针对传统小波包风电波动平抑方法存在的过度平抑问题,提出一种基于时频分析的改进小波包平抑方法。首先,找出功率最大变化范围超过波动标准的时刻对集合,利用小波包对风电功率进行小波分解得到各频段分量;然后,从高频到低频依次对各频段分量在时刻对集合上进行局部削峰填谷,直到风电功率满足波动标准,从而得到平抑后的风电并网功率和储能功率指令;最后,对波动平抑效果进行评价。算例仿真表明该方法在满足风电波动标准的基础上,减小了储能功率指令的累积功率和充放电切换次数,有利于降低储能配置成本、延长储能寿命。
Abstract
Aiming at excessive smoothing in the traditional wavelet packet method to smooth wind power fluctuations, an improved wavelet packet smoothing method based on time-frequency analysis is proposed. Firstly, the set of time pairs when the maximum power-fluctuation range exceeds the fluctuation standard is found out; and the wavelet decomposition based on wavelet packet is performed on wind power to obtain its components in each frequency band. Secondly, starting from the highest frequency component, the local peak-shaving and valley-filling of the components are performed only at these time pairs until the fluctuation standard is satisfied, and thus the grid-connected wind power and energy storage power command are obtained. Finally, the effect of smoothing is evaluated. Results of the case study show that this method can reduce the cumulative power and the charging-discharging switching times of energy storage power command, thus helping reduce the cost of energy storage configuration and prolong the life of energy storage while meeting the standards of wind power fluctuations.
关键词
风电功率 /
储能 /
小波分解 /
时频分析 /
小波包 /
波动平抑
Key words
wind power /
energy storage /
wavelet decomposition /
time-frequency analysis /
wavelet packet /
fluctuation smoothing
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基金
新能源与储能运行控制国家重点实验室开放基金（NYB51201901203）; 中央高校基本科研业务费专项资金（PA2020GDSK0099）
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