为了降低风电功率波动对电网的影响，提出一种基于蜉蝣算法（mayfly algorithm, MA）优化变分模态分解（variational mode decomposition, VMD）参数的混合储能系统（hybrid energy storage system, HESS）控制策略。首先，利用滑动平均算法确定满足并网标准的风电并网功率。然后，综合两个评价指标构建适应度函数，利用蜉蝣算法寻优确定VMD算法的最优参数；将最优参数带入VMD算法分解混合储能功率，实现混合储能功率的初次分配。最后，利用模糊控制优化储能设备的荷电状态（state of charge, SOC），修正超级电容器和锂电池的功率指令。结果表明，所提策略不仅能够自适应分解和合理分配混合储能功率，有效平抑风电功率波动；还能够保证储能设备的SOC维持在合理范围内，实现HESS安全稳定运行。

In order to mitigate the impact of wind power fluctuations on the power grid, a hybrid energy storage system (HESS) control strategy was proposed, which optimized the parameters of variational mode decomposition (VMD) using the mayfly algorithm(MA). Firstly, the sliding average algorithm was employed to determine the wind power grid connected power that met the grid standards. Then, a fitness function was constructed by combining two evaluation criteria, and the optimal parameters of the VMD algorithm were determined using the mayfly algorithm. The optimal parameters were then introduced into the VMD algorithm to decompose the hybrid energy storage power, realizing the initial allocation of the hybrid energy storage power. Finally, fuzzy control was utilized to optimize the state of charge (SOC) of the energy storage devices, adjusting the power commands of supercapacitors and lithium batteries. The results indicate that the proposed strategy not only enables adaptive decomposition and rational allocation of hybrid energy storage power, effectively mitigating wind power fluctuations but also ensures the SOC of the energy storage devices remains within a reasonable range, achieving safe and stable operation of the HESS.