混合储能平抑风电波动的功率分配策略

Power Distribution Strategy of Hybrid Energy Storage to Stabilize Wind Power Fluctuations

为有效解决风电功率波动的问题,提出了一种基于自适应滑动平均算法与遗传算法-变分模态分解(GA-VMD)的混合储能系统风电并网控制策略。首先,根据风电并网波动标准采用自适应滑动平均算法得到混合储能功率。其次,运用遗传算法,以VMD模态分量的样本熵值为适应度函数,确定模态个数及惩罚因子的最优组合。最后,根据希尔伯特边际谱确定分界频率,低频功率与高频功率分别交由锂电池与超级电容进行平抑。算例分析表明,所提方法不仅能够合理对风电功率进行分解,而且能够实现混合储能功率最优分配,具有自适应性。

In order to effectively solve the problem of wind power fluctuation,a wind power grid-connected control strategy for hybrid energy storage system based on adaptive sliding average algorithm and genetic algorithm-variational modal decomposition(GA-VMD)is proposed.Firstly,the adaptive sliding average algorithm is used to get the hybrid energy storage power according to the wind power grid-connected fluctuation standard,and the hybrid energy storage power is obtained.Secondly,the genetic algorithm is used to determine the optimal combination of the number of modes and the penalty factor by taking the sample entropy of the VMD modal component as the fitness function.Finally,the demarcation frequency is determined according to hilbert's marginal spectrum,and the low-frequency power and high-frequency power are flattened by the lithium battery and the supercapacitorrespectively.The numerical analysis shows that the proposed method can not only reasonably decompose the wind power,but also achieve the optimal distribution of hybrid energy storage power,which is adaptive.