Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm

doi:10.11930/j.issn.1004-9649.202201065

Abstract

Abstract: As demands on smoothing the output fluctuation of offshore wind power increase, this paper proposes an optimal configuration method for offshore wind power storage. The wavelet packet decomposition algorithm is used to process the output curve of the wind power, and an annual power response curve of the power storage system is obtained. In addition, the paper adopts an improved scene clustering algorithm combining a cloud model with a fuzzy c-means clustering algorithm to aggregate the annual power response curve and generate typical scenes of the power response. Furthermore, to minimize the annual comprehensive cost of the power storage, the paper constructs an optimal configuration model for offshore wind power storage and uses the particle swarm optimization algorithm to solve the optimal configuration model. Finally, the proposed method and model are analyzed and verified by typical examples. The results show that the proposed model and method can comprehensively consider the actual operating characteristics of the power storage system on the side of offshore wind farms and effectively guide the power storage configuration and construction planning of offshore wind farms.

Key words: offshore wind power, wavelet packet decomposition, scene clustering, particle swarm optimization algorithm, energy storage configuration

YI Jingui, ZHU Ziwei, XIE Qing. Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm[J]. Electric Power, 2022, 55(12): 2-10.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202201065

https://www.electricpower.com.cn/EN/Y2022/V55/I12/2

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