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ELECTRICITY STORAGE: APPLICATIONS AND BUSINESS CASES

CERI Breakfast Overview Allan Fogwill, President & CEO NAIT – Edmonton October 17, 2019

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Flagship Breakfast Overview Sponsor:

CANADIAN ENERGY RESEARCH INSTITUTE

Overview

Founded in 1975, the Canadian Energy Research Institute (CERI) is an independent, registered charitable organization specializing in the analysis of energy economics and related environmental policy issues in the energy production, transportation, and consumption sectors. Our mission is to provide relevant, independent, and objective economic and environmental research of energy issues to benefit business, government, academia and the public. CERI publications include:

• Market specific studies
• Geopolitical analyses
• Quarterly market reports (crude oil, electricity and natural gas)

In addition, CERI hosts a series of study overview events, executive briefings for organizations and an annual Petrochemicals Conference.

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CORE FUNDERS

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DONORS

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Ivey Foundation

AGENDA

• Introduction
• Energy storage applications:
• Behind the fence applications
• Energy arbitrage
• Renewable energy firming
• Results
• Conclusions

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ENERGY STORAGE: A RAPIDLY GROWING TECHNOLOGY

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ENERGY STORAGE APPLICATIONS

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APPLICATIONS – STORAGE TECHNOLOGY MATCHING

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SCOPE AND OBJECTIVES OF THIS STUDY

• Review current status of energy storage
• Provide an outlook of future cost of select energy storage
• Assess three energy storage applications for Canadian electricity

systems

• 1. Bill malmanagement (Customer side)
• 2. Bulk energy arbitrage (Grid side)
• 3. Renewable energy firming
• Use two metrics
• Internal rate of return (IRR) (cases 1 & 2)
• Levelized cost of electricity (LCOE) (case 3)
• Methods
• Application simulation models (cases 1 & 2)
• Optimization model for renewable energy and storage sizing (case 3)

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ENERGY STORAGE TECHNOLOGY CLASSIFCATION

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COST OF ENERGY STORAGE TECHNOLOGIES

• Cost decline due to technology learning: Rapid growth in energy

storage will lead to decline in capital costs

• Decline in costs are already observed
• Some technologies are growing faster than the rest
• Lithium and flow batteries are advancing at the fastest rate
• Utility-scale Battery costs are expected to see around 8% per

year cost decline over the next three years

• Capital cost of a utility-scale lithium-ion battery storage capital

costs are expected to decline by 52% between 2018 and 2030

• Cost of hydrogen fuel cells too are expected decline at a faster

rate

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FUTURE CAPITAL COSTS OF SELECT ENERGY STORAGE TECHNOLOGIES

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APPLICATION 1: BILL MANAGEMENT USING BEHIND-THE-METER (BTM) ENERGY STORAGE

• Commercial and industrial customers usually pay for facility

demand charges according to the peak demands recorded during their billing periods.

• The demand charges can amount to 50% of their total monthly

electricity bill.

• The demand charges can be decreased either by shaving the

peak demands using ESS or through shifting some of the

• perations from on-peak to off-peak hours (aka demand response

program) .

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APPLICATION 1: BILL MANAGEMENT USING BEHIND-THE-METER (BTM) ENERGY STORAGE

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Demand Charge Reduction

Shaving the peak demands using ESS Shifting operations from

• n- to off-peak hours

(Response program) NOT straight-forward to implement

(many legal, technical, and commercial issues need to be addressed before the fact)

The storage device stores energy during the

• ff-peak hours to

later discharge it within on- peak hours Promoted by: Noticeable Storage Cost Reductions

APPLICATION 1: BILL MANAGEMENT USING BEHIND-THE-METER (BTM) ENERGY STORAGE

• Four types of customers
• Secondary school
• Hotel
• Hospital
• Large office building
• Small mall building
• Five provinces (AB, BC, SK, ON, NB)
• Mainly due to availability of complete rate structure

information

• Lithium-iron storage
• Due to scalability and maturity
• Simulation model to optimally size storage
• Estimated the IRR of the application case
• Both current costs and future cost of storage (2020, 2030, 2040)

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SAMPLE BATTERY OPTIMAL SIZING FOR A SECONDARY SCHOOL IN AB (2025)

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E (kWh): 24 P (kW): 48 IRR: 17%

ECONOMIC ASSESSMENT OF ESS FOR BTM APPLICATIONS IN CANADIAN PROVINCES

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The load profiles of these facilities are collected from the public data available

• n OpenEI (OpenEI 2019)

APPLICATION 1: CONCLUDING REMARKS

• Lithium-ion batteries are the most widely utilized storage

technology, primarily because of their fast and powerful response to the demand making them an ideal candidate for this role.

• The shape of the load profile of a facility is the primary factor

controlling the amount of peak demand reduction achieved by

• ESS. Thus, any recommended size for the ESS will be specific to

that facility.

• Utility rate structure (primarily the difference between energy and

peak demand charges) is the second important factor affecting the profitability of ESS for BTM applications.

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APPLICATION 2: BULK ENERGY ARBITRAGE

• Buy electricity when price is low and sell back when the price is

high

• Possible when an open energy market is available
• Use Alberta market for the analysis
• Electricity prices observed over last four years
• Three storage technologies
• CAES, Flow batteries, and Li-ion batteries
• Simulation model with IRR analysis

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OBSERVED ELECTRICITY PRICES

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ENERGY ARBITRAGE (RESULTS)

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CAPACITY PAYMENTS

• Energy storage can provide capacity services and earn revenue
• Estimated the capacity payments required to break even under

current storage capital costs (assumed 2018 electricity prices)

• Required annual capacity payment to breakeven:
• CAES: $9000/MW
• Li-ion: $253,000/MW
• Flow batteries: $69,000/MW
• Assume that both energy market revenues and capacity

payments are stackable

• Note that CAES technology requires lower annual capacity

market payments due to its lower investment cost and longer project lifetime (30 years)

• It is higher for flow and Li-ion, mainly because of the shorter

project lifetime (16 years and 9 years respectively)

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APPLICATION 2: CONCLUDING REMARKS

• None of the technologies assessed are economically attractive

with the current capital cost and Alberta under current costs when energy arbitrage is the only revenue stream

• Higher spread between peak price and off-peak price improves

economics for energy storage under energy arbitrage applications

• Deploying the learning rate for future cost reduction shows that
• nly flow batteries have the potential to reach positive IRR values

(around 5%).

• For Li-ion batteries, despite the similar overnight cost as

compared to flow batteries, their IRR values remain negative by 2040, which is due to the low battery life cycle (9 years).

• Because of the replacement cost, fuel cost, and mature

technology (no potential reduction in capex), the storage using standalone CAES technology is not economically attractive (negative IRR value).

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APPLICATION 3: RENEWABLE ENERGY FIRMING

• Variable renewable energy firming is considered as a main

application for energy storage under current policies and market conditions

• Variable renewable such as wind and solar are intermittently

available and not necessarily available when the system needs energy/capacity

• Energy storage can be used to make variable renewables

dispatchable

• Assessed a case where co-located wind, solar PV, and energy

storage systems makes a electricity generation system with:

• 90% availability in peak demand periods
• 60% availability in other times
• Mimics a the reliability of a typical generating system

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APPLICATION 3: RENEWABLE ENERGY FIRMING

• All 10 Canadian provinces
• 30 locations with good wind and solar PV resources per province
• Wind resource availability: 30-42%
• Solar PV resource availability: 12-16%
• Storage technologies considered:
• Battery storage (Li-iron and flow batteries)
• Hydrogen fuel cells
• Optimization model that runs at hourly resolution to estimate optimal

generation and storage capacity

• Estimated the LCOE at each of the 300 locations in 2020, 2030, and

2040

• Considered technology learning for storage and renewable capital

costs

• Select the rated capacity of the integrated electricity generation

system to be 100MW

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LEVELIZED COST OF ELECTRICITY BY INVESTMENT YEAR AND PROVINCE

(all LCOE values are in cents/kWh)

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2020 2030 2040 Province Mean Range Mean Range Mean Range AB 22 [19 - 23] 17 [16 - 18] 15 [14 - 15] MB 18 [16 - 19] 16 [15 - 18] 15 [14 - 16] NS 18 [16 - 21] 15 [13 - 17] 14 [12 - 16] ON 19 [18 - 26] 16 [15 - 21] 14 [13 - 19]

• Depending on the province, LCOE reductions of up to 22% by 2030

and 32% by 2040 are possible due to technology learning

STORAGE UTILIZATION OVER TWO WEEKS IN SUMMER

location with lowest LCOE in Ontario

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TECHNICAL ATTRIBUTES OF REQUIRED STORAGE SERVICES

• Storage is utilized in two primary time scales
• Intra-day energy time-shifting
• Mainly solar PV time shifting: from daylight hours to other

periods

• Li-iron and flow batteries are more economical to provide this

service

• Inter-day and inter-week energy time-shifting
• Under assumed costs, hydrogen fuel cells are economical to

provide long duration storage arbitrage

• Compressed air energy storage can potentially provide long duration

energy storage

• However, expected cost decline of hydrogen fuel cells are more

competitive over long run and more economical than CAES

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COMPRESSED AIR ENERGY STORAGE: OPPORTUNITIES TO REDUCE CAPITAL COST

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• Cost of energy storage system (i.e.,

storage cavern) can potentially be reduced by utilizing existing reservoirs such as abandoned oil and gas reservoirs

• This potential need to be assessed

case by case through detailed geological and economic assessments

• For example, to build a 100MW

CAES system with 8 hours of storage duration require about $154 million, of which 26% is spent on storage cavern

• If cavern cost can be reduced by

50% by utilizing existing reservoirs, total capital cost can be reduced by 13%

CAPEX - Power 74% CAPEX - Energy 26%

100MW with 8 hours of storage duration CAPEX: $154 million

APPLICATIONS 3: CONCLUDING REMARKS

• Renewable energy with storage can produce 100% emissions free

electricity

• Average cost is lower when temporally stable resource–primarily

wind—regimes are available as it reduces the average storage cost

• LCOE of renewable energy firmed up with storage under current

costs are higher under current costs (for 2020 investment year)

• Depending on the province, LCOE reductions of up to 22% by 2030

and 32% by 2040 are possible due to technology learning

• Still higher, compare to competing conventional technologies
• In Ontario, without carbon pricing, NGCC LCOE is about 8.2

cents/kWh

• By 2030-2040 time period, variable renewables and storage

combined systems are competitive against other zero GHG emissive dispatchable technologies such as nuclear power, large hydro, coal/NG fired units with carbon capture and storage (not non zero GHG emissions)

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THANK YOU

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