基于MMAF的混合储能系统功率分配方法及定容研究

doi:10.19595/j.cnki.1000-6753.tces.222348

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Abstract

When the hybrid energy storage system (HESS) allocates power in the scenario of suppressing wind power fluctuations, the power distribution is inaccurate due to mode aliasing, which leads to the poor economy of the hybrid energy storage system. To address these issues,this paper suggests a method of multiple moving average filtering (MMAF) to decompose the total power command of hybrid energy storage.
Firstly, the minimum flat total power command of hybrid energy storage meeting the flat requirements was obtained, and the obtained total power command of hybrid energy storage was filtered through MMAF to make the battery respond to the filtered low frequency part and the supercapacitor respond to the high frequency part. Pearson correlation coefficient was used as the index to quantify modal aliasing, and Pearson correlation coefficient was used as the basis to determine the optimal filtering sliding window size and the optimal filtering times to ensure that the maximum limit of modal aliasing can be achieved under the sliding window size and filtering times. Taked the power command of the battery and the supercapacitor as the feasible region of the energy storage capacity, the minimum rated power and rated capacity of the hybrid energy storage system can be determined by comprehensively considering the battery state of charge (SOC) constraints. Secondly, based on the equivalent operating time, a quantitative model of battery life cycle was established, which provided a basis for the economic analysis of hybrid energy storage system. The cumulative effect of battery charging and discharging on its life loss was considered in the model, and the actual number of battery cycles was converted into the equivalent number of cycles at the rated discharge depth. Finally, the incremental factor of battery maintenance cost was introduced into the hybrid energy storage life cycle cost model (LCC) to describe the nonlinear increase of maintenance cost caused by the cumulative effect of battery aging every ten years, so as to better conform to the actual operation of the energy storage battery and improve the practicability of the LCC model. The effectiveness of the proposed method to reduce the comprehensive cost of hybrid energy storage was verified by simulation experiments.
According to the actual simulation experiment, the method in this paper can well smooth the power fluctuation of wind power grid connection, made it meet the grid connection requirements, and the hybrid energy storage configuration result was better than other configuration methods. The simulation results under different working conditions showed that MMAF method can ensure the battery operation life during power distribution, and can minimize the mode aliasing phenomenon and reduce the comprehensive cost of hybrid energy storage. Under normal working conditions, the LCC of MMAF was reduced by 87.6% compared with the empirical mode decomposition method (EMD); Compared with the variational mode decomposition method (VMD), the LCC of MMAF was reduced by 3.3%; Compared with the wavelet transform (WT) method, the LCC of MMAF was reduced by 56.8%. In case of failure, the battery and supercapacitor form a standby working mode for each other. The total power command of mixed energy storage was redistributed by MMAF method, which avoided the situation that the power command cannot respond due to battery failure, curbs the possibility of wind turbine disconnection, and avoided greater economic losses.

Key words： Hybrid energy storage power distribution mode aliasing MMAF algorithm quantitative model of battery life cycle

Received: 21 December 2022

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TM711

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	Tian Bowen
	Zhang Zhiyu
	Yang Mengfei

Cite this article:

Tian Bowen,Zhang Zhiyu,Yang Mengfei. Research on Power Distribution Method and Energy Storage System Planning of Hybrid Energy Storage Based on MMAF[J]. Transactions of China Electrotechnical Society, 0, (): 136-136.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.222348 OR https://dgjsxb.ces-transaction.com/EN/Y0/V/I/136

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