基于改进小波包方法的风电功率波动平抑

To address over-smoothing in traditional wavelet packet decomposition for wind power fluctuation suppression, this paper proposes an improved method introducing high-frequency attenuation coefficients. It identifies over-limit time intervals, decomposes power via wavelet packets, optimizes coefficients under constraints, and sequentially attenuates high-frequency components until dual-time-window fluctuation limits are met. Simulation shows reduced ESS cumulative charge/discharge and improved PCS output stability.

针对传统小波包分解在风电功率波动平抑过程中存在过度平抑的问题,在时频分析的基础上,引入高频分量的平抑系数,提出1种改进的小波包分解方法.首先,找出功率波动越限的时间集合,利用传统小波包分解得到各个频段的分量;其次,通过目标函数和约束条件确定最佳平抑系数,从最高频分量开始依次对越限时间集合内的功率分量进行平抑,直到满足2种时间窗口下的波动限制;最后,对平抑效果进行评价.经算例仿真分析,在不同场景中改进的小波包方法在满足波动限制的前提下,均可以降低储能的充放电累积量,并使储能的出力水平维持在较好的状态.