Hybrid Energy Storage Capacity Optimization Configuration for Wind Power Fluctuation Smoothing Based on GSWOA-VMD - Bao, Xuhong; Zhao, Bo; Zhang, Fang (Distributed Generation & Alternative Energy Journal, 2026)
To reduce the impact of wind power fluctuations on the power grid, this paper proposes a hybrid energy storage system (HESS) capacity optimization configuration method for wind power fluctuation smoothing. The method utilizes a Global Search Whale Optimization Algorithm (GSWOA) to optimize Variational Mode Decomposition (VMD) parameters. First, GSWOA determines the optimal parameter combination (K, α) for VMD. The optimized VMD then decomposes the wind power into a component suitable for direct grid integration and a component requiring smoothing. The smoothing-required component undergoes secondary allocation. Subsequently, an HESS capacity optimization model, considering system costs, is established. This approach achieves efficient wind power fluctuation smoothing and economically optimized operation of the HESS. Case study results demonstrate that the proposed method (GSWOA-VMD) offers superior calculation accuracy and convergence speed compared to alternatives. Furthermore, the HESS configuration exhibits a higher smoothing rate and lower comprehensive cost than single energy storage systems.