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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

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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

  • r:

Minne sota Public Utility Commission

July 11th, 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.

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SLIDE 2

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
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SLIDE 3

Ove rvie w

I. Bac kgr

  • und 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
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SLIDE 4

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 .

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SLIDE 5

MISO high pe ne tr ation r e ne wable e ne r gy study for 2050

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SLIDE 6

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

  • f c a pa c ity c o sts
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SLIDE 7

MISO high pe ne tr ation r e ne wable e ne r gy study for 2050

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SLIDE 8

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.

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SLIDE 9

T he WIS:dom Optimization Mode l

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T he WIS:dom Optimization Mode l

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SLIDE 11

T he WIS:dom Optimization Mode l

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SLIDE 12

T he WIS:dom Optimization Mode l - MISO

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SLIDE 13

T he WIS:dom Optimization Mode l - MISO

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SLIDE 14

T he WIS:dom Optimization Mode l - MISO

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SLIDE 15

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
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SLIDE 16

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.

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SLIDE 17

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.

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SLIDE 18

WIS:dom Simulation Matr ix F

  • r

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/

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J09: No T r ansmission E xpansion, No Stor age , No GHG Constr aints

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J09: No T r ansmission E xpansion, No Stor age , No GHG Constr aints

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SLIDE 21

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

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SLIDE 22

J02: T r ansmission E xpansion, Stor age Allowe d, No GHG Constr aints

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SLIDE 23

J02: T r ansmission E xpansion, Stor age Allowe d, No GHG Constr aints

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SLIDE 24

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

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J06: T r ansmission E xpansion, Stor age Allowe d, GHG Constr aine d

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SLIDE 26

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

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SLIDE 27

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
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SLIDE 28

Conc lusions: Summar y F r

  • m Othe r

Case s

  • F
  • rc e d sto ra g e sc e na rio re sults in a n inc re a se in L

COE

  • f 0.2% c o mpa re d with

the J09, b ut with 3% lo we r

GHG e missio ns. F

  • 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

  • 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.

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SLIDE 29

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.

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SLIDE 30

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

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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
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Mode ling Inputs and Assumptions

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Mode ling Inputs and Assumptions

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Mode ling Inputs and Assumptions

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Mode ling Inputs and Assumptions

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Mode ling Inputs and Assumptions

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Mode ling Inputs and Assumptions

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Mode ling Inputs and Assumptions

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Mode ling Inputs and Assumptions

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Mode ling Inputs and Assumptions