngsVVY-SAT
PCI 8-RockSpringsWY_Rev2
Main system parameters
Horizon
System type
Average Height
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
Grid-Connected
4.2'
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
Use/s needs
0" Axis Azimuth
CS3U-340P 1500V Pnom'19188 Pnom total
SMA SC2500 EV Prelim! Pnom2.0 Pnom total
0"
340 Wp
6524 kwp
2500 kW ac
5000 kW ac
Loss diagram over the whole year
1693 kwhhz Horizontal global inadiation
+34.0olo Global incidenl in coll. planc
4.91o
-1.7!o
Far Shading6 / Horizon
Near Shadings: iradiance loss
IAM factor on global
Soiling lo$ lactor
Eft€ctive iaradiancc on collectors
PV convercion
Anay nominal eneroy (at STC efiic.)
PV loss due to inadiance level
PV lo6s due to temperature
Module quality loss
LID - Light induced degradation
Module array mismalch loss
Ohmic wiring lo35
Anay virtual energy at l'rPP
-1.3%
-2.4vo
2132 kwh/m'. ' 38069 m'coll
efficiency al STC = 17.15olo
13916 MWh
-0.gvo
-2.10/o
-2.Oo/o
-1.0v.
-1.Ovo
13005 MWh
-1.70k
-2.11o
lnverter LoEs durino operaton (efficiency)
lnverter Losg over nominal inv- power
lnverter Lo6s due to power lhreshold
lnverter LoEs over nominal inv. voltage
lnverter LoBs due to voltage thre8hold
Night congumption
Available Ene,gy at lnve,ler Outsut
0.0Y0
0.0?o
0.00/o
0.0%
12510 MWh
12510 t\,,rwh
o.00/o AC ohmic loss
Energy injected into grid
PV9WI Licensed io Bums I Mcoonnen {UsA)
r4.1%
31/08/18 Page 114
Grid-Connected System: Simulation parameters
Project :
Geographical Site
Situation
Time defined as
PC'l 8-Grid-YakimaWA-SAT
Yakima Country United States
46.6"N Longitude 120.5"W
Time zone UT-8 Altitude 320 m
0.20
TIVY - NREL: TMY3 hourly DB (1991-2005)Meteo data:
Latitude
Legal Time
Albedo
Yakima Air Terminal
Simulation variant :Yaki maWA_SMW-SAT_Report
Simulation date 3'l/08/18 15h29
Simulation parameters
Tracking plane, tilted Axis
Rotataon Limitations
Axis Tilt 0"
lvlinimum Phi -60"
Axis Azimuth 0"
Ivlaximum Phi 60'
Backtracking strategy
lnactive band
Collector width
Right
1.98m
0.20 m
Models used
Horizon
Near Shadings
Transposition Perez
Free Horizon
Linear shadings
Diffuse lmported
PV Array Characteristics
PV module Si-poly Model
Manufacturer
Orientation
ln series
Nb. modules
Nominal (STC)
u mpp
Module area
CS3U-3/t0P 1500V
Canadian Solar lnc.#1 TiluAzimuth
26 modules ln parallel19188 Unit Nom. Power
6524 kwp At operating cond.
E95 V I mpp
38069 m' Cell area
Number of PV modules
Total number of PV modules
Array global power
Array operating characteristics (50'C)
Total area
30'/0'
738 strings
340 Wp
s890 kwp (so"c)
6s80 A
33931 m?
lnverter
Characteristics
lnverter pack
Model
Manufacturer
Operating Voltage
Nb. of inverters
SMA SC2500 EV Preliml
SMA
850-'1425 V Unit Nom. Power 2500 kWac
5000 kwac2 units Total Power
PV Array loss factors
Array Soiling Losses Jan Feb Mar lray June July Aug sep.Oct.Nov Dec
2.5%2.svo 2.50/o 2.1Vr 2.50k
Thermal Loss factor
Wiring Ohmic Loss
LID - Light lnduced Degradation
Module Quality Loss
Module Mismatch Losses
Uc (const)
Global array res.
Uv (wind)
Loss Fraction
Loss Fraction
Loss Fraction
Loss Fraction
1.2 W/m'K / m/s
1.6 % at STC
2.0 Yo
-0.4 o/o
1.0 % at MPP
25.0 W/m'K
2.5 mohm
PVsFt Li63.d io Bu6s & Mcoorelt{USA)
PVSYST V6,35
I
Tracker Spacing 5.50 m
Left 0.20 m
2.50k
PVSYST V6,35 31/08/1 8 Page 214
Grid-Connected System: Simulation parameters (continued)
lncidence effect, user defined profile l0'2A 80 90'
100 100 099 099 097 092 076 000
Wires 0 m 3x0.0 mm2 Loss Fraction 0.0 % at STC
User's needs :Unlimited load (grid)
Pvsylr L[6ne.d to Bumra Mcodml (uSA)
System loss factors
Wiring Ohmic Loss
PVSYST V6.35 31/08/18 Page 3/4
Grid-Connected System: Main results
Project:
Simulation variant :
PCl 8-Grad-Yaki maWA-SAT
Yak imaWA_5MW-SAT_Report
Main system parameters
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
User's needs
Linear shadings
tracking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
0" Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Prelim! Pnom2.0 Pnom total
340 Wp
6524 kwp
2500 kW ac
5000 kW ac
Main simulation results
System Production Produced Energy
Performance Ratio PR
10749 MWh/year Specific prod. 1&8 kwh/kwp/year
83.9 %
Normalized productions (per instell.d kwp): Nomln.l power 852t twp P€rlormance Ratlo PR
t
ai
n
I
e
J.,l F.o M- rI. Mly Ju .lJl tut S.p Oa r{d D-J- F6 M. ry .y .l Ji, Alll S.o Oc tbv O..
YakimaWA_sMW-SAl-R.port
Balances and main results
E_Grld
62.4
r0€9
r45 2
l8a.l
20E.6
2250
t90.6
140.7
91.2
qf.a
593
tr 57
14.14
19 2a
i968
15.67
906
219
-2.00
2U
478
u2
1076
1364
1458
1623
1122
1064
711
354
26f
274
469
1056
1L2
1397
1045
69€
36
261
15.45
15 5{'
r5.29
la g6
ta 6€
11.12
ia.37
11.47
15.03
15.35
t543
1510
r5n)
t50t
t4.60
It40
13 t7
13.04
11.12
14.32
15.02
15,09
1446 3 997 14.63
lu;m::;xr',**' B;:rffiwr::rIy, p;n c.d u*tu .E gy tMc dod,. 5 ! r,^r"rw;d.,
Hodzmlsl glot l lradlsoo.r
Gbbel lEirdt in @rl. d*
Elbcrivc Glo6.r, tr. lbr lAlI.rn lhadlDg.
Ei.clive .nergy al lh€ @rput ol th6 8r.y
Eturgy ,ijeted hto f.id
Efic Eout.ray / roogh a.oa
Efic Eout syslem / rdgh .Ga
F,v3y3r Lr@N6d ro Eums & Mcoonnen {USA)
Systemtype Grid4onnected
'c
483
8r1
1SO 1
245.1
2111
302 6
259.9
191.7
124 3
606
43t
r358
r78I
231.0
256 3
287 1
216.3
180.6
1r6.2
55.6
41.2
GlobE
E-GT'd
Ellsyla
PVSYST V6.35 31t08t18 Page 414
Project :
Simulation variant :
PCI 8-Grid-Yaki maWA-SAT
YakimawA_sMW€AT_Report
Main system parameters
Near Shadings
PV Field Orientation
PV modules
PV Anay
lnverter
lnverter pack
Use/s needs
Systemtype Grid{onnected
Linear shadings
lracking, tilted axis, Axis Tilt
Model
Nb. of modules
Model
Nb. of units
Unlimited load (grid)
0' Axis Azimuth
CS3U-340P 1500V Pnom19188 Pnom total
SMA SC2500 EV Prelim! Pnom2.0 Pnom total
0'
340 Wp
6524 kwp
2500 kW ac
5000 kW ac
Loss diagram over th€ whole year
1487 kWh/m'Horizonlal global ir,adiation
+32.2% Global incident in coll. pl.ne
Near Shadings: irradianc€ lo6s
IAM factor on global
Soiling loss factor
Eftective irradiance on colleclors
Array nominal energy (at STc effic.)
PV loss due to iradiance level
PV loss due to temperature
Module quality loss
LID - Light induced degradation
Module array mismatch loss
Ohmic whing loss
Aray virtual energy at MPP
-1.4v.
-2.50/.
etficiency at STC = 17.15%
12063 t\4wh
-12%
4.30k
,(+o4vo\ -z.ov"
[\.,.0.ot\.,,*
10987 t\!Wh
0.070
0.07.
0.07.
0.lqo
lnverter Loss during operation (efficiency)
lnverter Loss over nominal inv. power
lnverter Losg due to power threshold
lnverter Loss over nominal inv. vollage
lnverter Loss due to voltage threshold
Night consumption
Available Energy at lnve er output10749 t\4wh
0.0%AC ohmic loss
Energy injected inlo grid10749 MWh
Pv3y3i L@nl6d to Bums& McDnnerl(USA)
Grid-Connected System: Loss diagram
1848 kwhh'z ' 38069 m: coll
l\. ro.
\, -o.o*
APPENDIX C - SOLAR OUTPUT SUMMARY
BURNsS{sDoNNELL
Burns & McDonnell, Energy Division
Project Name:Pacificorp 2018 Renewables Technology Assessment
VC3 Oate: 31-Aug-18
Energy Production Summary
ldaho Fallr ldahoCity/State:
Latitude {N):
-112'LonSitude (W)
1441 m
ASHRAE CoolinE DB Iemp
-25 'CASHRAE Extreme Mean Min. Temp.
Site lnformation
PSo net production lyr-11 11597.3 MWh
AC caparity factor lnv Rating 26_44%
AC capaciw factor - POI Ratina 26.44%
DC caparity factor 20-oo%
Specific Production
Performan.e Ratio PR 81.08%
Nighttime logs€s
Plant Output Limitations 0.00%
tstlmated Annual Energy Production
system DC VoltaSe 1500 vDc
GCR 36%
5.5 m
MountinS
Tilt an8le or rotation limits 60"
0
Tracking strateEy TRUE
100.0 %
Degradation
Oesign Parameters
Nameplate Capacity 6.62 MWDC
Number of modules 19188
Nameplate Capacity 5-OO MWAC
1
lnter.onnection Limit 5-00 MwAc
lnteconnectioo Voltate 34.S kV
DC/AC ratio - POI R.tin8 1.324
F..illty l€vel lhf o.matlon
Module rating
26{ Modules p€r string
Strinss in parallel 738
Total number of modules 1918a
m capacity 5620 kW
5000 kw
1.324OqAC ratio - lnv Rating
Array Levelhlormation
TMYS
GHI 1618.2 kWh/m2
DHI
GlobalPOA 2160.8 kwh/m2
6.94 'C
AveraSeTemp. (6eneration)11.48'C
3.84 m/s
Av€.ase wind lGeneration)4.53 m/s
T.ansposition model
25.0 Wm2 XConrtant th€rmal loss factor lUc)
Wind loss factor (Uv)
2.4 %Soiling losses
LiBht induced d€pradation 2_0 %
DC wkinS loss
-0_4 %
Module mismatch loss 1.0 %
DC health loss r.0 %
Pvsyst Input Par.meters
MV transformer no-load losses o.o7%
MV transformer fullload losses 0 85%
Mv collection system o 70%
HVtrandormer no load losses 0.00%
HV tra nsformer fu ll load losses
0.00%
o.o1%
AC System loss€t
| 43.s .
345 W
I o.oo%
BURNSN{sDoNNELL
Bums & McDonnell, Energy Division
Project Name:Pacifi corp 2018 Renewables Technology Assessment
vc3 Datei 28'Au8-18
Energy Production Summary
City/state ldaho Falls.ldaho
Latitude (N):43.5'
Lonsitude (w)112'
1441 m
ASHRAE CoolinA Og Temp.32'C
ASHRAE Ertreme Mean Min. Temp.
Site lnformation
PS0 net production (yr-1)122928.5 MWh
AC capacity factor lnv Rating 25.57%
AC capacitv fuctor'POl Ratinr
DC capacityfactor
Specific Production
Perfo.mance Ratio PR 78-t3%
Nighttime losses .408.8 MWh
Plant Output l-imitations 2_61%
Ertimated Annual Ener8y P.oduction
System DC Voltage 15m VDC
GCB 36%
5.5 m
Tllt ansle or rotation limits 60
0
lracking strate8y TRUE
Availability 100.0 %
Degradation
Design PBrameters
Nameplate Capacity 72.82 MWDC
211068
Namepl.te Capacity 55.00 MWAC
11
lnterconnection timit 50.00 Mwac
lnteconnection Voltate 115 kV
DC/AC ratio - POI Ratina 1.456
Facility Level lnlormation
Module ratinB 345 W
t Modul€s per strinS 26
StrinSs in parallel 138
Totalnumberof module<19188
DC capacaty 6620 kW
s000 kw
DqAC ratio - lnv Ratin8 7-324
Array tevel lntormation
Source TMY3
GHI 16U.2 kwh/m2
oHt
GlobalPOA 2160.8 kwh/m2
6-94 'C
Averag€ Temp. (Generation)11.48'C
3.84 m/s
Av€rage Wind (Generation)4.53 m/s
Transposition model
Constant thermsl loss factor (Uc)29.0 Wm2-(
Wind loss factor(Uvl
Soiling los5es
LiSht induced deSradation 2.O %
DC warang loss t_s %
-o.4 %
Module mismatch lost 1_O %
OC health loss
Pvsyst lnput Parametert
MV tran5former no-load losses o.o7%
Mv transformer full load losses 0.85%
MV collection system 1.30%
HV transforrner no load losses o.07%
HV transformer fullload losses o.4a%
0.05%
0.01%
AC Syslem Losres
L.O %
24.O7%-------G;tr-
BURNS\lsDoNNELL
Pacifi corp 2018 Renewables Technology Assessment
VC3 Oate: 31-Aug-18
Energy Production Summary
ldaho talls,ldahoCity / State;
43-5'Latitud€ (N):
t12 'LonBitLrde (Wl:
1441 mAltitude
ASHRAE Cooling DB Temp.
ASHRAE Ertreme Mean Min. T€mp.
Site lnformetion
PSo net production (yr-l)491714.0 MWh
AC capacity factor - lnv Ratint 25.57%
AC capacity factor - POlRatins 28-07%
OC capacity factor 79_27%
Specific Production
Performan.e Ratio PR 78-11%
Night time loss€s -1635.2 MWh
Plant Output Limitat on9 2.63%
Ertlmated Annual Energy Produ.tion
System OC Volta8e 15m VOC
36%GCR
5.5 m
Tracker
Tilt anale or rotation limits 60
0
TRUE
100.0 %
Degradation
DerlSn Palameler9
Nameplate CaOacity 291..27 MWDt
844212
Nameplate Capacitv 220.00 Mwac
44
lnterconnection Limit 2m.00 Mwac
lnteconnection Voltace 230 kv
DC/AC ratio'POlRating 1.455
taclllty l€Yel lnformaion
Module ratina 345 W
26fl Modules per strlng
118Strin8s in parall€l
Totalnumber of modules 19188
6620 kWDC capa.ity
5000 kw
1 324DC/AC ratio- lnv R.tins
Aaray level lnf ormatlon
Source TMY3
GH 1618.2 kwh/m2
oHt
GlobalPOA 2160.8 kwh/m2
5.94 'C
Average Temp. (ceneration)11.48'C
3.8a m/s
Averate Wind (Generetion)4.s3 m/s
Iransposition model
2s.0 Wm2'(Constant th€rmal loss factor (Uc)
Wind loss fector (Uv)
2.4 %SoilinS losses
Lisht induced deEradation 2.O %
DC wirin8loss 15%
'0.4 %
1.0 %Module mi!match loss
DC h€alth loss 1.O %
Pvsyst lnputParem€ter5
MV transformer no-load losses o.o7%
MV tr.nsformer full load losses 0.85%
Mv collection system 1.30%
HV t.ansformer no-load losses o.o7%
HV kansformer full load losset 0.48%
HV line 0.05%
0.0I%
AC Syrtem [osser
Burns & McDonnell, Energy Division
Project Name:
32 'C
BURNsS,TsDoNNELL
Burns & McDonnell, Energy Division
Project Name:Pacificorp 2018 Renewables Technology Assessment
VC2 Date: 31-Aug-18
Energy Production Summary
Caty / Stete
Latitude {N):422'
l-ongitude (W)-120 '
Altitude
ASHRAE Cooling oB Temp.31 'C
ASHRAE Extreme Mean Min.Iemp.-22 'C
Sit€ lnfolmation
P50 net production vFr)12291.9 MWh
AC capacity factor - hv Ratins 2A_06%
ACcapacity factor - POI RatinF 28.06%
DC capacityfactor 7t.20%
Speciflc Production
Performance Ratio PR 4o.12%
NiSht iim€ losses .21.2 MWh
Plant Output Limitations 0.00%
Estimated Annual EnerSy Production
System DC Volta8e 1500 vDc
GCR 36%
5.5 m
Mounting
Tilt an8le or rotation limits 60'
0
TRUE
too.o %
DeSradation O-5'Alyt
De3i8n Parameters
6.62 MWDC
19188
5.OO MWAC
1
lnterconnection Limit 5-OO MWAC
lnteconnection Voltaae 34.S kV
OC/AC ratio. POI RatinS t.324
tacility Lev€l lntormation
Module rating 345 W
f Modules per ltrin8 26
Strings in parallel 73a
Totalnumber of module!19188
DCcapacity 6620 kW
5000 lw
DC/AC ratio - lnv Rating 1.324
Array Level lnrormation
TMYS
GHI 1704.3 kwh/m2
DHI
GlobalPOA 2300.2 kwh/m2
7.87 'C
Average Temp. (Generation)12.57'C
3.33 m/s
AveraSe wind (Generation)3.63 m/s
Tranrposition model
Constant thermalloss factor (Uc)25.0 w/m2-K
wind loss factor lUv)
SoilinS loss€s 2.2 %
LiSht aoduced degradation 2.O %
DC wirinB loss 1.5 %
-o.4 %
Module mismatch loss
OC h€alth loss 1.0 %
Pvsyst lnput Parameters
MV transformer no-load losses o.o7%
lrV transformer fullload losses 0.85%
MV collection system O.1V,6
HV transformer no-load losses 0.o0%
HV transformer full load losses 0.00%
0.00%
0.01%
AC Syslem Lo3s€i
1447 m
1.0 %
BURNS\/tsDONNELL
Burns & McDonnell, Energy Division
Project Name:Pacifi corp 2018 Renewables Technology Assessment
VC2 Datei 31-AuB,18
City / State;
42_2'lstitude (N)
Lon.itude (wl '120 '
1441 m
A5HRAE Cooling DB Temp.
ASHRAT Extreme Mean Min. T€mp.-22 'C
Site lnformation
P50 net production (vrl)130139.1 r/Wh
AC caDacitvfactor - lnv RatinE 27.01%
AC capacity factor - POlReting 29-17%
DC c.pacity factor 20 40%
Specific Produrtion
Performance Ratio PR 71.70%
Nithr time loss€s ,411.2 MWh
PlanlOutputUmitations 2_13%
Estlmared Annual Energy Produ.tlon
1500 vDcSystem DC VoltaSe
36%G'R
5.5 m
nit angle or rotation limits
0
TRUETracIinS strateBy
100.0 %
Detradation o.s %lyt
D€dgn Paramelers
Nameplate Capacitv 72.42 MWOC
211068
Nameplate Capacity 55-00 MWAC
11
lnterconnection Limit 50-oo Mwac
I nteconne.tion Voltage 115 kV
DC/AC ratio - POlRatinB 1.456
Facilhy L€v€l lnf o.mallon
345 WModule rating
, Modules per strins 26
Skings in parallel 738
19188Totalnumber ofmodules
DC capacity 6620 kW
5m0 kwlnverter rating
DC/AC ratio - lnv Ratin8 1.324
Ar.ay Level lnrormatlon
TMY]
GHI 1704.3 kwh/m2
DHI
GlobalPOA 2300.2 kwh/m2
7.87 "C
Averaqe Temp. {Generation)12.57 'C
3.33 m/s
AveraS€ Wind (ceneration)3.61 m/s
Transposition model
Const.nt thermal loss factor lUc)25.0 w/m2 k
wind loss factor (Uv)
Soilin8losses
2.O %Litht induced deBradation
DC wiring loss
-o.4 %Modul€ quality loss
Mod!le mismatch loss 1.0 %
to%DC health loss
PVsyrt lnput Parameterr
MV transformer no-load losses 0.07%
MV transformer full load losses 0.8s%
MV collection system 1.30%
HV transformer no-load losses o.o7%
HV transformer fLrll load lolses o.48%
0.05%
0.01%
Energy Production Summary
Burns & McDonnell, Energy Division
Pacifi corp 2018 Renewables Technology Assessment
vc2 Oate:31-Aug-18
Energy Production Summary
Caty/state:
Latitude (N)42.2 '
tonsitude lw):-120'
1441 m
ASHRAE Cooling DB Temp.3l'c
ASHRAE Extreme Mean Min. Temp.-72'C
Site lnformation
P50 net production (yr-1 520556.4 MWh
AC capacity factor- lnv Ratin8 27.O1%
AC capacity factor - POI RatinS 29_71%
20.40%DC capacity factor
Specific Production
Performance Ratio PR 77 -70%
-16,14.8 MWhNight time losset
2_75%Pl.nt Output Limitations
Estimated Annual tneray Production
Syrtem DC VoltaSe 1500 vDc
GCR 36%
S.5 m
Mountint
Tilt ansle or rotation limits 60'
0
TRUE
Availability 100.0 %
OeBradation O.5 %lyt
DeilSn Param€ters
Nameplate Capacity 291.27 MWDC
844172
Nameplate CapacitV 220-00 MwAc
44
lnterconnection Limit 200.00 Mwac
lnteconnsction Voltage 230 kv
OC/AC r.tjo - POlRating 1.456
Facility Level lnf ormation
Module rating 34S W
P Modules per strinE 26
Strings in parallel 734
Totalnumberof modules 19188
DC capacity 6620 kW
5000 k\{
DC/AC ratio - lnv Rating 1.324
A.ray level lnf ormation
TMY3
GHi 1704.3 kwh/m2
DHI
2300.2 kwh/mzGlobalPOA
7.81 "C
Averaae Temg. (Generation)12.57 'C
3.33 n/s
Average Wind (Generation)3.63 m/s
Transposition model
Constant thermal loss fador (Ucl 25.O w lml K
Wind loss factor (Uv)
5oilina losseg 2.2 %
LiSht induced deBradation 2.O %
OCwiring lots 1_5 %
n_4 %
Module mismai.h loss 1,.O %
DC health loss 1.0 %
PVryrl lnput Parameters
o.o7%MV transformer no-load losges
Mv tranrformer full load loss€s o.a5%
1.30%MV collection synem
HV translorm€r no-load losses o.o7%
HV transformer full load losses o.4E%
HV Iine o.o5%
0.01%
AC Syst€m Losses
BURNsS,IsDONNELL
Project Name:
BURNS\,TsDONNELL
Burns & [,4cDonnell, Energy Division
Pacificorp 2018 Renewables Technology Assessment
VC2 Oatei 3l Aug l8
Milford, UTCity / State
Latitude (N):38.4 '
-113 'LonBitude (Wl:
1534 mAltitude
34.9'CAsHRAE Coolins DB Temp.
-23.1 'CASHRAE €xtreme Mean Min. Temp.
Site lntormation
P50 net production {yr'1)13450.8 MWh
AC capacity fador - lnv Rating 30.71%
Ac caoacity factor - POI Ratina 30.7t%
DC capacity factor 23.20%
Specific Production
Performan.e Ratio PR 79.48%
Night time losres 20.8 MWh
Plant Output Limatations 0.oo%
f Jtimeted Annual Energy Productlon
System DC VoltaSe 1500 voc
GCR 36%
5.5 m
Mounting
Tilt antle or rotation limits 60
0
Trackins stratesv TRUE
Availability 100.0 %
O.5 %lttDegradation
D€sign Parameters
Nameplate Capacity 5.52 MWOC
Nameplate Capacity 5.00 Mwac
I
lntertonne(tion Limit 5.00 Mwac
hteconn€€tion Voltage 34.5 kV
OC/AC ratio - POI Ratina 7.324
Facillly L€vel lnf ormation
145 W
16r Modules per strang
Strines in parallel 738
Iotalnumber of modules 19188
DC cap3city 6620 kW
5000 kw
| 324DC/AC ratio - lnv RatinS
Array [€v€l lntormalion
Source NSRDB PSMv3
GHI 1903.4 kwh/m2
DHI
GlobalPoA 2556.6 kwh/m2
9.92 'C
Av€raEe Temp. (Generation)14.91 'C
2.11'I,ls
Av€ra8€ Wind (Generation)2.82 'r,ls
franspositaon model
25.O Wlmz-KConstantth€rmal loss factor (U.)
wind loss f.dor (uv)
Soilins losses 2.2 %
Lisht induced de.radation 2.0 %
DC wiring loss 1.5 %
{.4 %
Module mismatch loss 1.0 %
DC health loss 1.0 %
Pvsyst lnput Paramet€r
MV transformer no-load losses o.o7%
MV transformer full load losses 0.45%
MV collection system o-10%
HV transformer no-load losse5 0.00%
HV transformer full load losses 0.00%
0 007"
0.0r96
AC System Lorses
Energy Production Summary
Project Name:
19188
BURNS\{sDoNNELL
Burns & McDonnell, Energy Division
Project Name:Pacificorp 2018 Renewables Technology Assessment
VC2 Date: 31.Aus 18
City/state:Milford, UT
Lrtitude (N):3a.4 '
Lonsitude (W):-113 "
1534 m
ASHRAE Cooline DB Temp 34.9 'C
ASHRAT Extreme Mean Min. Temp.23.1 'C
site lnformation
PSo net oroduction (vrl)142375.3 MWh
AC capacity factor - lnv RatinS 29.55%
AC capacity factor - POIRatinE 32.51%
DC capacity factor 22.12%
Specific Production
Performance Ratio PR 76.4A%
Night time losses -401.9 MWh
Planr Output Limitations 2_76%
Estimated Annual Enerty Production
System DC VoltaBe 1500 voc
GCR 36%
5.5 m
Mounting
Tllt anale or rotation limitt 60
0
TRUE
100.0 %
DeEradation o.s %l\l
De6i8n Paramat€rs
Nameplate Capacity 72.82 MWDC
Number of modules 211068
Nameplate Capacaty 55.00 MWAC
11
lnterconneclaon Limit 50.00 Mwac
lntecoonection Voltage 115 kV
DC/AC r.tio - POI RatinS 1.456
Eacllily Level lnformation
Module rating 145 W
I Modules per strins 26
Strin8s in parallel
Iotalnumbe. ofmodules 19188
DC capacity 6520 kW
5000 kw
DC/AC ratio - lnv Raring 7.124
Array Level lnrormation
Source NSRDB P5Mv3
GHI 1903.4 tWh/m2
DUt
GlobalPOA 2556.6 kWh/m2
9.92 "C
Average Temp. (Generarion)14.91 "C
2.11 m/s
Average Wind (Generation)2.82 mls
fransposition model
Constant thermal loss factor lUc)2s.0 w/m2-x
Wind loss factor lUv)
Soiling losses 2.2 %
Lisht jnduced desradation 2.O %
DC wirinS loss 1.5 %
-o.4 %
Module mismatch loss 1_0 %
DC health loss 1.O %
Pv3yst lnput P.rameters
MV transformer no-load losses o.o7%
MV transformer tull load losses o-85%
MV collection system 1.30%
HV transformer no load losses o.o1%
HV transformer full load losses o.48%
0.05%
0.01%
AC Syiem to$es
Energy Production Summary
BURNS\,tsDONNELL.
Burns & McDonnell, Energy Division
Project Name:Pacifi corp 2018 Renewables Technology Assessment
VC2 Date: 31 AUE 18
Energy Production Summary
City/state:N,lilford, UT
Latitude lN):38.4 '
LonsitLrde (Wl
1534 mAltilude
ASHRAT Coolina 08 Temp 34.9'C
-23.1 'CASHRAE Extreme Mean Min. Temp.
Slte lnformation
P50 net production (yr-1)569501.1 MWh
AC capacity factor'lnv RatinE 29.55%
AC capacity factor . POI RatinS 32-31%
OC ctspacity factor 12.12%
Specific Production
Performance Ratio PR 7614%
Night time losses -1607.7 MWh
Plant Output Limitations 2_16%
Estlmated Annual Enecy Productlon
System DC Volt.Be 1500 vDc
GCR 36%
S.5 m
TrackerMounti.8
Tilt angle or rotation lamits 60'
0
TRUT
Availability 100.0 %
o.s %lytOeSradation
Desitn Param€teri
Nameplate Capacity 291.27 MWDC
8r'.4272
Nameplate Capacity 220.m MWAC
44
lnt€rconnection Limit 200.00 Mwac
lnteconnection Voltage 230 kV
DC/AC ratio' POI Ratiflg 1.456
f a.illty L.vel lnformation
Module ratins 345 W
fl Modules per string 25
strinas in Darallel 138
Totalnumber of modules 19188
OC(aoaciW 6620 kW
5000 kw
OC/AC ratio'lnv Ratint 1_124
array Level lnf ormation
NSRDB PSMV3
GHi 1903.4 kwh/m2
DHI
GlobalPOA 25S6.6 kWh/m2
9.92'C
Averase T€mp. (Gen€ration)14.9r'C
2.11 m/s
Average Wind (Generation)2.82 nls
Transposition model
25.0 w/m2'(Constant therma I loss fBctor lUc)
Wind los! factor (Uv)
2_2 %Soilint losses
Lisht induced dearadation 7.O %
DC warint loss LS%
-o.4 %
10%Module mismatch loss
oC health loss 7.0 %
PVsyst lnput Paramelers
MV transformer no-load losses 0.o7%
MV transformer fullload losses 0.85%
MV collection system 1.30%
HV transformer no-load losses o.o7%
HV transformer frrll load losses o.48%
0.05%
0.01%
kwh/m2
BURNs\{sDoNNELL
Burns & Mcoonnell, Energy Division
Pacificorp 2018 Renewables Technology Assessment
vC2 Date: 31'Aur 18
Energy Production Summary
City / State:Rocl SprinSs, Wyoming
tatitude (N)41.6 "
Lonsitude lwJ -109 "
2035 m
ASHRAE CoolinS DB Temp.29.8 'C
ASHRAE Extreme Mean Min. Temp.-25.1 'C
Site tnformataon
PsO net production (yr-l)12343.3 MWh
AC capacity factor - lnv RatinS 28.r8%
AC capacity factor - POlRating 28.18%
0C capacityfactor 21_29%
Specific Production
Pe*ormance Ratio PR 42.fi%
NiSht time losses -20.0 Mwh
Plant Output timitations 0.00%
Estlmated Annual Energy Produclion
System DC Volta8e rs00 vDc
GCR 36%
S.5 m
Mounting
Tilt ansle or rotation limitt 60'
0
TRUT
100.0 %
Oegradation o.5 %l,tt
Deslgn Parameters
Nameplate Capacity 6.52 MWOC
19188
Nameolate Capacity 5.00 MwAc
1
lnterconnection timit 5.00 MwAc
lnteconnection Voltage 34.5 kV
DC/AC ratio ' POI Ratint 1.124
f acility Level lntormalion
Module rating 345 W
n Modules per strin8 26
String5ln parallel 718
Totalnumberof modules 19188
DC capacity 6620 kW
5000 kw
DC/AC ratio - lnv Rating 1.324
Array level lnlormaiion
TMY3
GHI 1693.s kwh/mz
oHt
2269.3 kwh/m2GlobalPOA
6.49 'C
Averar€ TemD. IG€neratio.)10.35'C
4.81 m/s
Averase Wind (Generation)5.32 mls
Transposition model
Consta nt thermal losr facto I lUc)25.0 w/m2 K
Wind loss factor (Uv)
Soilins losses
Light induced deEradation 2.O %
DC wiring loss t.5 %
-o.4 %
Module mismatch loss 1.0 %
OC h€alth loss t.o %
Pvsysl lnput Parameters
MV transformer no-load losses o.o7%
MV tra nsformer fLr ll load losse5 0.85%
MVcollection system 0.70%
HV transformer no-load losses 0.00%
HV t ransformer full load losses 0.00%
0.0tr6
0.01%
Ac system lolles
Project Name:
BURNS\,TsDONNELL
Bums & McDonnell, Energy Division
Proiect Name:Pacifi corp 2018 Renewables Technology Assessment
vc2 Date 31-Au8-18
Energy Production Summary
Ro.k Sprinss, Wyomins
Latitude {N)41.6 '
-109'Lonsitude {W)
2055 mAltitude
ASHRAE Cooline DB Iemp.29.8 ',C
-25.1 'CASHRAE b(reme Mean Min. Temp.
Site lnlormataon
PSo net productaon lyr.ll 131702.0 MWh
AC rap.city factor - lnv Ratint 27.34%
AC capacity factor - POI Ratins 10_o1%
DC capacity factor 20-65%
Specific Production
Performan.e Ratio PR 79.70%
Ni8ht time losses 387.3 MWh
PlantOutputtimitations 2-O4%
Estlmated Annu.l Encrgy Production
system DC Voltage 1500 vDc
GCR 36'
5.5 m
Mounting
Tilt anEle or rotation limits 60
0
TBUE
100.0 %
o.5.alyroegradation
Oesign Parameters
Nameplate Capacitv 72.82 MWDC
211068
Nameplate Capacity 55.00 MWAC
11
lnterconnection Limit 50.q) Mwac
lnteconnection Voltage 115 kV
DqAC ratio - POI RatanB 1.456
Facility Level lnformation
345 WModule rating
26fl Moduleg per strinE
Strines in parallel
Iotalnumber ofmodules 19188
6620 kWDC capacity
s000 kw
1.324OC/AC ratio lnv RatinS
Array Level lnf o,mation
IMY3
GHI 1693.s k\r,/h/m2
DHI
GlobalPOA 2269.3 kwh/m2
6.49 "C
Avera8€ Temp. IGeneralion)10.35 "c
4.81 m/s
Avera8e Wind (Gen€ration)s.32 m/s
Transposition model
25.0 Wln2.XConstant thermalloss factor (Uc)
Wind loss factor (Uv)
2_2 %Soiling losses
2.0 %Light induced degradation
DC wting loss 7_S %
-0.4 %
1.0 %Modul. mismat.h loss
1.0 %DC health loss
Pvsyst ln?ut Peramet€15
MV transformer no-load losses o.o1%
MV transformer full load losses 0.85%
MV colle.tion system 1.30%
Hv transformer noload losse5 o.o7%
0.48%HV i ransformer fu ll load lo<ses
0.05%
0.01%
AC Syitem loss€s
Ciry/ St te:
Burns & McDonnell, Energy Division
Project Name:Pacificorp 2018 Renewables Technology Assessment
VC2 Oate: 31-Aug'18
Energy Production Summary
City / Statel Rock Sprina!, Wyoming
Latatude (N)41-6 ',
Lonsitude {W)-109'
2055 fi
ASHRAE CoolinE Dg Temp.29.8 'C
ASHRAE Extreme Mean Min. Temp--25.1 'C
Site lnformalion
P50 net production (y.1)526808.1 MWh
AC capacity fector- lnv Rating 27.34%
AC capacitv f.ctor - POI RatinR 30.07%
DC capacity factor 10_65%
Specific Production
Performance Ratio PR 79-70X
Nithttime losses 1549.3 MWh
Plant Output Limitations 2.U%
Estimated Annual En€rgv Produ(tion
System DC Voltage 1500 vDc
GCR 36%
5.5 m
Mounting
Tilt angle or rotation limit5 60'
o
Trackina strategy TRUE
100.0 %
Degradation o.s %/yt
Desitn P.rameters
291.27 MWI)G
8/,4272Number of module!
220.00 Mwac
200.00 MwAc
230 kv
1.456
tacilily L€Yel lnf ormatlon
Module ratinS 345 W
i Modules per string 26
Strings in par.llel
Iotal number of modules 19188
OC capacity 5620 kW
lnvert€r ratint 5000 kw
OC/AC ratio - lnv RatinS 1.324
ArIey Lev€l lnrornatlon
Source TMY3
GHL 1693.5 kwh/m2
oHr
GlobalPOA 2269.3 kwh/m2
6.49 'C
Averase Temp. lG€neration)r0.35'c
4.81 m/s
Average Wind {Gen€ration)5.32 m/s
Transposition model
Constant thermal loss fador (Uc)2s.0 Wm2-(
Wind loss factor (Uv)
Soiling losses 2.2 %
LiSht induced derradation 2.0 %
DCwtinB loss 1.5 %
-o.4 %
Module mismatch loss l.o %
1.0 %
Pvsyst lnpul Param€ters
MVtranslormer no load lortes 0.07%
MV t.ansformer fu ll load lo5ses 0.85%
MV collection system r.30%
HV transformer no-load losses o_o1%
0.48%HV translormer fullload lo.ses
0.05%
0.01%
AC System losles
BURNsS/tsDoNNELL
734
Nameplate Capacity
Nameplate Capaclty
lnterconoection Limit
lnte.onne.tion vohage
oc/Ac retio - Pol Ratina
BURNS${sDONNELL
Burns & McDonnell, Energy Division
Project Name:Pacificorp 2018 Renewables Technology Assessment
VC3 Date: 31'Aug'18
Energy Production Summary
City/state
466Latitude {N):
-120.5'LonSitud€ (W)
324 n
34.1 "CASHRAE Cooling DB Temp.
ASHRAT €xtreme Mean Min. Temp -1,7 'C
site lnformation
P50 net production {yr-1)10609.2 MWh
AC capacitv factor' lnv Ratina 24.22%
AC capacity factor . POI RatinS 24.22%
DC capacity fa6or 18.29%
Specific Production
Performance Ratio PR 8r.56%
NiEht tim€ losses
PlantOutput Limitations 0.00%
[3timated Annual Ene,8y Production
1500 vDcSystem DC VoltaSe
36%GCR
5.5 m
Mounting
60Tilt angle or rotation limits
0
IRUETracking strateSy
100.0 %
DeBradation O.5 %/yt
Deilgn Paramater
6.62 MWOC
Number of modules 19188
Nam€plate Caparity 5.00 MwAc
1
lnterconnection [imit 5.00 Mwac
I nteconnection VoltaEe 34.5 kV
DCIAC ratio - POlRating 1.324
f aclllty tev.l lntormation
345 WModule rating
# Modules oer strina 26
Strines in parall€l 738
19188Iotalnumberof modules
DC capacity 6620 kW
s000 kw
DC/AC ratio' lnv RatinR 1.324
Array L€v€llnformadon
TMY3
GHI 1486.8 kWh/m2
DHI
GlobalPOA 1964.9 kwh/m2
9.97'C
Averaae Temp. {6eneration)14.53'C
3.r7 mls
Av€rage Wind (Gene.ation)3.30 m/s
Transposition model
Consta nt thermal loss factor (uc)2s.0 Wm2'K
wind loss factor (Uv)
SoilinB losses 2.4 %
2.O %LiBht induced deSradation
t.s %OC wiring lois
-o.4 %
Module mismatch loss 1.0 %
1.0 %OC health loss
Pvsyst lnput Pammele6
MV transformer no-load loss€s 0.07%
MV Vansformer fullload losses 0.85%
MV roll€ction system o.709t
Hv tranrrormer no-load losses 0.00%
HV transformer tull load losses 0 00%
0.00%
0.ot%
AC Syslem Losses
BURNsN{sDoNNELL
Project Name:Pacificorp 2018 Renewables Technology Assessment
VC3 Oate: l1-aug-18
Energy Production Summary
City / State:
Latitude (N)46.6 '
Lonritude iw)-120.5 '
324 m
ASHRAE CoolinS DBTemp.34.1 "C
ASHRAE Ertreme Mean Min. Temp.-17'C
Slte lnlormation
P50 net production (yr-1)114064.6 MWh
AC capacity factor - lnv RatinE 23_61%
AC capacity factor - POI Rating 26.O4%
OC capacity factor 17.88%
Specific Production
Pe.formanc€ Ratio PR 79.72%
NiAht tim€ losses -389.2 MWh
Plant Output Limitations 7_32%
Ettlmated Annual Energy production
System DC Voltage 1500 vDc
GC8 36%
5.5 m
MoLrnting
Tih angleor rotation limits 60"
0
TrackinS stretegy TRUE
100.0 %
De8radation O-5 %lyt
Design Param€ters
Nameplate Capacity 72.E2 MWOC
Nameplate Capacity 55.00 MWAC
1l
lnterconn€ction Limit 50,00 Mwac
lnteconneation voltaSe 115 kV
1.456DC/aC ratio - POlRatin8
Facility Level lnf ormalion
Module rating 345 W
{ Modules per string 26
Strinss in parell€l 138
Totalnumber of modules r9 r88
OC capacity 5620 kW
5000 kw
DCIAC ratio'lnv Rating 1.324
A.ray tevel lnformatlon
IMY3
GHI 1486.8 kwh/m2
DHI
GlobalPOA 1964.9 kwh/m2
9.97 'C
AveraEe Temp. lGeneration)14.53'C
3.17 m/s
Average Wind (G€neration)3.30 m/s
Transposition model
Con5tant the.mal loss factor (Uc)25.0 Wm2-K
Wand loss factor (Uv)
Soiling losses
Li8ht induced detradation 7.O %
OC wiring lols
o.4 %
Module mismatch loss
DC health loss 7-0 %
Pvsyst lnput Parameters
Mv transformer noload losses o o7%
MV transformer full load Iosses 0.85%
Mv collection system 1.30%
HV transformer no-load losses o.o7%
0.48%HV transformer fullload losses
0.05%
0.01%
AC System Loiser
Burns & McDonnell, Energy Division
1.5 %
7.O %
2r1068
BURNsS{EDONNELL
Burns & McDonnell, Energy Oivision
Pacificorp 2018 Renewables Technology Assessment
VC3 Date: 31 Au8 18
Energy Production Summary
City/State
Latitude (N)
-120.5 "Lon8itude {w)
324 m
ASHRAE CoolinE DB Temp.34.1 'C
-17'cASHRAE Extreme Mean Min, Temp
Site lnformation
P50 net production (yr-1)
AC capacity factor - lnv RatinB 23.67%
ACcapacitYf.ctor POI Rating 26.O4%
DC ca pacity faclor 17.88%
Specific Production
Pedormance Ratio PR 79.72%
Night time losses ,1556.8 MWh
Plant Output Limitations r_32%
Esrimated annual Eneray Produ.tlon
Syrtem DC Voltat€1500 vDc
GCR 36%
5.5 m
Mountine Tracker
50"Tilt anSle or rotation limits
0
TRUETrackinS strategy
1m.0 %Availability
Oegradation o.s %/yl
Desitn Param€ters
Nameplate Caga(ity 291.27 MWOC
Numberof modules a44272
Nameplate capacity 220.00 Mwac
lnterconne€tion Umit 2m.m MwAc
lnteconnection Voltace 230 kv
oq/AC ratio ' POI Ratint 1.456
Facility L€1,el lntormatlon
Module.atin8 345 W
, Modules per strinp 26
StrinB5 in parallel
19188Totalnumber ofmodules
DC capacity 6620 kW
smo kwlnvener rating
DC/AC ratio - lnv Ratin8 1.324
Array Level lnf ormation
Source TMY3
GHI 1486.8 kwh/m2
DHI
GlobalPOA 1964.9 kwh/m2
Avera8e T€mp-9_91 'C
Averase TemD. {Generationl
Average Wind (G€neration)3.30 m/s
Transposition model
Constant thermal loss factor (uc)2s.0 w/m2.K
Wind loss factor (Uv)
SoilinB losses 2.4 %
2.O %LiSht induced deSradation
DC wiring loss 1.5 %
.o.4 %
1.0 %Module mismatch loss
1.0 %DC health loss
Pvsyst lnput Parem€ter
MV transform€r no'load lors€s 0_o7%
Mv transformer full load lorres 0.85%
MV coll€ction system 1.30%
HV transformer noJoad losses o.o7%
HV tra nsformer lull load losses 0.48%
0.05%
0.01%
AC System loss€r
Proiect Name:
14.53 'C@-
APPENDIX D - WIND PERFORMANCE INFORMATION
A I
ldaho - AnnualAverage Wind Speed at 80 m
tto 1't4"112"
48'Wind Speed
m/s
>10.5
10.0
9.5
9.0
8.5
8.0
7.5
7.0
6.0
5.0
4.5
4.0
< 4.0
IIIIII
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BURNs\StToNNELL-
CREATE AMAZING.
Burns & McDonnell
9785 Maroon Circle. Suite 4OO
Centennial, CO 8Oll2o 303-7 21-9292
F 303-72r-O563
www.burnsmcd.com
Appt NDx P - R.ENEWABI.! RrsouRCEs AssEssMENT
576
PACIIICORP _ 2OI9 IRP
ArerNotx Q - ENency Sronecp PorpNrrel
EvaluauoN
Energy storage resources can provide a wide range ofgrid services and can be flexibly sized and
sited. Many of these grid services have been increasing in value with increasing penetration of
variable energy resources such as wind and solar, while energy storage costs have been falling. As
a result, storage resources are an increasing component of PacifiCorp's least-cost, least-risk
preferred portfolio. While the 2019 IRP portfolio analysis captures the system benefits of energy
storage, it does not fully account for localized benefits and siting opportunities. This appendix
provides details on how energy storage resources can be configured to maximize the benefits they
provide.
Because energy storage resources are highly flexible, with the ability to respond to dispatch signals
and act as both a load and a resource, they can potentially provide any ofthe grid services discussed
herein. Other types of resources, including distributed generation, energy effrciency, and
interruptible loads can also provide one or more of these grid services, and can complement or
provide lower-cost altematives to energy storage. Given that broad applicability, Part I of this
appendix first discusses a variety of grid services as generically and broadly as possible. Part 2
discusses the key operating parameters of energy storage and how those operating parameters
relate to the grid services in Part l Finally, Part 3 discusses how to optimize the configuration and
dispatch of energy storage and other distributed resources to maximize the benefits to the local
grid and the system. Part 3 also provides examples of specific applications and examples of
applications that may be cost-effective in the future.
PacifiCorp must ensure that sufficient energy is generated to meet retail customer demand at all
times. It also must maintain resources that can respond to changing system conditions at short
notice, these operating reserves are held in accordance with reliability standards established by the
National Electric Reliability Corporation (NERC) and Western Electricity Coordinating Council
(WECC). Both energy and operating reserves are dispatch-based, and dependent on the specific
conditions at a specific place and time. These values are generally independent from hour to hour,
as removing a resource in a subset ofhours may not impact the value in the remaining hours.
Because load can be higher than expected and some resources may be unavailable at any given
time, suffrcient generation resources are needed to ensure that energy and operating reserve
requirements can be met with a high degree of confidence. This is referred to as generation
capacity. The transfer ofenergy from the locations where it is generated to the locations where it
is delivered to customers requires poles, wires, and transformers, and the capability ofthese assets
is referred to as transmission and distribution (T&D) capacity. Generation and T&D capacity are
both generally asset-based, and provide value by allowing changes in the resources and T&D
elements. In general, assets cannot be avoided based on changes to a subset of the hours in which
they are needed and only limited changes are possible once constructed or contracted. It should
577
PACFTCoRP - 2019 IRP APPE},IDTX Q _ ENERCY STORAGE PoTENTIAL EVALUAIIoN
Introduction
Part 1: Grid Services
PAcTHCORP -20l9IRP AppENDrx Q- ENERGY STOLAGE P0TENTTAT. llvAr-uAr toN
also be noted that the impact ofasset or capacity changes on dispatch must also be included in any
valuation.
These obligations are broken down into the following grid services, which are discussed in this
sectlon. Energy, including losses;. Operating reserves, including:
o Spinning reserve;
o Non-spinningreserve;
o Regulation and load following reserves; ando Frequency responsel
o Transmission and distribution capacity; ando Generation capacity.
Energy Value
Background
Because PacifiCorp's load and resources must be balanced at all times, when an increment of
generation is added to PacifiCorp's system, an increment ofgeneration must also be removed. This
could take the form of a generator that is backed down, an avoided market purchase, or an
additional market sale. The cost ofthe increment that is removed (or the revenue from the sale),
represents the energy value, and this value varies by location and by time. Location can also impact
losses relative to the generation which would otherwise have been dispatched, with losses
manifesting as a larger effective volume. With regard to time, there are two relevant time scales:
hourly values, and sub-hourly values.
The energy value in a location is dependent on PacifiCorp's load and resource balance, the dispatch
cost of its resources, and the transmission capability connecting those resources to load.
Differences in energy value occur when the economic resources in area exceed the transmission
export capability to an area that must then use higher cost resources to serve load. Once
transmission is fully utilized, the higher cost resources must be deployed to serve the imponing
area and lower cost resources will be available in the exporting area. As a result, the value in each
location will reflect the marginal resources used to serve load in each area. Iltransfers are not fully
utilized in either direction, the marginal resource in both areas would be the same, and the energy
value would be the same.
Both load and resource availability change significantly across the day and across the year.
Differences in value over time are driven by the cost ofthe marginal resource needed to serve load,
which changes when load or resource availability change. When load goes up, or the supply of
lower-cost resources goes down, the marginal resource needed to serve load will be more
expensive.
The value by location is also dependent on the losses relative to the generation which would
otherwise have been dispatched. Losses occur during the transfer ofenergy across the T&D system
to a customer's location. As distance and voltage transformation increase, more generation must
be injected to meet a customer's demand. As a result, a distributed resource that is close to
customer load or located on the same voltage level can avoid both energy at its location as well as
the losses which otherwise would have occurred in delivering energy to that location. As a result,
578
PA(TrCoRP - 2019 IRP APPENDX Q_ ENERGY SToRAGE POTFNTIAI- EVALUATIoN
the marginal generation resource's output may be reduced by an amount greater than the metered
output ofa distributed resource. This increase in volume due to losses is also relevant to generation
and T&D capacity value. In addition to varying by location and voltage, losses vary across time,
primarily due to line loading, as loss rates increase as loading increases. To the extent distributed
resources impact line loading, it is reasonable to incorporate the marginal losses that they avoid.
Modelinq
There are two basic sources of energy values: market price forecasts and production cost models
There are also two relevant time scales: hourly values, and sub-hourly values.
PacifiCorp produces a non-confidential offrcial forward price curve (OFPC) for the major market
points in which it typically transacts on a quarterly basis. The OFPC represents the price at which
power would be transacted today, for delivery in a future period. The OFPC contains prices for
each month for heary load hour (HLH) and light load hour (LLH) periods and goes forward
approximately 20 years.r However, not all hours in the HLH or LLH periods have equal value. To
differentiate between hours, PacifiCorp uses scalars calculated based on historical hourly results.
For PacifiCorp's operations and production cost modeling, scalars are based on the California
Independent System Operator's day-ahead hourly market prices. Because these values are used in
operations, the details on the methodology and the resulting prices are treated confidentially. To
allow for transparency, PacifiCorp has also developed non-confidential scalars using historical
Energy Imbalance Market prices. With either scalars, the result is a forecast ofhourly market prices
that averages to the values in the OFPC over the course ofa month. Using hourly market price to
calculate energy value implies that market transactions are either the avoided resource, or a
reasonable representation of the avoided resource's cost.
Production cost models contain a representation of an electric power system, including its load,
resources, and transmission rights, as well as markets where power can be bought or sold. They
also account for operating reserve obligations and the resources held to cover those obligations.
All models are simplified representations, and there are several key simplifoing assumptions. The
granularity of a model is its smallest calculated timestep. While calculating twice as many
timesteps should take roughly twice as long from a mechanical standpoint, maintaining inputs to
represent those timesteps is more complicated, and a model is only as good as its inputs- To
simplifu the representation of location, transmission areas can be defined by the key transmission
constraints which separate them, with transmission within each area assumed to be unconstrained.
Another simplifuing assumption is to model all load and resources at a level equivalent to generator
input. For instance, load is "grossed up" from the metered volume to a level that includes the
estimated losses necessary to serve it. This allows for a one for one relationship between all
volumes, which vastly simplifies the model.
PacifiCorp's production cost models with these representations include the Planning and Risk
(PaR) model, used to evaluate portfolios in the lRP, and the Generation and Regulation Initiative
Decision Tools model (GRID), used to calculate net power costs in general rate cases and for some
qualifting facility avoided cost rates. Both ofthese models reflect the system down to an hourly
granularity. While these production cost models use the hourly market prices from the OFPC, a
distributed resource's energy value in these models will depend on its location and other
t HLH is 6:00 a.m, to l0:00 p.m. Pacilic Prevailing '[ ime Monday through Sanrrday, excluding N[.RC holidays. LLll
is all other hours.
579
PACTHCoRP - 20l9IRP AppENDrx Q- ENIRGY Sr 0&A,GE PorFNrrAL Ev r-r]ATroN
characteristics and can be either higher or lower than the market price in a given hour. Generally,
a resource's value is based on the difference between two production cost model studies: one with
the resource included, and one with the resource excluded. This explicitly identifies the marginal
resources dispatched in the absence ofthe resource being evaluated.
More detailed models of the electrical power system also exist, for instance PacifiCorp uses
physical models for grid operations and planning that account for power flows and the loading of
individual system elements. Similarly, the Califomia Independent System Operator (CAISO) uses
a "Full Network Model" with detailed representations of all resources and loads, as well as the
transmission system. CAISO's model includes a representation of PacifiCorp's system for the
purpose of dispatching resources in the Westem Energy Imbalance Market (EIM), and models a
five minute granularity for that purpose. The added detail these physical models produce comes
from a significant increase in the complexity ofinputs and computational requirements.
Hourly market prices can be used to provide a readily available estimate ofenergy value, as shown
in Table Q.l for various energy storage technologies. The variables which impact energy margin
include: hours of storage, efficiency, forced outage rates, and variable degradation costs. Table
Q.l contains twenty-year nominal levelized values for 2019-2038, and reflects an average ofthe
margins at the Mid-Columbia and Four Comers markets.
Table l-En Ma n SEn Techn
These market values do not account for the effects of location, volume, or operating reserve
requirements. For instance, PacifiCorp is obligated to hold contingency reserves equal to three
percent of all generation in its balancing authority areas, but is not required to hold those reserves
for market purchases. This is analogous to the additional regulation reserves held to account for
the variability and uncertainty in the output of wind and solar (a.k.a. integration costs).
Adjustments can be applied to account for these differences, but the results are likely to diverge as
market prices and resource portfolios change. Hourly market prices are also more likely to
understate the value of dispatchable resources.
The PaR model and the GRID model both identif, resources to carry operating reserves for each
hour, but do not include the intra-hour changes that would cause those resources to be deployed.
Because resources that are dispatchable within the hour can be dispatched up when marginal
energy costs are high, and down when marginal energy costs are low, this can result in incremental
value relative to an hourly market price or hourly production cost model result. In practice, sub-
hourly dispatch benefits are largely derived ftom PacifiCorp's participation in EIM, and the
specific rules associated with that market. For instance, resources must be participating in EIM in
order to receive settlement payments based on their five-minute dispatches. Resources that are not
participating receive settlement payments based on their hourly imbalance. Because non-
participating resources are not visible to the market, their sub-hourly dispatch would not impact
-s80
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6
9
PACII-ICoRP - 2019 IRP APPFXDIX Q _ I1NERGY STORAGE POTENTIAL EVALTIATION
the market solution. Because distributed resources can be aggregated for purposes of EIM
participation, size should not be an impediment; however, the structure of the EIM may dictate
some aspects of their use and would need to be aligned with the other services a distributed
resource provides.
To help identifu sub-hourly energy value not captured in its hourly production cost models, during
the development of the 2019 IRP, PacifiCorp calculated intra-hour flexible resource credits
(IHFRC) for a variety ofresource types, based on expected economic dispatch relative to historical
EIM sub-hourly pricing. Unsurprisingly given their flexibility, energy storage resources provide
the highest value ofthe resources evaluated, as shown in Table Q.2 below. Values shown are in
201 8$.
Table .2 - Intra-hour Flexible Resource Credits b Resource
PacifiCorp initially proposed that IHFRC values be netted out ofthe resource costs identified in
its supply-side resource table, such that the net costs would be used for portfolio selection and
valuation. In response to stakeholder feedback about the concept and methodology, the adjusment
for IHFRC values was not incorporated as part ofthe 2019 IRP. PacifiCorp anticipates that the
resources above would generate incremental value relative to the hourly granularity of the 2019
IRP modeling, but additional work is required to engage stakeholders and ensure that the results
are truly additional.
Operating Reserve Value
Background
Operating resewe is defined by NERC as "the capability above firm system demand required to
provide for regulation, load forecasting error, equipment forced and scheduled outages and local
581
Pumped Hydro 6-l4hr
CAES 4IIfu
Flow 6hr
Li-Ion 4hr
Li-lon 2hr
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25.02
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0.2 - 0.4
0.05
0.38
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nla
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18.51
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5.54
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5.6%
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(7o of Nameplate)SourceResourceCycles/dav
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level (%)Resource
Resource/Bid Price 9/o of annual outDut
*Resources are dispatched up and down ftom base schcdule in EIM.
P^crFrCoRr - 20l9IRP AppENDIX Q - INER(;Y S'r oR GE P0TENTIAT- EVAL[TATIoN
area protection."2 Operating reserves are capability that is not currently providing energy, but
which can be called upon at short notice in response to changes in load or resources. Operating
reserves and energy are additive - a resource can provide both at the same time, but not with the
same increment of its generating capability. Operating reserves can also be provided by
intemrptible loads, which have an effect comparable to incremental resources. Additional details
on operating reserve requirements are provided in Volume II, Appendix F (Flexible Reserve
Study).
As with energy value, operating reserve value is based on the marginal resource that would
otherwise supply operating reserves, and varies by both location, time, and the speed of the
response. Because operating reserve requirements are primarily applied at the Balancing Authonty
Area (BAA) level, the associated value is typically uniform within each of PacifiCorp's BA,.As.
An exception to this is that operating reserves must be deliverable to balance load or resources, so
unused capability in a constrained bubble without additional export capability does not count
toward the meeting the requirements. Operating reserve value is somewhat indirect in comparison
to energy value, as it relates to the use ofthe freed up capacity on units that would otherwise be
holding reserves. [f that resource's incremental energy is less expensive that what is currently
dispatched, it can be dispatched up, and more expensive energy can be dispatched down. The value
ofthe operating reserves in that instance is the margin between the freed up energy and the resource
that is dispatched down. Note that the dispatch price of the resource being evaluated does not
impact the value, since holding operating reserves does not require dispatch. When the freed up
resource is more expensive than what is currently dispatched, it will not generate more when the
operating reserve requirement is removed, and the value ofoperating reserves would be zero. With
this in mind, operating reserves are generally held on the resources with the highest dispatch pnce.
Finally, operating reserve value is limited by the speed ofthe response: how fast a unit can ramp
up in a specified time period, and how soon it begins to respond after receiving a dispatch signal.
Reliability standards require a range ofoperating reserve types, with response times ranging from
seconds to thirty minutes.
Modelinq
As discussed above, the value of incremental operating reserves is equal to the positive margin
between the dispatch cost of the lowest cost resource that was being held for reserve, and the
dispatch cost of the highest cost resource that was dispatched for energy. Similar to the value of
energy, the price of different operating reserve bpes could be forecasted by hour, based on
forecasts of reserve capability, demand, and resource dispatch costs. Given the range and
variability in these components, this would be an involved calculation. In addition, because
operating reserves are a small fraction ofload, they are more sensitive to volume than energy. For
instance, spinning reserve obligations are approximately three percent of load in each hour. As a
result, resource additions may rapidly cover that portion of PacifiCorp's requirement met by
resources that could otherwise provide economic generation and which produce a margin when
released liom reserve holding. This is particularly true for batteries and interruptible load resources
that can respond rapidly and thus count all or most oftheir output toward reserve obligations.
While a market price for operating reserve products does not align well with PacifiCorp's system,
the specifics ofthe calculation descnbed above are embedded within PacifiCorp's production cost
models. Those models allocate reserves first to energy limited resources in those periods where
: NERC Glossary of Tcrms: http://rvww.nerc.com/Iiles/gkrssary_ol_te rnrs.pdt, updated May 13,2019
582
PACTFTCoRP - 2019 IRP AppENDIx Q- [,NERcy S'roRACE Por[NTrAL ljvALUAlroN
they could generate, but are not scheduled to do so. Examples ofenergy limited resources include
intemrptible loads, hydro, and energy storage. Ifcalled on for reserves, these resources would lose
the ability to generate in a different period, so the net effect on energy value for that resource is
relatively small. As a result, the unused capacity on these resources can't be used for generation,
but that also means it can count as reserves without forgoing any generation and incurring a cost
to do so. After operating reserves have been fully allocated to the available energy-limited
resources, reserves are allocated to the highest cost generators with reserve capability in the supply
stack, up to each unit's reserve capability, until the entire requirement is met. This is generally
done prior to generation dispatch and balancing, because the requirements are input to the model
or based on a formula and aren't tlpically restricted based on transmission availability. After the
reserve allocations are complete, the remaining dispatch capability ofeach unit is used to develop
an optimized balance ofload and resources.
As part of the calculation of wind and solar integration costs for the 2019 IRP, as reported in
Volume II, Appendix F (Flexible Reserve Study), PacifiCorp prepared a study assessing the cost
ofholding incremental operating reserves. That study identified a cost of$sO/kw-yr (2018$), based
on a 2018-2036 study period. This value would be applicable to any resource that provided
operating reserves uniformly throughout the year.
Transmission and Distribution Capacity
For the first time, the 2019 IRP has endogenously included transmission upgrades as part of
portfolio selection. This allows the cost of transmission upgrades to be considered as part of the
modeled cost ofresources in each area. However, energy e{ficiency, load control, and stand-alone
energy storage resources were not subject to these constraints, placing them at an advantage
relative to both thermal and renewable resource options. In addition, while the cost of specific
T&D projects varies, a generic system wide estimate of transmission upgrade costs is included as
a credit to energy effrciency in the 2019 IRP, and amounts to $4.l6lkw-year (2018$). ln practice,
these costs would vary by project and some transmission upgrades would not be suitable for
deferral by distributed resources. Because ofthe large scale of many transmission upgrades, and
the binary nature ofthe expenditures, it may be difficult to procure adequate distributed resources
to cover the need in a timely fashion and in accordance with reliability requirements, though it is
always appropriate to consider the available options when considering expenditures on an upgrade.
Distribution capacity upgrades are more likely to be suitable for defenal by a distributed resource,
as the scale of tlte need is closer to that ofthese types ofresources.
To that end, PacifiCorp maintains an "Alternative Evaluation Tool" which is used to screen the
list of projects identified during T&D planning to assess where distributed resources, includrng
energy storage, could be both technically feasible and cost competitive as compared to traditional
T&D solutions. Ifa study shows that distributed resource altematives are feasible and potentially
cost-competitive that project is flagged for detailed analysis.
To help illustrate the potential for distribution capacity deferral, PacifiCorp assessed the peak
loading and forecasted gro*th at each ofthe distribution substations across its system. Once peak
loading reaches 90 percent ofa distribution substations capability, PacifiCorp takes steps to either
reconfigure the loads or add capacity to ensure that it remains sufficient to serve customers. For
this analysis, substations were classified as having a high potential for distribution capacity
deferral if their current loading is at or above the 90 percent threshold, medium if they are
583
AppE}.Drx Q - tNERcy SToRAGE PorENThr EvALrrA' oN
anticipated to exceed the 90 percent threshold within the next twenty years, and low ifdrey are not
expected to exceed the 90 percent threshold in the next twenty years. The results shown in Table
Q.3 identiS, the portion of PacifiCorp's distribution load that is part of each of these three
categories in each state. The "low" category represents a majority ofPacifiCorp's system, which
indicates that programs targeting distributed resources in specific locations have the potential to
provide significantly greater value.
Table .f, - Share of Distribution Load State with Potential U Deferral
Because distribution upgrades are primarily driven by load growth, distributed resources need to
be sufficient to maintain load within existing peaks to defer distribution upgrades. Energy storage
resources can be cost-effective to cover briefpeaks, but are less cost-effective as the duration of
the shortfall increases. To the extent load in an area continues to grow, the deferred distribution
upgrade is likely to be necessary eventually. Table Q.4 illustrates the distribution load growth by
state that is likely to trigger distribution upgrades during the IRP planning period. The forecasted
distribution capacity deferral value is $21 .89/kw-yr (201 8$) for substations with a planned upgrade
that can be deferred indefinitely. If distributed resource programs result in resources on a mix of
substations that include medium or low value areas, the effective distribution capacity deferral
value would be reduced.
Table .4 - Forecasted Distribution Load Growth Above the 90 Percent Plan Threshold
CA
ID
OR
UT
WA
WY
38o/o
360/o
30%
32%
2t%
84%
23%
5t%
62%
43%
72%7%
t3%
l3o/o
8o/o
Total l3v"3tv"56v"
20t9
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
I
I
I
I
I
I
I
2
2
2
2
2
2
2
2
2
2
2
2
2
l9
72
22
23
23
3l
34
35
35
35
35
39
40
40
43
46
46
5l
5l
57
79
108
ll6
t23
164
164
165
t70
t7z
t94
t96
206
248
279
313
353
357
367
384
395
t2
l8
t8
2t
25
25
26
26
30
33
JJ
JI
,J
3l
36
36
36
36
36
43
9llll
ll
llll
ll
ll
t4
t4
55
55
59
59
6l
63
68
68
68
70
30
30
30
42
42
5l
63
72
74
77
86
90
94
99
t)g
l0l
t06
108
I l5
ll8
r5t
190
199
22t
266
283
300
315
327
354
406
424
476
5ll
554
601
615
633
655
679
584
PACTFICoRP - 2019 IRP
State Hish Medium Low
38o/o
Year WACAIDORUT WY Total
Generation Capacity
Backeround
To provide reliable service to customers, a utility must have sufficient resources in every hour to:o Serve customer load, including losses and any unanticipated load increase.. Hold operating reserves to meet NERC and WECC reliability standards, including
contingency, regulation, and frequency response.
. Replace resources that are unavailable due to:
o Forced and planned outages
o Dry hy&o conditions
o Wind and solar conditions
o Market conditions
PacifiCorp refers to "Generation Capacity" as the total quantity ofresources necessary to reliably
serve customers, after accounting for the items above. The level of resources needed for reliable
operation is discussed in Volume II, Appendix I (Planning Reserve Margin Study). For the 2019
IRP, PacifiCorp selected a planning reserve margin of l3 percent over its coincidental peak loads
and this is applied to both summer and winter peaks. The planning reserve margin does not
translate directly into eitler resources or need. Instead, PacifiCorp assesses the capacity
contribution of each of its resources in Volume II, Appendix N (Capacity Contribution Study).
Capacity contribution represents the portion ofa resource that can be counted on to reliably meet
peak demand. This is inherently dependent on the composition ofa portfolio, so for the first time
in the 2019 IRP, PacifiCorp performed a detailed assessment of the hourly reliability of each
portfolio and increased requirements for portfolios that failed to achieve a minimum reliability
level.
All resources contribute to a reliable portfolio, but they do so in ways that are not straightforward
to measure. Removing a resource from a portfolio will make that portfolio less reliable unless it is
replaced with something else, ideally in a quantity that provides an equal capacity contribution and
results in equivalent reliability. As indicated above, reliability is dilficult to predetermine, hence
PacifiCorp's reliance on a reliability assessment for the 2019 IRP.
As a result, the most direct measurement of the generation capacity value ofa resource is to build
a portfolio that includes it, and compare that portfolio to one without it. But even that analysis
would identifu more than just generation capacity value, as it would also include energy and
operating reserve impacts related to both the resource being added and resources that were delayed
or removed. This is an essential description ofthe steps used to develop portfolios in the IRP, and
while powerful, the IRP models and tools do not lend themselves to ease of use, rapid tumaround,
or the evaluation of small differences in portfolios.
As an altemative, a simplified approach to generation capacity value can be used when the
resources being evaluated are similar to the proxy resource additions identified in the IRP preferred
portfolio. The premise ofthe approach is that the IRP preferred portfolio resources represent the
least-cost, least-risk path to reliably meet system load. The appropriate level ofgeneration capacity
value is inherently embedded in the IRP preferred portfolio resource costs, because those resources
achieve the stated goal of reliable operation. Again, while it is difficult to identifu exactly what
portion of the resource cost should be considered generation capacity as opposed to energy or
operating reserve value, the total resource cost is straightforward and known.
585
APPFNDD( Q - ENERGY SToRAGE Po TENTIAL EVALUATIoNPA( lrrcoRP - 2019 IRP
PACrr-rCoRP - 20l9lRP AppENDrx Q - ENERGY SToRAGE PoTF,.ITIAL EVALUATToN
The 2019 IRP preferred portfolio includes stand-alone four-hour lithium-ion battery storage
resources starting in 2028. These resources have annual fixed costs (capital recovery and fixed
operations and maintenance) ofapproximately $ 173/kw-yr in 2028. After netting out energy values
based on market as described above, the remainder is $l I l/kw-yr (2028$) based on Four Comers
market prices and $ 130/kw-yr (2028$) based on Mid-Columbia market prices. In 201 8 dollars, this
is equivalent to $89-$104/kw-yr (2018$). These values do not include any value from operating
reserves or from charging during periods of renewable resource over-supply when the marginal
dispatch cost on PacifiCorp's system is less than market due to transmission congestion or limits
on market volumes.
While uncertainty remains in these generation capacity values, the uncertainty in the conclusrons
can be small to the extent a resource being evaluated provides largely the same services as the
resource in the 2019lRP. As a result, it is reasonable to compare the costs and benefits of energy
storage resources that provide energy value, operating reserves, and charging during renewable
resource over-supply to the costs and implicit benefits ofenergy storage resources in the 2019 IRP,
which also provide those same services. To the extent the resources being evaluated vary
significantly in characteristics or timing relative to the resources in the 2019 IRP prefened
portfolio, a more thorough analysis using a production cost model would be necessary to ensure
the relative benefits of preferred portfolio resources and a resource being evaluated are
characterized accurately.
This section discusses some of the key operating parameters associated with energy storage
resources. Beyond just defining the basic concepts, it is important to recognize the specific ways
in which these parameters are measured, and ensure that any comparison of different technologies
or proposals reports equivalent values. For example, many battery systems operate using direct
current (DC) rather than the alternating current (AC) of the vast majority of the electrical grid-
When charging or discharging from the grid, inverters must convert DC power to AC power, which
creates losses that reduce the effective output when measured at the grid, rather than at the battery.
To handle this distinction, PacifiCorp uses the AC measurement at the connection to the electrical
grid for alt parameters, as this aligns with the effective "generation input" ofan energy storage
resource. As previously discussed, an additional adjustment for line losses on the electrical grid
may also be necessary, but that is dependent on the location and conditions on the electrical grid,
rather than the energy storage resource.
Discharge capacity: The maximum output ofthe energy storage system to the grid, on an
AC-basis, measured in megawatts (MW). This is generally equivalent to nameplate
capacity.
Storage cap8city: The maximum output of the energy storage system to the grid, on an
AC-basis, when starting from fully charged, measured in megawatt-hours (MWh).
Hours of storage: The length of time that an energy storage system can operate at its
maximum discharge capacity, when starting from fully charged, measured in hours.
Generally, the hours of storage will be equal to storage capacity divided by discharge
capacity.
Chnrge capacity: The maximum input from the grid to the energy storage system, on an
AC-basis, measured in megawatts (MW).
586
Part2: Enerqy Storage Operating Parameters
PACrr rCoRP - 2019 IRP Appr.NDrx Q- ENIRGy sTorL\cE P()TlN'r'rAr. EvALrrATloN
Round-trip efficiency: The output ofthe energy storage system to the grid, divided by the
input from the grid necessary to achieve that level of output, stated as a percentage. A
storage resource with eighty percent efficiency will output eight MWh when charged with
ten MWh. Ifcharge and discharge capacity are the same, losses result in a longer charging
time. For instance, an energy storage system with four hours of storage, eighty percent
effrciency, and identical charge and discharge capacity would require five hours to fully
charge (4 hours of discharge divided by 80 percent discharge MWh per charge MWh).
State ofcharge: This is a measure ofhow full a storage system is, calculated based on the
maximum MWh of output at the current charge level, divided by the storage capacity when
fully charged, and is stated as a percentage. One hundred percent state ofcharge indicates
the storage system is full and can't store any additional energy, while zero percent state of
charge indicates the storage system is empty and can't discharge any energy. As previously
indicated, PacifiCorp's state ofcharge metric is based on output to the grid. As a result, the
entire round-trip efficiency loss is applied during charging before reporting the state of
charge. For example, a storage system with a ten MWh storage capacity and eighty percent
effrciency would only have an eighty percent state of charge after ten MWh of charging
had been completed, starting from empty.
Station service: Round-trip effrciency is a measure of the losses from charging and
discharging. Some energy storage systems also draw power for temperature control and
other needs. This is typically drawn from the grid, rather than the energy storage resource.
Some energy storage technologies experience degradation oftheir operating parameters over time
and based on use. The following parameters are used to quantit/ the effects of degradation.
Storage capacity degradation: The primary impact ofdegradation is on storage capacity.
Much of the degradation occurs as part of charge-discharge cycles, and can be measured
as the degradation per thousand cycles. After one thousand cycles, a four-hour storage
system might only be capable ofstoring 3.5 hours ofoutput. Some storage resources also
experience degradation that isn't tied to cycles, for instance based on differing state of
charge levels or time.
Cycle life: This is the total number of full charge and discharge cycles that energy storage
equipment is rated for. Three thousand cycles is corrmon for lithium-ion resources, but
operating under harsh conditions can also cause the effective cycle count to decline faster.
Once storage capacity has degraded by thirty percent degradation per cycle may accelerate.
Depth ofdischarge: Operating at a very high or very low state ofcharge, particularly for
an extended period of time, can cause more rapid degradation. This metric can be used to
identi$, how particular operations impact the elfective remaining cycle life.
Variable degradation cost: Lithium-ion energy storage equipment is composed ofa large
number ofbattery modules, each of which experience degradation. These modules can be
gradually replaced over time to maintain a more consistent storage capacity, or they can be
replaced all at once when cycle limits are reached, at the expense of a reduced storage
capacity in the interim. In either case, dre replacement cost of storage equipment can be
expressed per MWh ofdischarge, and accounted for as part of resource dispatch.
587
I'ACll-rCoRP -2019 IRP AppENDx Q - ENERcy SToRAGE PorErrrAr- EVALUATToN
This section described the potential benefits of different distributed resource siting and
configuration options. Due to economies of scale, distribuled resource solutions generally higher
cost relative to utility-scale assets. For example, the 2019 IRP supply-side table shows fixed costs
for a fifteen megawatt, four-hour lithium-ion battery costs that are approximately halfthat ofthe
costs for a one megawatt, four-hour battery. While these savings are appreciable, it should be noted
that a fifteen megawatt battery is small and can be considered modular relative to traditional
resources such as a simple cycle combustion rurbine. Many of PacifiCorp's distribution substations
have capacity in excess offifteen megawatts, such that a battery ofthat size could be feasible at
the distribution level, with the potential for incremental benefits relative to the transmission-
connected battery resources modeled as part of the 2019 IRP preferred portfolio. The most cost-
effective locations for distributed resource deployment are likely to reflect a balance of local
requirements and economies of scale.
Secondary Voltage
A distributed resource which is located dounstream from the high voltage transmission grid will
have a larger energy impact than its metered output would indicate, due to line losses. This is true
for both charging and discharging; however, the marginal loss rate increases with load, so the
effects are not equal. To the extent discharging is aligned with periods with higher load, and
charging is aligned with periods with lower load, the benefits will increase. For example, the
marginal primary voltage losses for Oregon are estimated at 9.5 percent on average across the year.
Savings based on primary losses would be appropriate to apply to a resource connected at the
secondary voltage level so long as it is not generating exports to the higher voltage system, as
losses would still occur within that level, but would be reduced due to lower deliveries across the
higher voltage system. When the hourly loss profile is applied to the hourly market prices used to
calculate the energy values described in Part l, the result is 16 percent higher for a four-hour
lithium-ion battery. Much of the incremental benefit is due to high loss rates in summer and winter
peak load months, when prices are relatively high. For lithium-ion batteries, there is also an
incremental benefit related to variable degradation costs. While the effect of losses makes the
battery appear larger from a system benefits perspective, it discharges the same amount, so the
variable cost component doesn't scale with losses, creating an additional benefit that is captured
in this energy margin.
In addition to incremental energy value, resources connected at primary or secondary voltage will
also have a proportionately higher generation capacity value. In the example for Oregon above,
this amounts to a roughly I I percent increase in effective capacity contribution based on avoided
primary losses.
T&D Capacity Deferral
As indicated in the grid services section, distributed resources can allow for the deferral of
upgrades by reducing the peak loading of the transmission and distribution system elements
serving their area. In order for deferral to be achieved, a distributed resource must reliably reduce
load under peak conditions. However, the timing of peak conditions for a given area is likely to
vary from the peak conditions for the system as a whole. As a result, the energy or generation
capacity value of energy-limited resources used for a T&D capacity deferral application are Iikely
588
Part 3: Distributed Resource Configuration and Applications
PAoFTCoRP - 2019 IR?AppENDrx Q- ENERcy STORAGE PoTENTTAL EVALUATToN
to be reduced. For instance, when energy-limited resources are reserved for local area requirements
they would not be available for system reliability events or a period ofhigh energy prices.
Combined Solar and Storage
Solar resources can qualifu for a thirty percent federal investment tax credit (lTC) if they come
online prior to the end of2023. Thereafter, solar resources will continue to qualifu for a ten percent
ITC. Storage that is constructed in combination with a solar resource and which is charged using
that solar resource for the first five years of operation qualifies for the same ITC as the solar
resource. This can result in l0-30 percent reduction in the costs of combined solar and storage,
relative to stand-alone storage. There are also construction and operational efliciencies that can
further improve the economics ofcombined storage and solar assets, including shared construction
crews. inverters. property, and maintenance.
As a result ofthe items benefits above, the 20l9IRP found that the inclusion of storage with solar
resources produced an across the board benefit relative to portfolios that included new solar
resources without storage. The 2019 IRP analysis assumed that storage resources combined with
solar would be sized equivalent to 25 percent of the solar nameplate and have four hours ofstorage.
These sizing parameters will evolve as PacifiCorp goes out to procure specific resources to capture
the benefits of the expiring ITC at the end of 2023, based on both the costs and effective
capabilities ofdifferent configurations. In general, energy storage should be sized to allow it to be
fully filled each day using coJocated solar output.
Cost-Effectiveness Results
Table Q.5 provides details on the year-by-year benefits ofvarious lithium-ion battery applications,
and identifies years and configurations that are estimated to be cost-effective, either on a stand-
alone basis or with the applicable solar ITC at that time.
Since a stand-alone battery is included in the preferred portfolio starting in 2028, it is assumed to
be cost effective and providing benefits equal to its costs starting in 2028. Prior to 2028, benefits
are based on the intra-hour flexible reserve credit values and operating reserve benefits through
2O23, as the battery penetration in this time frame is unlikely to fufly cover the operating reserve
requirements. Starting in 2024, benefits are assumed to be based on hourly market energy value
and the intra-hour flexible reserve credit values, as the higher value operating reserve values are
assumed to be fully satisfied with the 2o24 battery resources in the prefened portfolio.
-589
P^crrcoR.r, - 2019 IRP APPENDIX Q. ENERGY SIORAGE PoTENTIAL EVALUATION
.5-E Stora A tions - Annual Benefits Stream and Cost-Effectiveness
Valuation inputs I
Cost-effective w le/o trc
22.W
22.64
25.52
29.s3
34.02
&.54
6.47
5L.72
51.43
s2.15
57.36
&.79
69.40
74,71
79.63
84.30
u.73
88.33
94.67
103.07
105.42
107.83
110.29
112.80
t7L'tz
175.66
180.69
184.81
189.02
193.33
197.74
2OL25
206.86
21L57
275.N
22L33
226.38
23L54
236.82
26.19
26.74
27.39
24.02
28.66
29.31
29.98
30.66
31.36
32.08
32.81
33.56
34.32
35.10
3s.90
36.72
37.56
38.42
39.29
40.19
41.10
42.U
43.m
43.98
s1.17
52.U
53.53
v.75
56.00
57.28
58.s8
59.92
61.29
62.58
64. t :L
65.57
67.O7
68.60
70.16
71.76
13.40
75.07
76.78
78.53
80.32
82.16
84.03
85.9s
4,m
3.98
4,35
4.74
5.28
5.99
5.35
6.79
5.72
6.73
7.27
7.92
&30
8.'t8
9.20
9.57
9.49
9.68
10 36
11.15
11.41
71.67
11.Ct
!2.N
18.69
19.11
19.55
19.9,!)
20.4s
20.92
21.39
21.88
22.2A
22.a9
23.41
23.95
24.49
25,05
8,62
22.39
22.90
23.42
23.95
24.50
25.06
25.61
26.22
25.81
27.42
28.05
28.69
29.34
30.01
30.70
37.40
32.11
32.U
33.59
34.35
3s.14
35.94
36.76
3?.@
103.74
60.8ti
87.56
ar.9
75.4
&t.21
77.36
79.12
80.93
82.77
84.56
75.85
81.79
82.79
Stand-alone
ll.lon 4hr
S/kw-yr Fixed crst
Hourly
Market
EneGy
operating
Re5erye
Primary
Losses
Gen
capacity
Prlmary
[osses
Prima.y
T&D
Deferral
Primary
Losses
Ene rBy
T&D
oetenal
203
Table
81.:lS
83.10
8s.28
lntra-
hour
Flex
Credit
Uti lity-
scale
Resource
Cost-effective 096 ITC
590
AppsNprx R -Coel Sruotr,s
The 2019 Integated Resource Plan (IRP) includes a thorough and robust economic analysis of
PacifiCorp's coal units. The coal study analysis conducted in the 2019IRP was initially prompted
by the Public Utility Commission of Oregon (OPUC) in its 2017 IRP acknowledgement order,
which administratively established certain study parameters that defined the scope and breadth of
the analysis. PacifiCorp met these requirements and then developed a more complete study to
ensure that it adequately captured the costs to maintain system reliability. The coal study analyses
that informed the 2019 IRP portfolio-development process were completed in three phases:
a Phase One
Unit-by-unit early retirement sh.rdies, which focused on impacts to resource portfolio selections
and system costs from the System Optimizer (SO) model, were developed. Each unit-specific
early retirement scenario assumes closure at the end of2022. This phase met requirements set
forth by the OPUC 2017 IRP acknowledgement order (Order No. l8- 138), and concluded with
the June 28-29,2018 2019 IRP public-input meeting and compliance filing to the OPUC in
Docket No. LC-70 on June 29, 2018.
Phase Two
A series of studies were produced that expanded the scope of the phase one shrdies. The
expanded scope included an evaluation of unit-by-unity early retirement scenarios using the
Planning and Risk model (PaR), stacked retirement scenarios, where multiple early closures
were evaluated in a single scenario, and alternative year scenarios, which considered changes
in the timing ofassumed early closure dates for certain coal units. At this point in the process,
PacifiCorp had identified capacity shortfalls in the early retirement scenarios that would
compromise system reliability if not remedied. The second phase concluded with the
December 2018 coal analysis presented to stakeholders at the December 3-4, 2018 public-input
meeting, where PacifiCorp communicated to its stakeholders that additional analysis would
need to be developed to address the capacity shortfalls identified in the phase two results.
Phase Three
Additional analysis was performed on the stacked retirement scenarios evaluated in phase two
of the coal study analyses. The third phase concluded with the April 2019 coal analysis,
presented to stakeholders at the April 25, 2019 public-input meeting.
Each ofthe coal study phases show that early retirement ofcertain coal units has potential to reduce
overall system costs. In particular, the coal studies showed that the greatest customer benefits were
most likely to be realized with potential early retirement of coal units at the Naughton and Jim
Bridger coal plants located in Wyoming.
This appendix describes the methodology and approach taken in each of the three phases of the
coal studies and reports modeling and performance evaluation results. Aligning with expectations
communicated to stakeholders atpublic-input meetings held as the 2019 IRP was being developed,
the outcomes ofthe coal studies were used to inform the 2019 IRP portfolio-development process,
which is described in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach).
591
PACTFTCoR-P - 2019 IRP APPENDX R- CoAL SruDrEs
Introduction
PACTHCORP - 2019 IRI)APPENDTX R-CoAr. SruDrEs
In its 2017 IRP acknowledgement order (Order No. l8-138), the OPUC established requirements
for a unit-by-unit series ofcoal retirement studies, which were to be completed by June 30, 2018.
The requirements set forth in Order No. l8-138 are as follows:
PacifiCorp agtees to perform 25 SO model runs, one for each coal unit and a base case.
PacifiCorp agrees to summarize results and provide:
In agreeing to perform this analysis, PacifiCorp cautioned that
The snrdies would not provide a complete, portfolio-level view of the economics of
PacifiCorp's coal portfolio;
The structure of the analysis requested by OPUC staffwould not capture the system-cost
impact that would result from retiring more than one coal unit; and
Results from these studies would therefore provide limited insight into a least-cost, least-
risk resource portfolio.
o A table of the difference in present-value revenue requirement (PVRR) resulting fiom the
early retirement of each unitlo An itemized list ofcoal unit retirement cost assumptions used in each SO model run: ando A list of coal units that would free up transmission along the path from the proposed
Wyoming wind projects if retired.
These requirements are consistent with OPUC staff data request 65, which was submitted to
PacifiCorp during the 2017 IRP acknowledgement proceeding. In this data request, OPUC staff
provided additional guidance that established expectations for the scope ofthe unit-by-unit coal
study analysis described in OPUC Order No 18-138. The specific guidance provided in OPUC
staff data request 65 include:
PacifiCorp should assume Reference Case Regional Haze assumptions (from the 2017 IRP)
that are modified to exclude incremental selective catalltic reduction (SCR) costs for Jim
Bridger, Hunter, and Huntington in the benchmark case.
Recognizing PacifiCorp's concems outlined above, the Utah Public Service Commission in is
2017 IRP acknowledgment order in Docket No, l7-035-16 states "we find that additional analysis
will be helpful only if it supplements, rather than replaces, the type of coal plant modeling
PacifiCorp utilized for its 2017 IRP."
Unit-by-Unit Study Methodology
To meet the requirements set forth in OPUC Order No. l8- 138, PacifiCorp developed a portfolio
optimization for each coal unit using the SO model, and compared those model results to a
benchmark case that assumed continued operation of coal units through their depreciable life,
592
Phase One: Unit-bv-Unit Coal Studies
PacifiCorp should assume aDecember 2022 retirement date for each early retirement run.
PACTFICoRP - 2019 lItP APPENDTX R - CoAL STUDTES
which for certain units, extends beyond the life assumed in the 2017 IRP preferred portfolio.r
Consequently, in this context, the benchmark case developed for the coal studies is not intended
to represent PacifiCorp's default plan. Rather, the benchmark case developed for the coal studies
is only intended to serve as a point of comparison for the unit-by-unit retirement scenarios. Table
R.l summarizes the steps that were followed to produce the unit-by-unit analysis.
Table Rl - Summ of Uni -Unit Methodo S s
o High-level estimatcs of transmission reinforcement costs are applied as an adder b the results from step C.r Each SO model mn reflccts uniquc coal-unit operating cost assumptions consistcnt with assumed retirement dates
(,-e., fuel cost, run-rate operating costs, and decommissioning cosls).
o PacifiCorp did not pcrform SO model runs in step B lor Naughton tlnit I and Cholla Unit 4, which are already
assumed to retirc betore 2O22.
Unit-by-Unit Study Results
Table R.2 lists the coal units studied in the unit-by-unit analysis, including each unit's relative
ranking of potential customer benefits fiom a potential early closure based on the SO model
optimized portfolio results. Units with the lowest numeric rankings (starting with l) reported the
greatest potential for customer benefits from early retirement. Relative to the Reference Case liom
the 2Ol7 IRP, the SO model reported lower system costs with an assumed 2022 early retirement
date for eight of the 22 units studied (39 percent on a capacity basis). The units with the greatest
potential for customer benefits from early retirement on a unit-by-unit basis were Jim Bridger Unit
I , Jim Bridger Unit 2, Naughton Unit l, and Naughton Unit 2, followed by Hayden Unit l, Hayden
Unit 2, Hunter Unit l, and Craig Unit 2.
I For instance, the 20t7 IRP pret'ened portfolio assumed Jim tsridger Unit I would rctire at the end of2028 and Jim
Bridger tlnit 2 would rctire at thc end of2032. The coal study bcnchmark case assumes that these unilr cotrtinue to
opcrate through 2037.
593
A
2017-2036 System
PVRR (x1)
Base Case (OrE SO Model Rt[l)
. 2017 IRP tlpdate with lblbwing rndif,:atbrs
. Remvalof l6l MW Uhta Wird Projcct (2021-2036)
. 20 I 7 IRP ReErcrpe Case Regbnal }larE a-ssrrptbns
. March 20 I 8 oiicial forward prbc crrve wilh rrEdirn CO, price fuplds
. Resuhs are cabulated with and witlnu ircre[Ental sebcti\€ cataMt redu]ction
cosls for Jin Brilger I ad2
B
2017-2036 System
PVRR (x22)
RetierEr[ Cases (22 SO Model Rus)
. 20 I 7 IRP Update with bllowug nndiliatiors
. Rerrc lofl6l MW Uinta Wind Project (2021-2036)
. 201 7 IRP ReGrerce Casc Regbrnl Hare assrrr1rtbrc
. March 2018 official lbrward prte cttrve wilh rEdirm CO, plbe iryrrs
. No irrcrenrntal selective catalltt rcdEtbn costs
. Each nrl asy.rrns ttr retiE[Lnt ofa singb coal ufi at 0E erd of2022
c 2017-2035 System
PVRR(d)(x22)
Present-Vahre R()\.emr Requireu:nt Diflbrenrial (?\'RR(d)
. Change il system PVRR between lhe Base Case (A) and each of 22 RetiErcnt Cases (B)
Step Measule Des.riptlon
Table R.2 - Unit Unit Coal Stu Results Ranked Potential Customer Benefits
In the benchmark case, Jim Bridger Unit I and Jim Bridger Unit 2 include SCR costs. The
installation of SCR equipment would be required to maintain operation of this facility
through 2037.
Cholla Unit 4 and Naughton Unit 3 are not presented because PaciliCorp already assumes
that these units will cease operating as a coal fired facility before the end of2O22 and,the
intent ofthe unit-by-unit analysis was not to evaluate whether there might be economic
savings from operating these units longer.
The unit-by-unit studies completed in phase one of the coal studies have several limitations,
described in detail in both the June 29,2018 compliance filing in OPUC Docket No. LC-70 and
as communicated to stakeholders during the June 28-29,2018 public-input meeting. These
limitations include:
The potential benefits of early retirement for individual units are not additive and system
impacts are not linear. The studies did not attempt to capture the impact on system costs ifcoal
unit retirements are stacked (where more than one unit is assumed to retire early).
The studies did not capture the operational and other system-reliability impacts associated
with:o Meeting balancing area reserve requirements;. Meeting balancing area frequency response requirements;
l0 MT t7Colstnp 3 '74
l6Colstrip 4 74 l0 MT
fi2 t9 CO ltCraig I
Craic 2 l9 CO 9
Dave Johnston I 106 100 WY t2
Dave Johnston 2 r06 t00 WY l3
Dave Johnston 3 220 100 WY t4
Davc Johnston 4 330 100 WY I8
Hayden I 44 24 CO 7
Hayden 2 l3 CO 8
4llJ 94 UT l0Huntcr I
Huntcr 2 269 60 UT l5
Hunter 3 471 100 UT 20
Huntington I 459 100 UT 22
Huntington 2 450 I00 UT l9
Jim Bridgcr I 354 (t7 WY I
Jim Bridger 2 359 67 WY 2
Jim Bridger 3 349 WY 6
Jim Brideer 4 535367WY
Naughton I t56 100 WY 4
Naughton 2 201 100 WY 3
2lWyodak2(rt'l It0 WY
P^( rH(i)RP -20l9lRP APPTNDTX R- CoAL STTTDTES
Coal Unit PacifiCorp Share
Capacity (MW)
PacifiCorp
Percentage
Share {7")
State Ranking (High to Low
Potential Customer Benefits)
33
t/
594
Reduced flexibility between balancing areas (i.e., Jim Bridger provides energy and other
reliability services in both the east and west balancing areas); and
Reduced ability to participate in the energy-imbalance market due to a reduction in
flexible generation and inability to pass the flex ramp sufficiency test.
The studies reflect 2017 IRP system planning assumptions and do not capture system planning
assumptions that were being updated for the 2019 IRP (i.e., load forecasts, recent resource
additions, planning reserve margins, capacity-contribution values, conservation-potential
assessment, supply-side resources, elc.)
The studies were limited to SO model analysis and therefore do not analyze scenario-risk and
stochastic-risk analysis.
Considering these limiations, PacifiCorp engaged in phase two ofthe coal studies to advance and
improve upon results from phase one. The phase one results helped to prioritize the more detailed
analysis that would be prepared in phase two.
PacifiCorp presented the results of its stacked study coal analysis at its December 3-4,2018 public-
input meeting. As illustrated below, additional analysis was performed at this stage, including
updated unit-by-unit analysis, stacked retirement analysis, and additional analysis to evaluate
altemative retirement dates for certain coal units.
All studies in phase two were performed using the most current system planning assumptions
under development for the 2019 IRP (i.e., load forecasts, recent resource additions, planning
reserve margins, capacity-contribution values, conservation-potential assessment, supply-side
resources, etc.). Additionally, all studies in phase two reflect enhancements in the form of
additional resource options, transmission modeling enhancements, and PaR stochastic analysis.
These updates provided sigrificant improvements to the quality of the results used to indicate
which units to study further when developing stacked retirement scenarios.
Additional Resource Options
In updating modeling assumptions to align with the 2019 IRP, the updated and expanded coal
study analysis developed for this phase included roughly 250 more renewable resource options
that were available for selection in the SO model when it develops resource portfolios, inclusive
595
Ahernative
Retirement
Dates for Least
Economic Units
stacled coal
Unit
Retirements for
LEast Economic
Units
Updated Unit-
by-Unit
Anatysis
PACrrrCoR-P - 20l9IRP APPENDTX R -CoAL STUDTES
Phase Two: Stacked Coal Studies
PACTTTCoRI - 20l9lRP APPENDTX R -CoAL sruDrEs
ofcustomer-preference2 resources, more geographic locations, more resource types (i.e., solar and
wind resources combined with storage), and with updated capacity-contribution levels. This
enhancement aligns IRP modeling with the growing diversity of potential projects across
PacifiCorp's service area.
Transmission Modeling Enhancement
In the September 27-28,2019 public-input meeting, PacifiCorp discussed an improvement to
overcome transmission modeling limitations in the SO model while reasonably maintaining model
performance. Historically, the SO model has been unable to endogenously select among
transmission upgrade options when developing its optimized, least-cost mix of resources for a
given portfolio. Subsequently, transmission upgrade needs and costs had to be manually evaluated
and developed outside the SO model. This advancement of endogenous transmission modeling
represents a leap forward in the portfolio-optimization process, despite some resulting impacts on
run-time performance. Between June and December 2018, endogenous transmission options were
developed, tested and adopted in SO modeling along with validation and reporting features.
This enhancement had important implications for improving the quality of the coal study results.
The cost or benefit of a unit retirement at a specific time and location may swing significantly in
relation to transmission projects and opportunities to develop replacement resources and
brownfield locations following a plant retirement. Additional detail regarding the endogenous
transmission modeling approach implemented in the 2019 IRP is provided in Volume I, Chapter 6
(Resource Options).
Stochastic Risk Analysis
Once unique resource portfolios were developed by the SO model, additional modeling was
performed to produce metrics that support comparative cost and risk analysis among the different
resource portfolio alternatives. Stochastic risk modeling of resource portfolio alternatives is
performed using PaR. The stochastic simulation in PaR produces a dispatch solution that accounts
for chronological commitment and dispatch constraints. The PaR simulation incorporates
stochastic nsk in its production cost estimates by using the Monte Carlo sampling of stochastic
variables, which include: load, wholesale electricity and natural gas prices, hydro generation, and
thermal unit outages.3 The Monte Carlo sampling approach is discussed in more detail in Volume
I, Chapter 6 (Resource Options).
Updated tlnit-by-Unit Summary Results
Updated unit-by-unit studies were developed in phase two incorporating the enhancements
described above. The SO model was used to establish a portfolio for each unit retirement case and
the resulting portfolios were then run through the PaR model to assess stochastic performance for
the following price-policy scenarios (assumptions for the price-policy scenarios are summarized
in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach)):
596
2 Rcfer to Volume l, Chapter 7 (Modeling and Portfolio Evaluation Approach) for a description ofcustomer
prelbrence resources and modeling.
3 Front-otfice transactions, or FOTs, includcd in resource portfolios developed using thc SO model arc subielt to the
Monte Carlo random sampling ofwholcsale elcctricity prices in PaR.
PACTFTCORP - 20t9 IRP APPnTDH R - CoAL STrn IEs
. Base/Base: Medium gas price assumption with medium carbon dioxide (COz) price
assumptionr High/High: High gas price assumption combined with high COz price assumptionr Low,t{one: Low gas price conditions combined with no CO: price assumption
Table R.3 summarizes the unit-by-unit rankings from phase two, calculated on a nominal levelized
basis under the each of the different price-policy scenarios. A negative value represents the
potential for reduced costs when the unit is assumed to retire early. Conversely, a positive value
represents the potential for increased costs when a unit is assumed to retire early. As was the case
in phase one, the potential benefits of early retirement for individual units are not additive and
system impacts are not linear. The potential benefits of retiring more than one unit would not be
the same as adding up the potential benefits from the unit-by-unit results. Moreover, as discussed
previously, these results (and the results presented in Tables R.4 through Table R.7) do not account
for the costs to remedy capacity shortfalls in any given scenario. The cost to remedy capacity
sho(falls as necessary to maintain a reliable system were captured in phase three.
Table R,3 - Unit--Unit U te enefit ost of Retirement
llm Bridt.rl
,lnr BridF.,
Cr.:2
llmBridFr4
limSrldt.r3
Hunt€r2
cr:f r
@lstitp l
II
I
gggsHs
597
PaR Basc/Base
(Nom I-ev. $ikW-6a4
SO, Basc/Base
(Nom I-ev. $&W-]rcar)
Pa& HigMfuh
(Nom l.ev $&W-par)
Pa& lowNorx
(Nom t v. $.&w-ycar)
cr.k 2
,lm arids.rl
C'.g I
c.lrtrip4
JlmBridtErl
llm Bridaer4
,id add!.r2
888888
III!
I
I
ColstriD 4
Cokdp 3
lim EridSer 1
lim gridterS
,lm8dd8er4
lim g.ider2
cr.a 2
Gai I
AeAs88
c,aa t
c.a:1
,im SridGrl
tlm a.idte.2
,im BndB.rl
colrnip:l
I sa8 E t
Table R.4 through Table R,7 summarize the unit-by-unit rankings on a present value revenue
requirement basis, reporting SO model and PaR results as presented in the December 3-4, 2018
public input meeting.
C-01 (Benchmark)
C-02 (Colstrip 3)
C-03 (Colstrip 4)
C-04 (Craig I )
C-05 (Craig 2)
C-06 (Dave Johnston I )
C-07 (Dave Johnston 2)
C-08 (Dave Johnston 3)
C-09 (Dave Johnston 4)
C- l0 (Hayden I )
C-l I (Hayden 2)
C-I2 (Hunter I )
C-I3 (Hunter 2)
C-14 (Hunter 3)
C- 15 (Huntington l)
C- l6 (Huntington 2)
C-17 (Jim Bridger I )
C-18 (Jim Bridger 2)
C- l9 (Jim Bridger 3)
C-20 (Jim Bridger 4)
C-21 (Naughton l)
C-22 (Naughton 2)
C-23 (Wyodak)
$21,897
$21.906
$21,902
$21,897
$21,87s
$21,903
$21,90s
$21,895
$21,916
$21 ,885
$21,893
$21 ,816
$21,878
s2l,853
$21,808
$21,794
$21,690
$21.76 r
$21.800
$21,797
$21,794
$2t.801
$21,880
nla
S9
$s
($0)
($22)
$6
$8
(s2)
$19
($ l2)
($4)
(s8l)
($ 1e)
($44)
($8e)
(s 103)
($207)
(s 136)
(se7)
($ lo0)
($ l02)
(se6)
($ l7)
PACTFTCoRP -20l9lRP APPENDTx R - CoAL STI JDILS
Table R.4 - SO Model Medium Medium COz PVRR Unit
598
Study PVRR
($m)
PVRR(d) (Benefit/Cost of
2022 Retirement
PACIFToRP 2019IRP APPENDIX R - CoAL STUDIES
Table R.5 - PaR Medium Ga Nledium CO: PVRR Unit
$23,3r0
923,317
$23,302
$23,304
$23,281
$23,30s
$23,363
$23,273
$23,304
$23,252
$23,28',1
s23,34 t
$23,334
$23,438
$23,326
$23.310
$23,197
$23,381
$23,283
$23,349
$23,187
923,212
$23,323
nla
s7
($8)
(s6)
($2e)
(ss)
$53
($37)
($6)
($58)
($23)
$31
$24
$ r28
$17
s0
($ r r3)
$71
($27)
$39
($ 123)
($e8)
$13
C-01 (Benchmark)
C-02 (Colstrip 3)
C-03 (Colstrip 4)
C-04 (Craig l)
C-05 (Craig 2)
C-06 (Dave Johnston I )
C-07 (Dave Johnston 2)
C-08 (Dave Johnston 3)
C-09 (Dave Johnston 4)
C- 10 (Hayden l)
C-l I (Hayden 2)
C- l2 (Hunter l)
C-I3 (Hunter 2)
C-14 (Hunter 3)
C- 15 (Huntinglon l)
C- l6 (Huntington 2)
C-17 (Jim Bridger l)
C- 18 (Jim Bridger 2)
C-19 (Jim Bridger 3)
C-20 (Jim Bridger 4)
C-21 (Naughton l)
C-22 (Naughton 2)
C-23 (Wyodak)
PVRR
($m)
PVRR(d) (Benefit)/Cost of
2022 RetirementStudy
-s 99
C-01 (Benchmark)
C-02 (Colstrip 3)
C-03 (Colstrip 4)
C-04 (Craig l)
C-os (Craig 2)
C-06 (Dave Johnston I )
C-07 (Dave Johnston 2)
C-08 (Dave Johnston 3)
C-09 (Dave Johnston 4)
C- l0 (Hayden l)
C-l I (Hayden 2)
C- l2 (Hunter I )
C-13 (Hunter 2)
C-14 (Hunter 3)
C- 15 (Huntington l)
C- l6 (Huntington 2)
C-17 (Jim Bridger l)
C- l8 (Jim Bridger 2)
C-19 (Jim Bridger 3)
C-20 (Jim Bridger 4)
C-21 (Naughton l)
C-22 (Naughton 2)
C-23 (Wyodak)
$28,176
$28,152
$28,145
$28,265
$28,214
$28,225
$28,205
$28,275
$28,234
$28,167
$28,203
$28,258
$28,255
s28,297
$28,215
$28,t72
$28,107
$28,307
$2E,123
$28,156
$28,1l0
$28,134
$28,434
nla
($25)
(s3l )
$89
$37
s48
s28
$98
s58
($e)
926
$81
$79
$ 12l
$38
($4)
($6e)
$ l3l
($s3)
($20)
($66)
($42)
$2s8
APPFNT)rx I{ - Ci) r STrrDrr.s
Table R.6 - PaR Hi G H h CO: PVRR b Unit
600
P^crFlCoRP - 2019 IRP
Study PVRR
($m)
PVRR(d) @enefit/Cost of
2022 Retirement
C-01 (Benchmark)
C-02 (Colstrip 3)
C-03 (Colstrip 4)
C-04 (Craig l)
C-os (Craig 2)
C-06 (Dave Johnston I )
C-07 (Dave Johnston 2)
C-08 (Dave Johnston 3)
C-09 (Dave Johnston 4)
C- l0 (Hayden I )
C-l I (Hayden 2)
C- l2 (Hunter l)
C-13 (Hunter 2)
C-14 (Hunter 3)
C-15 (Huntington l)
C-16 (Huntington 2)
C-l7 (Jim Bridger l)
C-18 (Jim Bridger 2)
C-19 (Jim Bridger 3)
C-20 (Jim Bridger 4)
C-21 (Naughton l)
C-22 (Naughton 2)
C-23 (Wyodak)
$19,644
$ 19.701
$19,678
$19,579
$19,513
$ 19,601
$19,572
$19.554
$19,581
$19.553
$19,596
$ 19.675
$19,658
$ 19,796
$19,670
$ 19.696
$ 19,504
s 19,553
st9,642
$ 19,s78
$19,484
$ 19.488
$19,746
nJa
$s7
$35
($64)
($ l3l )
($42)
($71)
($8e)
($62)
($el)
($48)
$31
$14
$ 153
$26
s53
($l40)
($e0)
($2)
(s6s)
($ l60)
($ l s6)
$ 103
PACrrrCoR.P - 2019 IRP APPENDIx R_CoAI, STUDIES
Table R.7 - PaR Low Gas Zero COz PVRR b Unit
Alternate Year Unit Analysis
PacifiCorp selected units for further altemate-year analysis based on the unit-by-unit SO model
results. Based on the initial SO model results, the following units were selected to test the impacts
of delaying individual unit retirements:
Naughton Unit I
Naughton Unit 2
Jim Bridger Unit I
Hayden Unit I
Study PVRR
($m)
PVRR(d) (Benefit)/Cost of
2022 Retirement
Table R.8 reports the SO model outcomes ofthe altemate year studies, and indicates that delaying
the ret ement of individual units, before accounting for incremental reliability resources needed
to remedy capacity shortfalls, in the unit-by-unit studies would reduce potential benefits.
60r
PACU.TCoRP - 2019 IRP APPENDTX R - CoAL ST DTES
Table R.8 - SO Model Alternate Year Anal Medium G Medium CO:
To confirm this finding, PacifiCorp conducted additional analysis ofthese studies using PaR. Table
R.9 reports results consistent with the SO Model results-before accounting for incremental
reliability resources needed to remedy capacity shortfalls, potential benefits for early retirement
are greatest with assumed retirement at the end of 2022. Based on results of the alternate-year
cases, the stacked-retirement cases developed in phase two of the coal studies assume early
retirement of units at the end of2022.
Table R.9 - PaR Alternate Year Anal Medium Gas Medium COz
Stacked Study Methodology
Based on the outcomes ofthe updated unit-by-unit analysis, eight stacked-retirement cases were
defined to analyze retirement depth for nine coal resources with the highest potential for customer
benefits. Table R.l0 identifies these cases by name, retired units and the total nameplate of the
included retirements.
C-01 (Benchmark)
C-25 (Naughton l)
C-26 (Naughton l)
C-27 (Naughton 2)
C-28 (Naughton 2)
C-29 (Jim Bridger l)
C-30 (Jim Bridger l)
C-31 (Jim Bridger l)
C-32 (Hayden l)
C-33 (Hayden l)
nla
2025
2028
2025
2028
202s
202&
203 t
2025
2028
$21,897
$21,8{t7
s2l,915
s2l,8n2
s2l,915
s2 r,756
s2l,773
$21.788
$21,884
$21,888
n/a
(slo)
sl8
(s l5)
$18
(sr4l)
($124)
(s I oe)
($13)
($01
nla
$e2
sl20
s8l
$l l4
s66
$83
$99
($ l)
S3
C-01 (Benchmark)
C-25 (Naughton l)
C-26 (Naughton l)
C-27 (Naughton 2)
C-28 (Naughton 2)
C-29 (Jim Bridger l)
C-30 (Jim Bridger I )
C-3 I (Jim Bridger I )
C-32 (Hayden l)
C-33 (Hayden I )
nla
2025
2028
2025
2028
2025
2028
2031
202s
2028
$23,310
c)1 )?5
$23.290
523.277
s23,298
s23,27{t
s23,262
s23,238
$23,27r
()1)77
($12)
($40)
(M8)
($72)
($3e)
($33)
nla
(s3s)
($20)
(s33)
a
s87
s 103
$65
$86
$73
$64
$40
$20
$25
602
Study Alternate
Year
PVRR
(sm)
PVRR(d)
(Benefit/Cost of
2022 Retirement
Chenge from
2022 Retirement
Assumption
Studv Alternate
Year
PVRR
($m)
PvRR(d)
@enefit/Cost of
2022 Retirement
Change from
2022 Retirement
Assumption
P^cFrCoRP - 2019 IRP APPENDTX R-CoAL STUDTES
Each stacked case required the development of a unique set ofassumptions, accounting for fuel
costs, decommissioning costs, contractual obligations, and the potential loss of existing cost-
savings for co-located facilities.
The SO model was used to establish a portfolio for each stacked-retirement case and the resulting
portfolios were then run through PaR to assess stochastic performance for the following price-
policy scenarios (assumptions for the price-policy scenarios are summarized in Volume I, Chapter
7 (Modeling and Portfolio Evaluation Approach)):
o Base,Ease: Medium gas price assumption with medium COz price assumption. HighiHigh: High gas price assumption combined with high CO: price assumptiono LowlZero'. Low gas price conditions combined with no CO: price assumption
Table R.l0 - Stacked Retirement Cases
c-34 Natrghton l-2 (2022)357
c-3s Naughton l-2 (2022)
JimBriJger I (2022)7tl
Naughton | (2022)
Jim Brllger I (2022)5r0
c-37
Naughton | (2022\
Jim Brilger | (2022)
Haydenl (2022)
s54
c-38
Nanghton l-2 (2022)
Haydenl (2022)
JimBrilger | (2022)
755
c-39
Nanghton l-2 (2022)
Haydenl (2022)
Jim Brilger | (2022)
Cmbz (2022)
834
Naqlton l-2 (2022)
Haydenl (2O2?)
JimBrilger l-2 (2022)
Crate2 (2022')
c-40 1,193
c-41
Naughton l-2 (2022)
Jim Brltger l-2 (2022)
Hayden l-2 (2022\
Craryr-2Q022)
Dale Jotmston 3 (2022)
1,529
603
Case Nanre 2022 Retirerne nts Narrplate Retircd (MW)
c-36
P^0FrCORP - 2019 IRP APPFIDL\ R-CoAL STUDTES
Stacked Study Rcsults
Table R.l I summarizes the stacked study results under the Base/Base price-policy scenario. Cases
C-35, C-38, and C-39 show the largest potential benefits, and the PVRR(d) results for these tkee
cases are very close to one another. Cases C-40 and C-41, both in excess ol1,000 megawatts (N{W)
of incremental early retirements relative to the benchmark case, show a net cost. As discussed
previously, these results (and the results presented in Table R.l2 and Table R.l3) do not account
for the costs to remedy capacity shortfalls.
Table R.ll - Plannin and Risk Medium G Medium CO: PVRR b Stu
Table R.l2 summarizes the stacked study results under the Higl/High price-policy scenario. As in
the base/base price-policy scenario, Cases C-35, C-38, and C-39 show the largest potential
benefits. Cases C-40 and C-41, both in excess of 1,000 MW of incremental early retirements
relative to the benchmark case, continue to show a net cost.
Table R.l2 - Plann and Risk Hi h COz PVRR Stu
Table R.13 summarizes the stacked study results under the lodzero price-policy scenario. As in
the base/base and high/high price-policy scenarios, Cases C-35, C-38, and C-39 show the largest
potential benefits, and the PVRR(d) results for these three cases are reasonably close. Cases C-40
and C4l, both in excess of 1,000 MW of incremental early retirements relative to the benchmark
case, continue to show a net cost.
C-01 (Benchnurk)
c-34
c-35
c-36
c-37
c-38
c-39
c40
c-41
$23,3 r0
$23.1 80
s23,009
$23,286
s23,288
$23,002
$22,993
$23,4n3
$23,600
nJa
(S 130)
($3ol)
($z+1
($22)
($107)
(s317)
$ 173
$290
C-01 (Borchmark)
c-34
c-35
C-3(r
c-37
c-38
c-39
c-40
c4l
$28,176
$28,109
$27,897
$28.252
828,249
$27,1t96
$27,877
s28,397
$28,249
nJa
(s67)
($27e)
$76
s72
($280)
($2ee)
s22l
$368
604
Base/Base Case PlRR PvRR(d)
(Benefitycost of Retirement (Sm)
HighiHigh Case PVRR ($m)PVRR(d)
(Benefrt)/Cost of Retirement ($m)
C-01 (Benchmark)
c-34
c-35
c-36
c-37
c-38
c-39
c-40
c4l
$19,6,9
$ l9,4tt7
$19,386
$r9,54e
$t 9.573
$ r9,359
$19,336
$19,747
s19,828
r,la
(s 156)
($257)
(se5)
($71)
($285)
($308)
$ 103
$184
Table R.l3 - P and Risk Low No COz PVRR s
Initial Reliability Assessment
While the December 2018 stacked coal studies incorporated important enhancements in
methodology and the alignment ofdata to the 2019 IRP planning assumptions, a method had not
yet been fully developed to capture the operational and other system-reliability impacts associated
with potential early coal unit retirements.
PacifiCorp performed an initial reliability assessment on a sampling ofthree cases using an hourly
deterministic PaR run for 2023, which is the first full year after assumed coal unit retirements, The
deterministic run provides the granularity necessary to represent system reliability shortfalls that
may be lost in aggregated data, a factor of increasing importance as flexible resources are retired
and potentially replaced with non-dispatchable variable resources. Because deterministic studies
lack stochastic shocks, thermal units are modeled using de-rated capacity to account for unplanned
outages.
For these initial reliability studies, system balances were summarized for load, net load (load net
of energy efficiency, private generation. wind, and solar), spinning reserves. non-spinning
reserves, and regulation reserves and compared to the type and amounts of resources providing
system services across each hour ofseveral selected days. Selected days included peak load days
and peak net-load ramp days. Shortfalls were measured for spinning, non-spinning, and regulating
reserves, as well as [oad. Table R. l4 summarizes the aggegated findings of the initial reliability
assessment.
605
PACIFTCoRP - 20t9 IR?APPENDTX R-COAL SruDrEs
Capacity shortfalls were observed in 2023, the year after early retirements, in each ofthe sample
cases, and the number ofoccurrences and the magnitude ofthe worst occurrence increased in cases
with more stacked retirements. The results confirmed that the retirement cases could degrade
system reliability, and the potential cost to remedy these capacity shortfalls was not directly
factored into the phase two results (i.e., via a potential addition or change in the resource mix to
alleviate capacity shortfalls). Addressing these capacity shortfalls observed in the phase two results
was the primary objective ofphase three of the coal studies.
Lo Zero Case P!'RR
(sm)
PVRR(d)
(Benefit)/Cost of Retirement ($m)
C-01 (Benchmark)
c-3s
c-40
29 (0.3o/o)
146 (t.7%\
609 (1.oya
290
3l tt
351
Table R.14 - Reliabili A C Shortfalls
From December 2018 through April 2019, PacifiCorp continued in its efforts to address the
capacity shortfalls observed in preliminary results as pan of this stage of the coal studies. Four
public-input meetings were held including the April 25,2019 meeting, which concluded the coal
studies. During these months several shortfall mitigation enhancements were made to improve
model representation, and a path forward was identified to address reliability concems.
Stakeholder Feedback
As an outcome of the phase two stacked-retirement results, two additional cases were developed
in response to stakeholder interest, cases C-42 and, C-43. Case C-42 examined the impacts of
retiring the four coal units most consistently reporting high customer benefits over the course of
the coal studies. C43 examined the impacts of replacing a Jim Bridger unit with a Dave Johnston
unit. Table R. l5 provides the assumed retirements of the two additional cases plus the total retired
nameplate capacity assumed for each case.
Table R.l5 - Additional Stacked Coal Studies
Coal Unit Focus
At the March 21, Z0l9 public-input meeting, PacifiCorp presented analysis of real levelized cost
rankings ofthe coal units as an additional verification of the coal units which were to be the focus
ofthe stacked-retirement cases. While this analysis is independent ofdirect locational factors tied
to the IRP topology, the findings reported in Table R.16 generally confirms the focus of specific
units established by the phase two coal studies completed in December,20l8.
c-42 Naughton 1-2 (2022)
Jim Bridger 1-2(2022)
c-43
Naughton l-2(2022)
Jim Bridger 1 (2022)
Dave Johnston 3 (2022)
928
APPFNDTX R -CoAL STUDTESPA( rFrCoRP - 2019 IRP
Case Shortfall Hours Marimum Shortfall (MW)
Phase Three: Reliabilitv Analvsis of Coal Studies
Case Name 2022 Retirements Nameplate Retired
(M\9
1,063
606
Table R.l6 - Real Levelized Cost Rankings ofCoal Units
The top candidate list in both views include Naughton, Jim Bridger, Hayden and Craig units.
While the Dave Johnston units were not indicated in this new analysis, Dave Johnston Unit 3
was retained in certain cases for completeness and in response to stakeholder interest.
Shortfall Mitigation
Renewable Regulation Reserves
Wind and solar resources with requisite contractual rights and controls can provide regulation
reserves when forecasted output can be curtailed to free-up operating capacity on the system.
Curtailment results in:
. Replacement energy cost (t)?ically market)o Lost renewable energy credit revenue, where applicable (only included where explicitly
known). Lost production tax credits, where applicable
607
o&M
Rank
CaPEI
Rank
Fult Load
Fuel
nal*
t4
t2
9
10
11
10
9
L2
L4
15
Ilec +4
PvRn(d)
Rank
PA('rFICL,ru, - 20l9 IRP A-PPINrrrx R- CoAr. STLJDIES
C-02 (Colstrip 3)
C-03 (Colstrip 4)
C-04 (Craig 1)
c-os (craig 2)
c-06 (Dave Johnston 1)
C-07 (Dave lohnston 2)
C-08 (Dave Johnston 3)
C-09 (Dave Johnston 4)
C-10 (Hayden 1)
C-11 (Hayden 2)
C-12 (Hunter 1)
C-13 (Hunter 2)
C-14 (Hunter 3l
C-15 (Huntington 1)
C-16 (HuntinSton 2l
C-17 (Jim Bridger U
c-18 (Jim Bridger 2l
C-19 (Jim Bridger 3)
C-m (Jim Bridger4)
C-21 (Naughton U
C-22 (Naughton 2)
c-23 (wtodak)
ABgregate
Rank
1
2
18
16
7
9
10
l'
4
3
L7
11
15
13
13
n
11
3
72
RPal Levelized cost Rankings
15
10
11
7
13
2t
6
11
4
9
19
18
an
t7
l4
2
5
8
20
1
3
l6
Avoided taxes (Wyoming wind only)
To mitigate the impacts of curtailments, wind and solar resources with requisite contractual rights
and controls were modeled as dispatchable resources in PaR.
Hydro Dispatch Configuration
To better account for the flexibility of dispatchable hydro resources, these resources were
configured for spring months (February through May in this context) to maximize reserve
capability by establishing a consistent monthly dispatch rather than shaping to load.
Non-Peak Front Oflice Transaction Modeling
Modeling enhancements that address the modeling of dispatchable wind, solar, and hydro
resources can result in less energy to serve load, so their viability in mitigating operating-resewe
shonfalls may be restricted by limits on market purchases. Recognizing that market conditions
vary by season, Iiont office transaction (FOT) limits, which were established with a focus on
summer and winter peakJoad periods, are increased during the spring and fall to align with firm
transmission rights. The increase is fiom I,425 MW to 2,277 MW in these periods.
Lewis River Hydro Project Refinement
The original and standard model configuration led PaR to use the Lewis River Hydro project to
shave peak load using available energy over a sample week for a given month. Any remaining
capacity was then available for use as operating reserves.
PacifiCorp tested and implemented a modeling enhancement allowing PaR to shave peak load,
using available energy of a sample week for a given month, net of wind, solar, battery storage,
energy efficiency, and private generation resources (i.e., net load). Any remaining capacity, but no
less than l0 percent ofthe Lewis River Hydro project, is considered available for use as operating
reserves-
Baftery Storage Optimization
PacifiCorp initially attempted to mimic the model settings used to enhance PaR's use of the Lewis
River Hydro project to improve its use of battery-storage resources (dispatch, charging, and reserve
resources). However, unlike the Lewis River Hydro project, battery-storage resources do not have
an established volume of energy to use over a sample week in a given month.
Given complexity of PacifiCorp's system, the PaR model experienced difficulty optimizing the
dispatch for battery storage resources. To improve upon this shortcoming in the PaR model,
PacifiCorp developed and tested a method to produce an optimized peak-shave/valley-fill profile
for these resource outside ofPaR that is based on load net of wind, solar, energy efliciency, and
private generation resources in any given portfolio. Fixed hourly dispatch, charging, and operating
reserves are entered as inputs to the PaR model. This was presented and discussed in the March
2l ,2019 public-input meeting.
Model Granularity Cost-Driver Adjustment
At the January 24.2019 public-input meeting, PacifiCorp discussed that differences between
portfolios in some cases were contributing to differences in reserve deficiencies (primarily 2038).
These portfolio differences were causing disproportionate impacts on present-value portfolio costs
in PaR relative to the SO model. Subsequent testing confirmed that differences in the granulanty
608
P^crrrCoRP - 2019 IRP ApptNutxR-ConLSnrurs
PA('rFrCoR-P - 2019 IRP APPFNDIX R - CoAr. Sr uDrES
between the two models contributes to alternative resource selections and that these resource
selections are influencing these seemingly incongment results.
When cost-driver adjustments based on the diflerences in hourly granularity between the SO model
and PaR model are applied to resource cost inputs used in the SO model, differences to resource
portfolio results for seemingly similar cases are more stable and the cost disparity driven by reserve
deficiencies are mitigated. Accounting for the reduced hourly granularity in the SO model yields
the average solar and wind resource costs shown in Table R.17.
Table R.17 - Model Granulari Cost-Driver ustment Summa
Reliability Study Methodology
The modeling enhancements previously described give the SO model and PaR improved insight
into the value and capabilities of various resowces, and are applicable to every case. This allows
the SO model to provide portfolios that are better-aligned with how PaR evaluates the performance
and reliability of resources in its more granular perspective. In addition, due to the unique
combination of resource types, locations and timing, and their interactions with transmission
option modeling, a methodology was necessary to identi$ and address remaining reliability
shortfalls on a case-by-case basis. This method was developed, tested and implemented, and
subsequently presented to stakeholders at PacifiCorp's April 25, 20l9IRP public-input meeting.
Figure R.l outlines the development steps followed in this process.
re R,l -Studies Methodolo Process
Oregon ($7 oo $0.95
Washington ($7.17)s1.05
Idaho ($7.28)(so.l4)
Utah ($7.73)($0.3s)
Wyoming ($7.33)(s0.eo)
Final Pass: Reliabllity Portiolio Optimlzalion (6 requlred)
lnltlal Pass: Portfolio / Reliabllity Assessrnent
609
Average Resource Cost (increase/decrease
($/MWb of expected output)Resource Location
Solar Wind
(so)
Pntfolio Prep...tion for Planning and Risk
{sol
Rcpaocess So PlanRdi.bility Po.tfolio lnputs
P^crHCoRP - 20l9lRP APPENDTX R- CoAL SnJDIES
The reliability methodology is an expansion ofthe initial reliability analysis explored at the end of
2018 and previously described in Stage Two of the coal studies and is described in more detail
below.
Deterministic Reliability Assessment
In the initial reliability analysis, a single deterministic run for the year 2O23 was used to assess
reliability shortfalls. The methodology adopted in this reliability stage includes a deterministic
reliability assessment for tkee years,2123,2030, and 2038. Years 2030 was added as an outcome
of a 20-year analysis which determined that 2030 was most frequently the year with highest
measured shortfall. Likewise 2038 was added as a bookend, and also because the final year was
observed to have relatively high shortfalls.
In evaluating the reliability of the deterministic studies, portfolios must meet four hourly
requirements: energy, non-spinning reserve. spinning reserve, and regulation reserve. Separate
requirements for East and West are developed in the methodology, but transfers are allowed up to
transmission limits. Using the method described in the Initial Reliability Analysis above, the
hourly balance ofnet load and all resource contributions were compared to calculate the shortfall
or unused available capacity for each hour. The maximum hourly shortfall (or minimum available)
is identified by season. The resulting measures describe four reliability requirements for each
proxy year: surnmer east, summer west, winter east and winter west.
Reliability requirements for the test year 2023 were applied to simulation years 2023 through 2027.
Requirements for the test year 2030 were applied to simulation years 2028 through 2036.
Requirements for the test year 2038 were applied to simulation years 2037 and 2038.
Uncertainty Requirement
Deterministic studies have the advantage ofincreased detail through hourly granularity appropriate
to identifoing potential shortfalls in an increasingly complex system. In the absence ofstochastic
variance, these studies also reflect "perfect foresight" for the following assumptions:
Normal load (l -in-2 exceedance)
Average thermal outages in all hours
Average hydro conditions
Fixed variable energy resource generation profiles, and
Average market prices without electric or natual gas price volatility and physical supply risks
Additional flexible capacity is required beyond the capacity needed to "cure" hourly shortfalls to
reliably serve customers considering that the above factors vary from day to day and hour to hour
and are not known in advance. To account for these intrinsic uncertainties, 500 MW ofadditional
reliability requirement was added to address significant day-ahead, hour-ahead and real-time
unknowns in market supply. This 500 MW capacity requirement is in addition to capacity to
sufficient to cover the maximum hourly shortfall identified in the deterministic studies.
The 500 MW incremental requirement relative to a deterministic forecast ofloads, outages, market
prices, and hydro generation was established upon review of operational data and with
consideration of operational experience. In operations, capacity held in reserve for contingency,
forecast error and intra-hour variability is approximately l6 percent ofpeak load. In the summer
months, additional capacity is held in reserve to mitigate risk associated with high volatility in
610
P^crlrCoRP - 20l9IRP APPENDTX R-CoAr. STUDrfs
load and resource availability. In 2018, capacity held in reserve that is incremental to the l3 percent
planning margin for contingency, forecast error, and intra-hour volatility totaled 295 MW. In 2018,
capacity held in reserve to mitigate risk during peak load conditions in the summer months was
approximately 241 MW. Combined, these sum to 536 MW. PacifiCorp conservatively adopted the
500 MW figure for planning purposes in the 2019 IRP.
Retiability Portfolio
Once the reliability requirements are known, the SO model is run with the ability to add or
accelerate the following resource types relative to the pre-reliability portfolio to meet seasonal east
and west incremental requirements: batteries, energy efficiency, gas peaking resources, and
pumped storage resources. Other resource types are locked-in at levels determined by the pre-
reliability portfolio. The four types of reliability resources are allowed as additions because they
provide the necessary flexibility to effectively meet identified shortfalls.
Stochastic Outcomes
The last step in the process is to run a 20-year, SO-iteration PaR study on the resulting reliability
portfolio, providing stochastic risk analysis over the full IRP snrdy period.
Table R18 - Ear Retirement Assum tions Summa for all Reliabili Coal Studies
Note: in all cases it is assumed that Naughton 3 (280 MW) is retted in 2019 and that Cholla 4 (387 MW) is relired at the efld of
2020; lhese units arc retircd iD lhe bflchmark casc and therel'ore not ircremental to the stacked-retircmcnt cases listcd above.
ln the final coal study analysis, case C-42 produced the lowest present value revenue requirement
(PVRR) total system cost, and therefore the highest potential customer benefits associated with
potential early retirement. Cases retiring greater amounts of coal resource (C-40, C-41), or those
emphasizing different coal units for early retirement (C-43) reported reduced benefits. This
outcome is broadly supported by findings from phase one and two, and again by the real levelized
cost rankings ofcoal unit run-rate costs across the fleet, as reported previously in Table R-16.
6il
Case (Sm1
NauBhton
I
N.0ghton
2 grid*er I Btidset 2 Hayden 2
Capacity in
208 {rvrw}Crait 1 CtaiE2 Johnston 3
c34 351 523,536
c,35 7t1,
c36 S23,118510
c37 554
c38
c-39 S23,4x814
c-rto 1,193
1,529
1,063
924 s23,458
Reliability Study Results
Table R.l8 summarizes the assumed retirements for the complete set of stacked coal reliability
cases, including retired capacity and PaR model measured (benefit)/cost.
523,381
s23,{O5
7SS s23,398
523.3r7
c41 s23,390
c-42 523,3o2
c-43
' l EI
m
-t-
I ----r--tII
l--f
PACtrTCoRP - 2019 IRP APPENDTX R-CoAr. SruDrEs
Stacked Coal Case C-42
At the April 25,2019 public-input meeting, PaciflrCorp reported a PVRR differential benefit of
$248m against the C-01 benchmark case. As noted in the Unit-by-Unit Methodology discussion,
above, the benchmark was an administratively established in phase one of the coal studies, and is
not representative of PacifiCorp's plan. Also, the $248m figure did not include a correction to the
granularity adjustment driver included in the reliability coal studies. Corrected, the PVRR values
(given in Table R.18, above) did not alter the conclusions of the April 2019 analysis, which
continue to confirm that the greatest potential benefit for early retirements resides with the
potential early closure ofunits at the Naughton and Jim Bridger plans in Wyoming.
Aligned with the April 25,2019 results, Figure R.2 reports the average annual cost ofreplacement
resources and levelized costs relative to the assumed 2022 accelerated retirements of Jim Bridger
Units I and 2, and Naughton Units I and 2.
Figure R.2 - C{2 Average Annual Replacement Resource Capacity and Levelized Costs
Average Annual Capacity of Replacement Resources
and Levelized Costs Relative to Retired Coal
400
200
0
= (2oo)
(6oo)
(800)
(1,000)
Nominal Levelized cost (S/MWh)
$s4
I Coal Removed
I Solar+Bat
I Gas CCCT
I Wind
I Battery
r Class 2 DSM
r Solar r Wind+Bat
a Pumped Storage I Gas Peaker
i Class l DSM r FOT
612
o The nominal levelized cost of retired coal resources is $14.21llvlWh higher than the
nominal levelized costs ofthe portfolio ofreplacement resources.o COz emission cost savings account for 77.0 percent of the overall benefit associated with
accelerated retirement.. Run-rate fixed costs would need to drop by 26.3 percent to achieve break-even economics
with the replacement portfolio.
PACIT.TCoRP - 2019 IRP APPENDTX R - CoAL STUDTES
The updated coal-retirement cases account for incremental resource costs to address reliability
issues identified and discussed at the December 3-4,2Ol8 public-input meeting. The updated
analysis shows there are potential customer benefits from accelerating the retirement of certain
coal units, where the greatest customer benefits are associated with the potential accelerated
retirement of units at the Naughton and Jim Bridger plants located in Wyoming.
Aligning with the long+erm study plan established during the 2019 IRP public-input process, the
identification ofthese key units informed PacifiCorp's 20l9IRP portfolio-development process,
described in detail in Volume I, Chapter 7 (Modeling and Portfolio Evaluation Approach). The
portfolio-development process considers other planning factors not fully evaluated in the coal
studies (i.e., Regional Haze compliance, altemative retirement dates forjointly owned coal plants
where PacifiCorp is a minority owner and not an operator, altemative timing of potential
retiremen6 when accounting for incremental capacity to maintain reliability). Consistent with the
findings from the coal study, more than half of the cases developed in the initial phase of the
portfolio-development process evaluated varying combinations of retirement dates for Naughton
and Jim Bridger units, including coal retirement assumptions from case C-42-
6t3
Conclusions
PAcrrcoRP - 2019 IRP APPINDTx R-CoAL Sl'uDrEs
614