为解决并网过程中，风电功率波动、间隙性等影响电网稳定运行的问题，提出一种利用经验模态分解（empirical mode decomposition, EMD）和变分模态分解（variational mode decomposition, VMD）结合的飞轮-锂电混合储能系统的容量优化配置方案。首先，采用K均值算法得到典型日数据，通过EMD将风电典型日数据输出功率信号分解为满足波动量限值的并网功率和混合储能平抑功率；然后，由麻雀搜索算法完成VMD算法中分解模态个数K值和二次惩罚因子α值的优化，通过VMD分解混合储能平抑功率，完成锂电池和飞轮储能的合理分配。最后，在考虑储能充放电功率和荷电状态约束条件的前提下，以储能成本为目标函数构建经济模型，采用青海省海南州共和县切吉敦曲风电场实际发电数据借助MATLAB平台进行仿真计算。结果表明：所提策略不仅有效地平抑了风电波动，还提高了整个系统的经济性。

In order to solve the problems of wind power fluctuations and intermittency during grid integration, which affect the stable operation of the power grid, a capacity optimization configuration scheme for a flywheel-lithium battery hybrid energy storage system was proposed. This scheme combined empirical mode decomposition (EMD) and variational mode decomposition (VMD). Firstly, typical daily data was obtained using the K-means algorithm, and EMD was applied to decompose the output power signal of these typical wind power daily data into grid-connected power that meets fluctuation limits and power that needs to be smoothed by the hybrid energy storage system. Then, the sparrow search algorithm was used to optimize the number of decomposition modes K and the quadratic penalty factor α in the VMD algorithm. By decomposing the power that needs smoothing using VMD, a reasonable allocation between lithium batteries and flywheel energy storage was achieved. Finally, considering the constraints of energy storage charging and discharging power and state of charge, an economic model was constructed with energy storage cost as the objective function. The actual power generation data of Qiejidunqu wind farm in Gonghe County, Hainan Prefecture, Qinghai Province were simulated and calculated by MATLAB platform. The results show that the proposed strategy not only effectively mitigates wind power fluctuations but also improves the overall economy of the system.