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Collaborative optimization of VRB-PS hybrid energy storage system for large-scale wind power grid integration

Author

Listed:
  • Li, Hongze
  • Sun, Dongyang
  • Li, Bingkang
  • Wang, Xuejie
  • Zhao, Yihang
  • Wei, Mengru
  • Dang, Xiaolu

Abstract

In order to achieve the carbon peak and neutrality goals, wind power in China has been vigorously developed. However, the random volatility and intermittence of wind power output may threaten the safe and stable operation of the power system. Energy storage, as a flexible resource, can play an important role in promoting the large-scale integration of wind power. In this paper, a two-stage collaborative optimization method for the Hybrid Energy Storage System (HESS) composed of Vanadium Redox flow Battery (VRB) and Pumped Storage (PS) is proposed. In the first stage, VRB is configured to suppress wind power output fluctuations, and in the second stage, a two-layer capacity configuration and operation optimization model for PS is developed to support the safe and economic operation of the system. Finally, the effectiveness of the proposed collaborative optimization method is verified. The simulation results show that the VRB can suppress high frequency fluctuations of wind power, and the PS can promote the wind power utilization rate and improves the economy, safety and flexibility of system operation, that is, the proposed HESS has better regulation ability and operating economy than the single energy storage.

Suggested Citation

  • Li, Hongze & Sun, Dongyang & Li, Bingkang & Wang, Xuejie & Zhao, Yihang & Wei, Mengru & Dang, Xiaolu, 2023. "Collaborative optimization of VRB-PS hybrid energy storage system for large-scale wind power grid integration," Energy, Elsevier, vol. 265(C).
    • Handle: RePEc:eee:energy:v:265:y:2023:i:c:s0360544222031784
    DOI: 10.1016/j.energy.2022.126292
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    2. Li, Xuehan & Wang, Wei & Ye, Lingling & Ren, Guorui & Fang, Fang & Liu, Jizhen & Chen, Zhe & Zhou, Qiang, 2024. "Improving frequency regulation ability for a wind-thermal power system by multi-objective optimized sliding mode control design," Energy, Elsevier, vol. 300(C).

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