Towards Energy Storage for Profitable Renewable Integration:

What’s Needed and When

(Valuating Functional Loss in Energy Storage Installations)

Jay Whitacre, Guannan He

Scott Institute for Energy Innovation, Department of Engineering and Public Policy,

Department of Materials Science and EngineeringCarnegie Mellon University

Harvard April 20191

Motivation…

Economically Viable Electrochemical energy storage (EES) is enabling future power systems

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What is Economic Viability?

• (of course) Depends on the application• Low hanging fruit

• C&I demand reduction• Ancillary services

• “white whale” of storage: renewable integration. . . .

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Already Viable! Small market price taking assumptions needed

4https://about.bnef.com/blog/battery-powers-latest-plunge-costs-threatens-coal-gas/

5https://about.bnef.com/blog/battery-powers-latest-plunge-costs-threatens-coal-gas/

“Onshore wind and photovoltaic solar have also gotten cheaper, their respective benchmark LCOE reaching $50 and $57 per megawatt-hour for projects starting construction in early 2019, down 10% and 18% on the equivalent figures of a year ago.”

“. . .lithium-ion battery storage has dropped by 76% since 2012, based on recent project costs and historical battery pack prices.”

• “Levelized cost of stored electricity” used most commonly to valuate and inform decisions- Very basic/simple approach typically used: storage capX price is

amortized through cycles as weighted by efficiency and discount rate- Does not contemplate degradation or how to valuate it over time

Focus on Utility Use and Economics

6*https://www.solarpowerworldonline.com/2016/12/calculating-true-cost-energy-storage/

7Kittner, N., Lill, F. & Kammen, D. M. Energy storage deployment and innovation for the clean energy transition. Nat. Energy 2, 17125 (2017).

?Capacity = f(cycles, depth of discharge, temperature)

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Testing on Tesla “Model S” Battery Cells at CMU

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The Materials Science of Battery Aging. . .

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11Kittner, N., Lill, F. & Kammen, D. M. Energy storage deployment and innovation for the clean energy transition. Nat. Energy 2, 17125 (2017).

?Capacity = f(cycles, depth of discharge, temperature)

• In General – as DoD and Cycles are increased, Capacity decreases

• Fewer actual cycles the more you use the pack• ~1000 Full cycles or less for EV packs

• NOT a problem for cars. . . • HUGE problem for 4 hour stationary storage

12Kittner, N., Lill, F. & Kammen, D. M. Energy storage deployment and innovation for the clean energy transition. Nat. Energy 2, 17125 (2017).

“Based on a ten-year project lifetime, and in the optimal case assuming a full charge–discharge cycle on a daily basis ignoring losses, LCOE at current prices is US$0.15 kWh−1 at residential scale and US$0.10 kWh−1 at utility scale”

Kittner, N., Lill, F. & Kammen, D. M. Energy storage deployment and innovation for the clean energy transition. Nat. Energy 2, 17125 (2017).

13Kittner, N., Lill, F. & Kammen, D. M. Energy storage deployment and innovation for the clean energy transition. Nat. Energy 2, 17125 (2017).

Baseload Renewables Coming Soon??

• No. These LCOE values are off by at least a factor of 2• The relationship between cycle life and DoD is not captured

properly in these common market assessments• What is actually needed (to get to a place where subsidies might

work): • LCOE adder for storage is less than the cost of the primary

energy (~$5/MWh)• Energy storage with installed capital costs of < $75/kWh, with at least

2000 100% cycles of known non-fading capacity• NO known battery can do this – some long term projects seeking

solution

The Present Reality

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• Like other installed capital assets, batteries have more value earlier in their life, and less value as they age

• Use/dispatch decisions should be based on the evolving present value of the assets, and weighed against the use case value proposition

Our Solution: Create A dispatch decision model that incorporates incremental battery degradation to determine the true value and the optimal

dispatch for different use cases of the storage asset

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Why Intertemporal?• Intertemporal choice/decision is used when choices at one time influence the

possibilities available at other points in time

• Short-term operational decision is necessary‒ Accurate forecasting information is only available in day/hour-ahead

• The degradation/usage of battery has long-term constraint and effects‒ The incremental degradation accumulates and affects future profitability‒ The total degradation/usage of battery has a life-cycle limit

• The short-term profit opportunities vary significantly in long term‒ Weekday v.s. Weekend/Holiday, Summer v.s. Winter‒ Increasing penetration of renewables

• Battery owner has time preference in battery revenues

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New Metrics/Concepts Introduced. . .

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Marginal Benefit of Usage Average Benefit/Cost of Usage• Average Benefit of Usage (ABU):

The average life-cycle benefit per unit of battery usage/degradation

• Average Cost of Degradation (ACD): The average capital cost per unit of battery degradation

CAPEXACDD

=

maxLBABU

D=• Derivation: A necessary optimality

condition for long-term optimization problem that maximizes the life-cycle benefit:

• Definition: The maximum benefit that can be achieved with an incremental unit of battery usage/degradation

Short-term Benefit MBU Degradation Discount Factor

t

t t

∂=

∂

The Framework

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Maximize

MaximizeShort-term

Mid-term

Long-term

Operating

Aggregate

Aggregate

DailyOutputs

Discounted MBU

Life-cycle MBU

Decisions

Daily Benefit

Annual Benefit

Life-cycle Benefit

Objectives

Short-termPrices

Life-cycle Degradation

Inputs

ABU

Capital Cost

InvestmentPlanning

SubsidyACD

Decision Order

Simulation Order

Case Study: Energy Arbitrage

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Power capacity 50 MW

Energy capacity 200 MWh

Cycle life 3000 cycles-100% DOD30000 cycles-10% DOD

Calendar degradation 0.5% capacity loss/year

Capital Cost $200-300/kWh

Charge/discharge efficiency 90%

Price scenario: California ISO 2016 market prices

~3X better than most data suggests

Optimal Decisions - Year 11DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 22DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 33DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 44DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 55DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 66DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 77DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 88DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 99DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 1010DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Optimal Decisions - Year 1111DMBU (1 7%) 5 $/MWh-throughput= + ⋅

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Decreasing Value Analysis

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Valuation & SubsidyEnergy

ArbitrageEnergy Arbitrage +

Frequency Regulation

Total profit ($ million 2016) 8 37

Optimal MBU ($/MWh-throughput) 5 25

ABU ($/MWh-throughput) 7 35

Unit capacity capital cost ($/kWh) 200 200

Average cost of degradation ($/MWh-throughput) 33 33

Break-even capital cost ($/kWh) 40 210

Required subsidy ($/MWh-throughput) 26 0

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Summary• Current energy storage technology is not tenable for making renewable +

Battery power economically competitive. . • capacity fade + capX are both issues

• An intertemporal framework for quantitatively assessing values and costs, and determining the optimal dispatch of electrochemical energy storage has been developed

• We introduce new usage/degradation metrics (ABU & ACD) for economic assessment, subsidy design and technology learning study of battery storage.

• The only viable use case calls on multiple income streams, some of which are limited in market size.

Long-term Decision

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Numerically optimize the life-cycle MBU based on historical and forecast information

Arbitrarily setting the unit cost of degradation in short-term operational decisions could cause great life-cycle benefit loss