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Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend

Author

Listed:
  • Wei Guo

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050023, China)

  • Wenyi Fan

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050023, China)

  • Yang Zhao

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050023, China)

  • Jiakun An

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050023, China)

  • Chunguang He

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050023, China)

  • Xiaomei Guo

    (School of Electrical Engineering, North China Electric Power University, Baoding 071000, China)

  • Yanan Qian

    (School of Electrical Engineering, North China Electric Power University, Baoding 071000, China)

  • Libo Ma

    (School of Electrical Engineering, North China Electric Power University, Baoding 071000, China)

  • Hongshan Zhao

    (School of Electrical Engineering, North China Electric Power University, Baoding 071000, China)

Abstract

For the optimal power distribution problem of battery energy storage power stations containing multiple energy storage units, a grouping control strategy considering the wind and solar power generation trend is proposed. Firstly, a state of charge (SOC) consistency algorithm based on multi-agent is proposed. The adaptive power distribution among the units started can be realized using this algorithm. Then, considering the trend of wind and solar power generation, a reasonable grouping control strategy is formulated. The grouping situation of the units is determined by using the probability distribution characteristics of energy storage charging and discharging, which reduces the number of charging and discharging conversions and extends the power station life. Finally, the actual data of a wind–solar energy storage microgrid is used to verify the method. The simulation results demonstrate that the proposed method has certain advantages in terms of control effect, SOC consistency, and extending the power station life.

Suggested Citation

  • Wei Guo & Wenyi Fan & Yang Zhao & Jiakun An & Chunguang He & Xiaomei Guo & Yanan Qian & Libo Ma & Hongshan Zhao, 2023. "Grouping Control Strategy for Battery Energy Storage Power Stations Considering the Wind and Solar Power Generation Trend," Energies, MDPI, vol. 16(4), pages 1-15, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1857-:d:1067257
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    References listed on IDEAS

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    1. Li, Guidan & Yang, Zhe & Li, Bin & Bi, Huakun, 2019. "Power allocation smoothing strategy for hybrid energy storage system based on Markov decision process," Applied Energy, Elsevier, vol. 241(C), pages 152-163.
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