Mode rnizing Minne sota ’s Grid An E c o no mic Ana lysis o f E ne rg y Sto ra g e Oppo rtunitie s MI SO-wide E le c tric ity Co -Optimize d Planning Sc e nario s Pre pa re d By: Vibr ant Cle an E ne r gy, L L C Dr Christo phe r T M Clac k Pre pa re d F o r: Minne sota Public Utility Commission July 11 th , 2017 Disc la ime r: T his pre se nta tio n ha s b e e n pre pa re d in g o o d fa ith o n the b a sis o f info rma tio n a va ila b le a t the d a te o f pub lic a tio n. T he a na lysis wa s pro d uc e d b y Vib ra nt Cle a n Po we r, L L C. No g ua ra nte e o r wa rra nty o f the a na lysis is a pplic a ble . Vib ra nt Cle a n E ne rg y, L L C will no t b e he ld lia b le fo r a ny lo ss, d a ma g e , o r c o st inc urre d b y using o r re lying o n the info rma tio n in this pre se nta tio n.
Ove rvie w I . Ba c kg ro und a nd the WI S:do m o ptimiza tio n mo de l I I . Ma in mo de ling re sults a nd a na lysis I I I . Co nc lusio ns I V. Mo de ling inputs a nd a ssumptio ns
Ove rvie w I. Bac kgr ound and the WIS:dom optimization mode l I I . Ma in mo de ling re sults a nd a na lysis I I I . Co nc lusio ns I V. Mo de ling inputs a nd a ssumptio ns
MISO high pe ne tr ation r e ne wable e ne r gy study for 2050 • I n 2016, Vib ra nt Cle a n E ne rg y, L L C (VCE ) pro duc e d a hig h re ne wa b le s study fo r the Midc o ntine nt I nde pe nde nt Syste m Ope ra to r (MI SO). • T he study fo und tha t MI SO c o uld re duc e e missio ns b y 80% c o mpa re d with 2005 le ve ls a t re a so na b le c o st b y e xpa nding g e ne ra tio n fro m wind a nd so la r PV a lo ng with c o mple me nta ry na tura l g a s a nd tra nsmissio n. • T he pre se nt syste m le ve l a na lysis is a n e xpa nde d ve rsio n o f the pre vio us MI SO study c a rrie d o ut b y VCE .
MISO high pe ne tr ation r e ne wable e ne r gy study for 2050
MISO high pe ne tr ation r e ne wable e ne r gy study for 2050 I nc luding re pla c e me nt o f c a pa c ity c o sts
MISO high pe ne tr ation r e ne wable e ne r gy study for 2050
T he WIS:dom Optimization Mode l WI S:do m is the o nly mo de l to c o mb ine : • i. Co ntine nta l-sc a le (g lo b a lly c a pa b le ), spa tia lly-de te rmine d tra nsmissio n a nd g e ne ra tio n e xpa nsio n (3-km, ho urly); ii. T ra nsmissio n po we r flo w, pla nning re se rve s, a nd o pe ra ting re se rve s; iii. We a the r fo re c a sting a nd physic s o f we a the r e ng ine s; iv. De ta ile d hydro mo de ling ; v. Hig h g ra nula rity fo r we a the r-d e pe nd e nt g e ne ra tio n; vi. L a rg e spa tia l a nd te mpo ra l ho rizo ns; vii. De ta ile d inve stme nt pe rio ds (1-ye a r, 2-ye a r, o r 5-ye a r) o ut pa st 2050.
T he WIS:dom Optimization Mode l
T he WIS:dom Optimization Mode l
T he WIS:dom Optimization Mode l
T he WIS:dom Optimization Mode l - MISO
T he WIS:dom Optimization Mode l - MISO
T he WIS:dom Optimization Mode l - MISO
Ove rvie w I . Ba c kg ro und a nd the WI S:do m o ptimiza tio n mo de l II. Main mode ling r e sults and analysis I I I . Co nc lusio ns I V. Mo de ling inputs a nd a ssumptio ns
Ke y F indings E le c tric Sto ra g e in MN re duc e s the le ve lize d c o st o f e le c tric ity • thro ug ho ut the MI SO fo o tprint a nd is a lwa ys se le c te d b y 2045 whe n a va ila b le ; MI SO is c a pa b le o f re duc ing GHG e missio ns b y 80% b y 2050 • witho ut sto ra g e ; ho we ve r, with sto ra g e a s a n o ptio n, L COE is re duc e d a nd le ss fo ssil fue l g e ne ra tio n is re q uire d; T he e ffic a c y o f e le c tric sto ra g e is inc re a se d whe n use d in • c o mb ina tio n with tra nsmissio n e xpa nsio n; L e ss tra nsmissio n e xpa nsio n is re q uire d whe n sto ra g e is se le c te d, • whe n a ll o the r c o nside ra tio ns a re he ld e q ua l.
Ke y F indings (c ontinue d) Mo re sto ra g e is se le c te d b y the WI S:do m o ptimiza tio n mo de l • whe n the I T C is a pplie d to sto ra g e a s we ll a s so la r PV; F inding s a re c o nsiste nt a nd suppo rtive o f the MRI T S study – MN • c a n suppo rt 40%+ va ria b le g e ne ra tio n. Curre nt study finds le ast-c o st c o nfig uratio ns thro ug ho ut MI SO b ase d upo n ho urly, hig h g ranularity we athe r data fo r variab le re ne wab le s; WI S:do m finds e c o no mic and c o nstraine d sc e nario s to de te rmine an ag no stic e nve lo pe parame te r spac e fo r ro le o f diffe re nt te c hno lo g ie s; Sto ra g e pro vide s lo we r c o sts, hig he r re silie nc y (g re a te r po rtfo lio • dive rsity), re se rve s, susta ina b le re so urc e use , a nd inc re a se d tra nsmissio n e ffic ie nc y.
WIS:dom Simulation Matr ix F or Study Re sults a rc hive is fo und thro ug h: http:/ / www.vib ra ntc le a ne ne rg y.c o m/ me dia / re po rts/
J09: No T r ansmission E xpansion, No Stor age , No GHG Constr aints
J09: No T r ansmission E xpansion, No Stor age , No GHG Constr aints
J02: T r ansmission E xpansion, Stor age Allowe d, No GHG Constr aints By a llo wing sto ra g e to pa rtic ipa te (a lo ng with tra nsmissio n) the GHG e missio ns de c re a se a nd so do e s the c o st o f e le c tric ity
J02: T r ansmission E xpansion, Stor age Allowe d, No GHG Constr aints
J02: T r ansmission E xpansion, Stor age Allowe d, No GHG Constr aints
J06: T r ansmission E xpansion, Stor age Allowe d, GHG Constr aine d Sto ra g e (with tra nsmissio n) a ssist in the re duc tio n o f GHGs a t lo we r c o st tha n witho ut sto ra g e a nd fa c ilita te hig he r a mo unts o f RE
J06: T r ansmission E xpansion, Stor age Allowe d, GHG Constr aine d
J06: T r ansmission E xpansion, Stor age Allowe d, GHG Constr aine d Sub sta ntia lly re duc e s the a mo unt o f tra nsmissio n ne e de d, c o mpa re d with pre vio us MI SO re po rt
Ove rvie w I . Ba c kg ro und a nd the WI S:do m o ptimiza tio n mo de l I I . Ma in mo de ling re sults a nd a na lysis III. Conc lusions I V. Mo de ling inputs a nd a ssumptio ns
Conc lusions: Summar y F r om Othe r Case s F o rc e d sto ra g e sc e na rio re sults in a n inc re a se in L COE o f 0.2% c o mpa re d with the J09, b ut with 3% lo we r GHG e missio ns . F o rc e d sto rag e inc re ase s b y 3 GW e ac h inve stme nt pe rio d to 24 GW b y 2050 . Sto ra g e inc luding I T C re sults in e a rlie r a do ptio n b y the WI S:do m mo de l o f sto ra g e . I t fa c ilita te s a re duc tio n in L COE o f 0.5% a nd a n a dditio na l 6 GW o f sto ra g e b y 2050. Whe ne ve r tra nsmissio n e xpa nsio n is a llo we d, WI S:do m se le c ts mo re sto ra g e tha n whe n it is no t a llo we d. Mo re so la r PV is se le c te d b y WI S:do m whe n mo re sto ra g e is a va ila b le . Sto ra g e c o mpe te s with a nd re duc e s CT s in so me re g io ns o f MI SO a s sto ra g e b e c o me s e c o no mic a l. Pa rtic ula rly in the “fo rc e d sto ra g e ” sc e na rio . All o the r re sults a re c o nsiste nt with tho se sho wn; mo re tra nsmissio n re sults in mo re sto ra g e de plo ye d, e missio n ta rg e ts inc re a se sto ra g e de plo yme nt, inc re a se d sto ra g e pro mo te s mo re so la r PV de plo yme nt.
Conc lusions Ado pting sto ra g e no w a dds no sig nific a nt c o st o r risk to the MN e ne rg y po rtfo lio ; ra the r it fa c ilita te s a mo re dive rse future po rtfo lio . Sto ra g e a ssists with re a c hing RPS g o a ls/ ta rg e ts a nd c a n lo we r the c o st o f e ne rg y a c ro ss MN a nd MI SO. Sto ra g e he lps re duc e the b urde n o n tra nsmissio n whe n hig h re ne wa b le s e xist. Sto ra g e re pla c e s CT s o n a c o st b a sis b y (a t le a st) 2040, muc h e a rlie r if I T C is inc lude d. Sto ra g e is a use ful to o l in pro viding a “le a st-re g re ts, le a st- c o st” e ne rg y tra nsitio n stra te g y.
T hank You Dr Christo phe r T M Cla c k CE O Vib rant Cle an E ne rg y, L L C T e le pho ne : +1-720-668-6873 E -ma il: c hristo phe r@ vib ra ntc le a ne ne rg y.c o m We b site : Vib ra ntCle a nE ne rg y.c o m
Ove rvie w I . Ba c kg ro und a nd the WI S:do m o ptimiza tio n mo de l I I . Ma in mo de ling re sults a nd a na lysis I I I . Co nc lusio ns IV. Mode ling inputs and assumptions
Mode ling Inputs and Assumptions
Mode ling Inputs and Assumptions
Mode ling Inputs and Assumptions
Mode ling Inputs and Assumptions
Mode ling Inputs and Assumptions
Mode ling Inputs and Assumptions
Mode ling Inputs and Assumptions
Mode ling Inputs and Assumptions
Mode ling Inputs and Assumptions
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