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用于混合储能系统平抑功率波动的小波变换方法 被引量:40

Wavelet transform method for hybrid energy storage system smoothing power fluctuation
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摘要 由锂电池和超级电容组成的混合储能系统(HESS)被广泛用于平抑电力系统中的功率波动,将低频功率分量分配给锂电池发挥其能量优势,将高频功率分量分配给超级电容发挥其功率优势。小波变换具有多尺度分解能力,能够根据储能介质特性更加合理地分配波动功率。基于储能介质的等效时间,提出了量化储能介质频率特性的方法。小波基的选取和分解层数的优化是小波变换的2个关键因素,直接影响波动功率的分解结果。采用互相关系数之和兼顾HESS的高、低频功率分量,选取合适的小波基。建立了储能介质频率特性与小波变换分解层数的关系,用于优化分解层数。仿真结果表明所提方法能够充分发挥储能介质的自身优势。 HESS(Hybrid Energy Storage System)composed of lithium battery and supercapacitor is widely used to smooth the power fluctuation in power system.Low frequency power components are allocated to lithium batteries to give full play to their energy advantages,while high frequency power components are allocated to supercapacitors to give full play to their power advantages.Wavelet transform has the ability of multi-scale decomposition,which can allocate the fluctuating power more reasonably according to the characteristics of energy storage devices.Based on the equivalent time of energy storage device,a method to quantify the frequency characteristics of energy storage devices is proposed.The selection of wavelet basis and the optimization of decomposition level are two critical factors for wavelet transform,which directly affects the decomposition results of fluctuating power.The sum of correlation coefficients,which takes into account both the high and low frequency power components of HESS,is used to select the appropriate wavelet basis.Meanwhile,the relationship between the frequency characteristic of energy storage device and the decomposition level of wavelet transform is established to optimize the decomposition level.Simulative results show that the proposed method can take full advantages of energy storage devices.
作者 程龙 张方华 CHENG Long;ZHANG Fanghua(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)
出处 《电力自动化设备》 EI CSCD 北大核心 2021年第3期100-104,128,共6页 Electric Power Automation Equipment
基金 国家自然科学基金资助项目(51777094)。
关键词 混合储能系统 功率波动 频率特性 小波变换 分解层数 hybrid energy storage system power fluctuation frequency characteristics wavelet transform decomposition level
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