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Title: Estimating the maximum potential revenue for grid connected electricity storage :

Abstract

The valuation of an electricity storage device is based on the expected future cash flow generated by the device. Two potential sources of income for an electricity storage system are energy arbitrage and participation in the frequency regulation market. Energy arbitrage refers to purchasing (stor- ing) energy when electricity prices are low, and selling (discharging) energy when electricity prices are high. Frequency regulation is an ancillary service geared towards maintaining system frequency, and is typically procured by the independent system operator in some type of market. This paper outlines the calculations required to estimate the maximum potential revenue from participating in these two activities. First, a mathematical model is presented for the state of charge as a function of the storage device parameters and the quantities of electricity purchased/sold as well as the quantities o ered into the regulation market. Using this mathematical model, we present a linear programming optimization approach to calculating the maximum potential revenue from an elec- tricity storage device. The calculation of the maximum potential revenue is critical in developing an upper bound on the value of storage, as a benchmark for evaluating potential trading strate- gies, and a tool for capital nance risk assessment. Then,more » we use historical California Independent System Operator (CAISO) data from 2010-2011 to evaluate the maximum potential revenue from the Tehachapi wind energy storage project, an American Recovery and Reinvestment Act of 2009 (ARRA) energy storage demonstration project. We investigate the maximum potential revenue from two di erent scenarios: arbitrage only and arbitrage combined with the regulation market. Our analysis shows that participation in the regulation market produces four times the revenue compared to arbitrage in the CAISO market using 2010 and 2011 data. Then we evaluate several trading strategies to illustrate how they compare to the maximum potential revenue benchmark. We conclude with a sensitivity analysis with respect to key parameters.« less

Authors:
;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1088080
Report Number(s):
SAND2012-3863
456396
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English

Citation Formats

Byrne, Raymond Harry, and Silva Monroy, Cesar Augusto. Estimating the maximum potential revenue for grid connected electricity storage :. United States: N. p., 2012. Web. doi:10.2172/1088080.
Byrne, Raymond Harry, & Silva Monroy, Cesar Augusto. Estimating the maximum potential revenue for grid connected electricity storage :. United States. doi:10.2172/1088080.
Byrne, Raymond Harry, and Silva Monroy, Cesar Augusto. Sat . "Estimating the maximum potential revenue for grid connected electricity storage :". United States. doi:10.2172/1088080. https://www.osti.gov/servlets/purl/1088080.
@article{osti_1088080,
title = {Estimating the maximum potential revenue for grid connected electricity storage :},
author = {Byrne, Raymond Harry and Silva Monroy, Cesar Augusto.},
abstractNote = {The valuation of an electricity storage device is based on the expected future cash flow generated by the device. Two potential sources of income for an electricity storage system are energy arbitrage and participation in the frequency regulation market. Energy arbitrage refers to purchasing (stor- ing) energy when electricity prices are low, and selling (discharging) energy when electricity prices are high. Frequency regulation is an ancillary service geared towards maintaining system frequency, and is typically procured by the independent system operator in some type of market. This paper outlines the calculations required to estimate the maximum potential revenue from participating in these two activities. First, a mathematical model is presented for the state of charge as a function of the storage device parameters and the quantities of electricity purchased/sold as well as the quantities o ered into the regulation market. Using this mathematical model, we present a linear programming optimization approach to calculating the maximum potential revenue from an elec- tricity storage device. The calculation of the maximum potential revenue is critical in developing an upper bound on the value of storage, as a benchmark for evaluating potential trading strate- gies, and a tool for capital nance risk assessment. Then, we use historical California Independent System Operator (CAISO) data from 2010-2011 to evaluate the maximum potential revenue from the Tehachapi wind energy storage project, an American Recovery and Reinvestment Act of 2009 (ARRA) energy storage demonstration project. We investigate the maximum potential revenue from two di erent scenarios: arbitrage only and arbitrage combined with the regulation market. Our analysis shows that participation in the regulation market produces four times the revenue compared to arbitrage in the CAISO market using 2010 and 2011 data. Then we evaluate several trading strategies to illustrate how they compare to the maximum potential revenue benchmark. We conclude with a sensitivity analysis with respect to key parameters.},
doi = {10.2172/1088080},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Dec 01 00:00:00 EST 2012},
month = {Sat Dec 01 00:00:00 EST 2012}
}

Technical Report:

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  • This guide describes a high-level, technology-neutral framework for assessing potential benefits from and economic market potential for energy storage used for electric-utility-related applications. The overarching theme addressed is the concept of combining applications/benefits into attractive value propositions that include use of energy storage, possibly including distributed and/or modular systems. Other topics addressed include: high-level estimates of application-specific lifecycle benefit (10 years) in $/kW and maximum market potential (10 years) in MW. Combined, these criteria indicate the economic potential (in $Millions) for a given energy storage application/benefit. The benefits and value propositions characterized provide an important indication of storage system costmore » targets for system and subsystem developers, vendors, and prospective users. Maximum market potential estimates provide developers, vendors, and energy policymakers with an indication of the upper bound of the potential demand for storage. The combination of the value of an individual benefit (in $/kW) and the corresponding maximum market potential estimate (in MW) indicates the possible impact that storage could have on the U.S. economy. The intended audience for this document includes persons or organizations needing a framework for making first-cut or high-level estimates of benefits for a specific storage project and/or those seeking a high-level estimate of viable price points and/or maximum market potential for their products. Thus, the intended audience includes: electric utility planners, electricity end users, non-utility electric energy and electric services providers, electric utility regulators and policymakers, intermittent renewables advocates and developers, Smart Grid advocates and developers, storage technology and project developers, and energy storage advocates.« less
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  • The Sandia Laboratories' optimizing computer code, SOLSTOR, has been used to investigate the role of battery storage in a residential photovoltaic system. The system is connected to the utility grid, and Time-of-Day (TOD) pricing and sell-back policies are considered. Several parameters, including geographic location, were varied, resulting in a large number of systems optimized with respect to the 20-year life cycle cost of providing energy for an all-electric home. Conclusions are that battery costs of around $100/kWh or less are required for storage to be economically beneficial, when combined with TOD ratios of 3:1 or more, or sell-back ratios ofmore » 0.5 or less.« less
  • This report documents the assessment of performance and design of a 250-kW prototype battery energy storage system developed by Omnion Power Engineering Company and tested by Pacific Gas and Electric Company, both in collaboration with Sandia National Laboratories. The assess- ment included system performance, operator interface, and reliability. The report also discusses how to detect failed battery strings with strategically located voltage measurements.
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