高阶统计量与小波包分解在风氢混合储能系统中的应用

APPLICATION OF HIGHER ORDER STATISTICS AND WAVELET PACKET DECOMPOSITION IN WIND HYDROGEN HYBRID ENERGY STORAGE SYSTEM

以平抑风电场有功功率波动为目标,利用小波包分解风功率信号得到功率波动超限分量,使用高阶统计量分析各个分量获取特征值,采用支持向量机对各个分量进行分类,得到风氢混合储能系统中需被超级电容吸收的高频波动部分和被制氢发电系统消纳的低频波动部分,构建风氢混合储能系统功率平滑控制策略。最后在仿真中通过与常规混合储能系统进行对比,得到该方法能够有效平抑风电场有功功率波动,平滑风功率曲线,研究结果可为电转气这一新型储能技术提供一定的参考。

In order to stabilize the wind power fluctuation,this paper proposed a method that using the wavelet packet to decompose the wind power signal to obtain the overrun component of power fluctuation,applying higher order statistics analysis to acquire the characteristic value of each component,classifying each the component by using support vector machine algorithm,obtaining the high and low frequency fluctuation component which needed to absorb respectively by using supercapacitor and hydrogen production and generation system in the wind hydrogen hybrid energy storage system, the power smoothing control strategy of wind hydrogen hybrid energy storage system is built.At last,The proposed method can stabilize the wind power fluctuation and smooth the wind power curve effectively,by comparing with the conventional hybrid energy storage system in the simulation,it provides a reference for the new energy storage technology of the Power to Gas.