基于完备局部均值分解和相关分析的光伏发电侧电-氢混合储能优化配置

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Abstract Intermittency and volatility of photovoltaic output still have great influence on power grid. Space-time translation of electric power by energy storage device can improve the controllability of photovoltaic power generation and improve the quality of power supply. In this paper, the capacity configuration method of hybrid energy storage system (HESS) composed of battery, super capacitor and hydrogen energy is proposed. Firstly, the mathematical models of photovoltaic power station and energy storage system are established. The difference between the dispatching power of power station and the actual output power of photovoltaic power generation is taken as the reference power of HESS. High, medium and low frequency components of HESS reference power are determined by ensemble local mean decomposition (ELMD) and Pearson product moment correlation coefficient (PPMCC). Under the constraint of the state of charge (SOC) of the three energy storage devices, the power of super capacitor, hydrogen energy storage and battery is allocated successively. The battery cycle life is considered, and the battery damage model is incorporated into the life cycle cost (LCC) assessment system of HESS. Finally, through the simulation of the actual scheduling data of a photovoltaic power station in Matlab, it is proved that the method can effectively decompose and reconstruct the HESS power according to different working frequency bands, and the advantages of HESS relative to single energy storage in economy and technology are reflected.

Key words： solar power hybrid energy storage ensemble local mean decomposition (ELMD) correlation coefficient capacity configuration

Received: 20 June 2022

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	Articles by authors
	LIU Yuchen
	YAN Qunmin
	GUO Yang
	LIU Xinyu
	SANG Xingyong

Cite this article:

LIU Yuchen,YAN Qunmin,GUO Yang等. Optimal configuration of electricity-hydrogen hybrid energy storage on photovoltaic generation side based on ensemble local mean decomposition and correlation analysis[J]. Electrical Engineering, 2022, 23(11): 21-29.

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http://dqjs.cesmedia.cn/EN/Y2022/V23/I11/21

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