cutter - e3 valuing storage short

Uncertainty and the Value of Energy Storage

Storage Week January 25, 2016

San Diego, CA

Eric Cutter

UTILITY VIEW

2

$0

$50

$100

$150

$200

$250

$300

$350

Combustion Turbine(2014)

Leve

lized

$/k

W-Y

r

Fixed Cost$200

Net Rev-enue$63

Net Capac-ity Cost$137

Utility view of storage: a CT

Fitting storage into a “standard” capacity product undervalues storageBest value for ratepayers requires better matching of technologies the grid services

3

aka “CONE”: Cost of New Entry

$0

$50

$100

$150

$200

$250

$300

$350

Flexible Capacity Product

Leve

lized

$/k

W-Y

r

Fixed Cost

Net Rev-enue

Net Ca-pacity Cost

Reducing cost of storage

Cost benchmarks that reflect future system needsForward looking flexibility value with high RPS

Operating experience and cost reductions for the storage needed in 2020

4

FUTURE BENEFITS OF STORAGE

6

Flexibility needed for high renewable penetration

Over-generation

is a new challenge in

solar-dominant

systems like CA

40% RPS Spring Day Generation

Profile

Grid benefits performed by flexible resources

7

Net Market Value

Utilities evaluate storage based on net market valueUtility planning assumptions and models determine benefits

Today Tomorrow

8

Challenges selling to utility

Not necessarily convinced they need storageUse traditional models and valuation frameworkFocus on costFocus on today’s marketsGetting multiple departments to sing in unisonLittle sense of urgency: wait and see approach

LOOKING AHEAD - WEST

9

10

WECC Wide Flexibility Study

10

Main zone:• Optimal investment decisions• Detailed treatment of operating

reservesOther zones:• Exogenous resource assumptions

and loads by scenarioFlows may be impacted by:• Min and max intertie flow

constraints• Min and max simultaneous flow

constraints for groups of interties• Ramping constraints on interties• Hurdle rates

Example zonal structure – High Renewable West Scenario

11

California dispatch, average net load day in May

California Overgeneration Driven by Mid-day Solar Production

Gas fleet operates at minimum, subject to

min gen constraint

Renewable production from solar PV causes mid-day oversupply, leading

to curtailment

Significant imports during shoulder periods

Renewable Penetration: 50%(% of load)

Renewable Curtailment: 8.7%(% of annual renewables)

Curtailment Frequency: 20%(% of hours per year)

12

Northwest dispatch, average net load day in May

Renewable Penetration: 30%(% of load)

Renewable Curtailment: 6.1%(% of annual renewables)

Curtailment Frequency: 10%(% of hours)

Northwest Overgeneration Results from Combined Hydro & Wind

Curtailment occurs throughout day but is most pronounced at night

(low loads & high wind)

Hydro energy accounts for significant shares of daily load

Significant exports during off-peak hours,

but limited during middle of day

13

Southwest

Scale (MW)

0

7,000

Northwest

Scale (MW)

0

4,000HE01 HE24

JanFebMarAprMayJunJulAugSepOctNovDec

HE01 HE24JanFebMarAprMayJunJulAugSepOctNovDec

California


HE01 HE24JanFebMarAprMayJunJulAugSepOctNovDecTot: 8.7%

Scale (MW)

0

16,000

Tot: 3.0%



Regional Coordination is a Low-Hanging Fruit Among Solutions

Historical IntertieLimits

Physical IntertieLimits

Tot: 5.6% Tot: 2.0%

Tot: 7.3% Tot: 6.1%

Large reductions in nighttime curtailment

Large reductions in non-spring curtailment

Limited impact on curtailment

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Storage Downward Flexibility Reduces Curtailment

Addition of 6 GW of long-duration storage relieves curtailment

Addition of 6 GW of flexible CCGTs has little impact

Source: TEPPC Western Interconnection Flexibility Assessment 04 Nov 2015

LOOKING AHEAD - EAST

16

Forward curves under energy policy uncertainty

Reference case represents best in class energy market and capacity market dispatch. Extension to scenario analysis approach describing key context and impact of policy on energy market identifies critical market disruptions

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Reference Case: Compliance with existing policy, with expected technology advancements

and cost reductions

High Renewables: Implement required renewables to hit

goal despite budget constraints. Increasing to 50% renewable

generation

REV Policy Case:Assuming successful policy

implementation and increased DER participation in energy markets.

Changing the load profile and load factor

$0

$20

$40

$60

$80

$100

$120

2008

2010

2012

2014

2016

2018

2020

2022

2024

2026

2028

2030

2032

2034

Ener

gy P

rice

($/M

Wh)

Year

HistoricalBusiness-as-usual

High Renewables

Long Island Baseload Energy Price ($/MWh)

Results show significant changes in market fundamentals depending on policy case and zone

17

REV Background and Impact

The goal of the REV proceeding is to facilitate the deployment of distributed energy resources (DER), provide consumers with choice and value over their energy use, and improve system efficiencyDetails of how to these goals will be achieved are not finalized, but a successful REV program should improve system efficiencyTo assess wholesale impacts of distributed resources, we assume NYISO’s system load factor improves to 60% by 2030 (agnostic to technology)Details

17

1 24

Load

(MW

)

Hour

Hourly Load Shape in 2030

Base load shape

REV load shapeFlatter due tovarious DER deployment

40%

45%

50%

55%

60%

65%

70%

75%

80%

1995

1997

1999

2001

2003

2005

2007

2009

2011

2013

2015

2017

2019

2021

2023

2025

2027

2029

Load

Fac

tor (

%)

Year

NYCA Annual Load Factor

Historical

BaseSystem efficiencycontinues to decline

REV ScenarioDER improvessystem efficiency

18

0

1,000

2,000

3,000

4,000

5,000

6,000

BAU High RE REV

Sum

mer

Cap

abili

ty (M

W)

Scenario

New Gas Plant Investment by 2035

CT Gas

CC Gas

Investment Outlook for New Plants

Economics of new investment varies substantially across scenarios

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Technology BAU High RE REV

Combined Cycle High Low Medium

Combustion Turbine Medium Medium Low

Onshore Wind Medium High Medium

Offshore Wind Low High Low

Utility-scale Solar Low High Low

CC outlook poor due to depressed energy marketCTs still attractive in capacity market

DER impact on load shapereduces need for peaking plants

Summary of Investment Outlook

LOOKING AHEAD - HAWAII

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System Overview

Oahu MauiMolokaiHawaii

Energy Production by Type

Peak Load (MW) 193 6 1176 197.3Min Load (MW) 82 2 521 86.7Pmin+ Downward Reserve (MW) 61 1.8 277 46.98Intermittent RE Capacity ‘15 (MW) 111.8 1.7 420.1 134.3Preapproved DG PV (MW) 25 0.426 117.2 35

44% RE 8% RE 8% RE 32% RE

Island system constrained by Pmin & reserves

Determine whether the net load ever drops below Pmin + reserves• If so, normal system operations are

interruptedHow often do these events occur?What is the frequency and size of the problem?What are the potential solutions?

headroom

21

Comparing Curtailment Cost to Battery Cost

2016

Curtailing renewables is cheaper than installing storage – using traditional evaluation framework

STORAGE VS. OTHER SOLUTIONS

Renewable integration solutions

24

Various solutions have been proposed, with different performance characteristics and costs• Energy storage (pumped hydro, batteries,

compressed air, etc)• Flexible loads or advanced DR• Flexible gas resources (new flexible CCGTs,

Aero CTs, Reciprocating Engines or retrofits to existing plants)

• Expansion/consolidation of balancing areas• Time-of-use rates

Teslamotors.com

http://renews.biz/67193/vattenfall-pumps-new-life-into-80mw

Wartsila.com

http://allthingsd.com/files/2012/10/Nest-Cooling-2.jpg

http://www.theiet.org/membership/member-news/31a/ev-charging-course.cfm

Economics of renewable integration

The consequence of failing to supply enough flexibility to integrate renewables is renewable curtailment

Full capability from procured renewables

Delivered energy from procured renewables

Curtailment

Renewable energy target

Option 1. Overbuild renewables

Anticipated renewable build

Curtailment-related renewable overbuild

Option 1. Overbuild the renewable fleetOverbuilding the renewable fleet allows for policy goal to be met with some allowance for curtailment

Curtailment

Option 2. Pursue integration solutions

Option 2. Pursue integration solutionsIntegration solutions (eg. storage, balancing area consolidation) permit more effective delivery of existing renewable fleet

Energy Storage

Renewable build

Energy storage build

Option 3. Mix of solutions (Options 1 & 2)

Option 3. Find optimal solutionOptimal solution combines multiple strategies based on costs and benefits

Energy Storage

Curtailment

Energy storage build

Anticipated renewable build

Curtailment-related renewable overbuild

Option 3 is Optimal Solution Balances Storage with Overbuild

Optimal amount of storage is highly

sensitive to assumed technology costs

Identifying optimal investment in solutions

30

Single solution case:• The cost of the solution can

be weighed against the avoided cost of overbuilding renewables for RPS compliance

Multiple solution case:• Multidimensional

optimization• Complex interactive effects• Requires sophisticated

model that treats both operations and investment costs

Optimal investment point:

Marginal avoided cost of renewable overbuild

=Marginal cost of solution

Example analysis:Optimal storage investment

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Wide uncertainty in future cost reductions

Wide range in optimal storage build

Base Assumption

Q. Given the wide range of potential future cost trajectories, what is the optimal amount of energy storage?RESOLVE: Storage cost scenarios can be designed to provide a plausible range of least-cost storage procurement strategies; can also:• Identify timing of storage build

across sensitivities• Test cost impacts of suboptimal

storage build

Storage technology costs ultimately determine the optimal energy storage investmentHigh level of uncertainty complicates the planning problem

STORAGE IN WORLD OF UNCERTAINTY - IDSM

32

Capacity Value of Renewables Declines Significantly Above 33%

High penetration of solar PV pushes the “net peak” demand that must be met with dispatchable resources into evening hoursCalifornia will continue to need capacity resources to meet peak demands

0

10

20

30

40

50

60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Load

(GW

)

Hour

0

1

2

3

4

5

6

0 6 12 18Pe

ak L

oad

Redu

ction

(GW

)

Installed Solar PV Capacity (GW)

Daily Load Shape with Increasing Solar PV Cumulative Peak Load Reduction

34

Storage as Part of Optimal Portfolio

DescriptionCurrent situation

Key metrics13.5 MW:Current peak56,000 MWh:Energy5%/year:Load Growth

24 hr load profile

Year on year load profile

Base

Cas

e Fo

reca

st

Alternative future states

Upg

rade

ele

men

ts

DER 1Hardware DER 211 MW 8 MW 4 MWHardware

SolarDREEStorage

Key

met

rics

24 hr load profile

0 MW 1.6 MW 4.4 MW0 MW 3.3 MW 3.3 MW0 MW 1.6 MW 1.6 MW0 MW 0 MW 5 MW

Cash flow

24 hr load profile

Cash flow

24 hr load profile




Cash flow

High load growth in urban area where upgrades are expensive due to site constraints

35

Storage Reduces Risk

Next gen solution

▪ Plan based on value of reliability and cost of upgrade

▪ Factor in forecast uncertainty into investment decision

IDSM ApproachCurrent solution

▪ Engineering studies to identify N-1 redundancy requirement

Identifying investment

▪ Choose from traditional T&D capital investment supply options

▪ Expand options to meet load growth and reliability needs to include DER

▪ Integrate DER and traditional investments in decision process

Investment options for maintaining reliability

Peak load served (MW)Sys

tem

ava

ilabi

lity

(% li

kelih

ood)

99.999%

Additional service from investment

Forecast Years

Pea

k Lo

ad (M

W) Forecast

uncertainty captured

subs

tatio

n

mod

ular

Inte

grat

ed

DE

R

Pre

sent

val

ue $

subs

tatio

n

mod

ular

Inte

grat

ed

DE

R

Exp

ecte

d ou

tage

$

36

Conclusions for energy storage

Utilities feel little sense of urgency: have a wait and see approachTraditional models and valuation frameworks undervalue the flexibility that storage providesTo utilities regional coordination and renewable curtailment look like cheaper alternatives to storageLooking further ahead with stochastic, portfolio models is crucial to fully value storageNeed to show utilities that storage is part of an optimal portfolio in an uncertain world

Thank You!Energy and Environmental Economics, Inc. (E3)101 Montgomery Street, Suite 1600San Francisco, CA 94104Tel 415-391-5100Web: http://www.ethree.com

Eric Cutter ([email protected])

cutter - e3 valuing storage short

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