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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摘要

为了解决混合储能系统（Hybrid Energy Storage System,HESS）功率分配时因模态混叠导致功率分配不精确、储能系统成本过高的问题,提出一种多次滑动均值滤波（Multiple Moving Average Filtering,MMAF）的功率分配方法用于削弱模态混叠现象,降低混合储能成本。首先,获取了满足平抑要求的混合储能最小总功率指令,采用MMAF算法对其进行滤波,获得蓄电池与超级电容各自的功率指令。引入Pearson相关系数量化模态混叠现象,作为判断滤波次数和每次滤波滑窗大小的指标。将蓄电池和超级电容各自的功率指令作为储能定容的可行域,考虑电池荷电状态（State of Charge,SOC）约束求取储能适配的最小额定功率和额定容量。其次,基于等效运行时间建立了蓄电池全寿命周期量化模型,为经济性分析提供依据。最后,以改进的混合储能全寿命周期成本模型（Life Cycle Cost,LCC）验证了本文方法可以有效限制模态混叠,降低混合储能系统成本。

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关键词 ：混合储能, 功率分配, 模态混叠, MMAF算法, 蓄电池全寿命周期量化模型

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

收稿日期: 2022-12-21

PACS:

TM711

基金资助:

国家自然科学基金联合基金重点支持项目（U21A20485）

通讯作者: 张志禹男,1966年生,博士,教授,研究方向为电网信息处理与深度学习。E-mail：zhangzhiyu@xaut.edu.cn

作者简介: 田博文男,1997年生,硕士研究生,研究方向为新能源侧储能优化配置与控制。E-mail：932725835@qq.com

引用本文:

田博文, 张志禹, 杨梦飞. 基于MMAF的混合储能系统功率分配方法及定容研究[J]. 电工技术学报, 0, (): 136-136. Tian Bowen, Zhang Zhiyu, Yang Mengfei. Research on Power Distribution Method and Energy Storage System Planning of Hybrid Energy Storage Based on MMAF. Transactions of China Electrotechnical Society, 0, (): 136-136.

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

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