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Optimal Operation Parameter Estimation of Energy Storage for Frequency Regulation

Author

Listed:
  • Sung-Min Cho

    (Korea Electric Power Research Institute (KEPRI), Korea Electric Power Company (KEPCO), 105 Munji-Ro, Yuseong-gu, Daejeon 34056, Korea)

  • Jin-Su Kim

    (Department of Electrical Engineering, Soongsil University, 369, Sangdo-ro Dongjak-gu, Seoul 06978, Korea)

  • Jae-Chul Kim

    (Department of Electrical Engineering, Soongsil University, 369, Sangdo-ro Dongjak-gu, Seoul 06978, Korea)

Abstract

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.

Suggested Citation

  • Sung-Min Cho & Jin-Su Kim & Jae-Chul Kim, 2019. "Optimal Operation Parameter Estimation of Energy Storage for Frequency Regulation," Energies, MDPI, vol. 12(9), pages 1-21, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1782-:d:230088
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    References listed on IDEAS

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    Cited by:

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    3. Yingjie Zhou & Qibin Li & Qiang Wang, 2019. "Energy Storage Analysis of UIO-66 and Water Mixed Nanofluids: An Experimental and Theoretical Study," Energies, MDPI, vol. 12(13), pages 1-9, June.

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