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Implementation of Distributed Autonomous Control Based Battery Energy Storage System for Frequency Regulation

Author

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  • Hyung-Seung Kim

    (OCI Power Co. Ltd., Jung-gu, Seoul 04532, Korea
    Department Electrical Engineering, Myongji University, Yongin-si 17058, Korea)

  • Junho Hong

    (Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI 48128, USA)

  • In-Sun Choi

    (OCI Power Co. Ltd., Jung-gu, Seoul 04532, Korea)

Abstract

It has been mandated that 5% of the generation capacity of conventional fossil fuel power plants shall be used exclusively for frequency regulation (FR) purposes in South Korea. However, the rotational speed of generators cannot be controlled quickly, and thus the variation in the power generation for FR takes some time. Even during this short period of time, frequency fluctuations may occur, and the frequency may be out of range of its reference value. In order to overcome the limitations of the existing FR method, 374 MW (103 MWh) battery energy storage systems (BESSs) for FR have been installed and are in operation at 13 sites in South Korea. When designing the capacity of BESS for FR, three key factors, i.e., the deployment time, duration of delivery, and end of delivery, are considered. When these times can be reduced, the required capacity for BESS installation can be decreased, achieving the same operational effects with minimal investment in the facilities. However, because a BESS for FR (FR BESS) needs to be installed under a large capacity, providing a single output, a centralized control method is employed. The centralized control method has the advantage of being able to view and check the entire system at once, although in the case of FR BESS, a novel system design that can optimize the above three factors through a faster and more accurate control is required. Therefore, this paper proposes the implementation of a distributed autonomous control-based BESS for frequency regulation. For the proposed FR BESS, the central control system is responsible for the determination of external factors, e.g., power generation/demand forecasting; and the system is designed such that the optimal control method of renewable energy sources and BESS according to real-time frequency variations during practical operation is determined and operated using a distributed autonomous control method. Furthermore, this study was verified through the simulation that the proposed distributed autonomous control method conducts FR faster than an FR BESS with conventional centralized control, leading to an increase in the FR success rate, and a decrease in the deployment time required (e.g., 200 ms).

Suggested Citation

  • Hyung-Seung Kim & Junho Hong & In-Sun Choi, 2021. "Implementation of Distributed Autonomous Control Based Battery Energy Storage System for Frequency Regulation," Energies, MDPI, vol. 14(9), pages 1-19, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:9:p:2672-:d:549710
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    References listed on IDEAS

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    1. Houfei Lin & Jianxin Jin & Qidai Lin & Bo Li & Chengzhi Wei & Wenfa Kang & Minyou Chen, 2019. "Distributed Settlement of Frequency Regulation Based on a Battery Energy Storage System," Energies, MDPI, vol. 12(1), pages 1-17, January.
    2. Roberto Benato & Sebastian Dambone Sessa & Maura Musio & Francesco Palone & Rosario Maria Polito, 2018. "Italian Experience on Electrical Storage Ageing for Primary Frequency Regulation," Energies, MDPI, vol. 11(8), pages 1-12, August.
    3. 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.
    4. Andrew Ly & Saeid Bashash, 2020. "Fast Transactive Control for Frequency Regulation in Smart Grids with Demand Response and Energy Storage," Energies, MDPI, vol. 13(18), pages 1-23, September.
    5. Michael Schimpe & Christian Piesch & Holger C. Hesse & Julian Paß & Stefan Ritter & Andreas Jossen, 2018. "Power Flow Distribution Strategy for Improved Power Electronics Energy Efficiency in Battery Storage Systems: Development and Implementation in a Utility-Scale System," Energies, MDPI, vol. 11(3), pages 1-17, March.
    6. Minhan Yoon & Jaehyeong Lee & Sungyoon Song & Yeontae Yoo & Gilsoo Jang & Seungmin Jung & Sungchul Hwang, 2019. "Utilization of Energy Storage System for Frequency Regulation in Large-Scale Transmission System," Energies, MDPI, vol. 12(20), pages 1-13, October.
    7. Sung-Min Cho & Sang-Yun Yun, 2017. "Optimal Power Assignment of Energy Storage Systems to Improve the Energy Storage Efficiency for Frequency Regulation," Energies, MDPI, vol. 10(12), pages 1-13, December.
    8. Natascia Andrenacci & Elio Chiodo & Davide Lauria & Fabio Mottola, 2018. "Life Cycle Estimation of Battery Energy Storage Systems for Primary Frequency Regulation," Energies, MDPI, vol. 11(12), pages 1-24, November.
    9. Jin-Sun Yang & Jin-Young Choi & Geon-Ho An & Young-Jun Choi & Myoung-Hoe Kim & Dong-Jun Won, 2016. "Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation," Energies, MDPI, vol. 9(12), pages 1-13, November.
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    Cited by:

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    2. Gustavo Adolfo Gómez-Ramírez & Carlos Meza & Gonzalo Mora-Jiménez & José Rodrigo Rojas Morales & Luis García-Santander, 2023. "The Central American Power System: Achievements, Challenges, and Opportunities for a Green Transition," Energies, MDPI, vol. 16(11), pages 1-20, May.

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