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.