Optimal Operation Parameter Estimation of Energy Storage for Frequency Regulation

This study proposes a method for optimally selecting the operating parameters of an energy storage system (ESS) for frequency regulation (FR) in an electric power system. First, the method allows the optimal objective function of the selected parameters to be set in a flexible manner according to th...

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Bibliographic Details
Published in:Energies (Basel) 2019-05, Vol.12 (9), p.1782
Main Authors: Cho, Sung-Min, Kim, Jin-Su, Kim, Jae-Chul
Format: Article
Language:English
Subjects:
Algorithms
Calendars
Computer simulation
Degradation
degradation model
Economic conditions
Electric power
Electric power distribution
Electric power generation
Electric power systems
electrical energy storage
Electricity
Electricity distribution
Energy
Energy storage
frequency regulation
Generators
Life span
Lithium
lithium-ion battery
Objective function
Parameter estimation
Regulation
Studies
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Summary:This study proposes a method for optimally selecting the operating parameters of an energy storage system (ESS) for frequency regulation (FR) in an electric power system. First, the method allows the optimal objective function of the selected parameters to be set in a flexible manner according to the electric market environment. The objective functions are defined so that they could be used under a variety of electricity market conditions. Second, evaluation frequencies are created in order to simulate the overall lifespan of the FR-ESS. Third, calendar and cycle degradation models are applied to the battery degradation, and are incorporated into evaluations of the degradation progress during the entire FR-ESS lifespan to obtain more accurate results. A calendar life limit is set, and the limit is also considered in the objective function evaluations. Fourth, an optimal parameter calculation algorithm, which uses the branch-and-bound method, is proposed to calculate the optimal parameters. A case study analyzes the convergence of the proposed algorithm and the results of the algorithm under various conditions. The results confirmed that the proposed algorithm yields optimal parameters that are appropriate according to the objective function and lifespan conditions. We anticipate that the proposed FR-ESS algorithm will be beneficial in establishing optimal operating strategies.
ISSN:1996-1073
1996-1073
DOI:10.3390/en12091782