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Energy Storage Capacity Planning Method for Improving Offshore Wind Power Consumption

Author

Listed:
  • Hao Yu

    (Grid Planning & Research Center of Guangdong Power Grid Co., Ltd., Guangzhou 510060, China)

  • Xiaojuan Yang

    (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Honglin Chen

    (Grid Planning & Research Center of Guangdong Power Grid Co., Ltd., Guangzhou 510060, China)

  • Suhua Lou

    (School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yong Lin

    (Grid Planning & Research Center of Guangdong Power Grid Co., Ltd., Guangzhou 510060, China)

Abstract

This paper proposes a method of energy storage capacity planning for improving offshore wind power consumption. Firstly, an optimization model of offshore wind power storage capacity planning is established, which takes into account the annual load development demand, the uncertainty of offshore wind power, various types of power sources and line structure. The model aims at the lowest cost of investment, operation and maintenance of the system, and takes lower than a certain abandoned wind level as the strict constraint to obtain two parameters of power capacity and energy capacity of energy storage on the source side. Secondly, taking a coastal power grid as a typical case, the energy storage capacity planning method is verified. Finally, the key factors affecting offshore wind power consumption are summarized, and the sensitivity analysis is carried out from the point of view of the transmission protocol of the transmission lines outside the province and the capacity allocation of the tie lines in the province. This study will be helpful for the planning and operation of the high-proportion of offshore wind energy power systems.

Suggested Citation

  • Hao Yu & Xiaojuan Yang & Honglin Chen & Suhua Lou & Yong Lin, 2022. "Energy Storage Capacity Planning Method for Improving Offshore Wind Power Consumption," Sustainability, MDPI, vol. 14(21), pages 1-15, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14589-:d:964821
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    Citations

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    Cited by:

    1. Zhaonian Ye & Yongzhen Wang & Kai Han & Changlu Zhao & Juntao Han & Yilin Zhu, 2023. "Bi-Objective Optimization and Emergy Analysis of Multi-Distributed Energy System Considering Shared Energy Storage," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    2. Jian Yang & Jichang Dong & Suixiang Gao & Guoqing Wang, 2023. "Blockchain-Based Long-Term Capacity Planning for Semiconductor Supply Chain Manufacturers," Sustainability, MDPI, vol. 15(6), pages 1-20, March.

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