To address the instability of wind power caused by the randomness and intermittency of wind generation, as well as the challenges in power compensation by hybrid energy storage systems (HESSs), this paper proposes a state of charge (SOC) balancing control strategy based on Successive Variational Mode Decomposition and multi-fuzzy control. First, a consensus algorithm is used to enable communication between energy storage units to obtain the global average SOC. Then, the Secretary Bird Optimization Algorithm (SBOA) is applied to optimize the Successive Variational Mode Decomposition (SVMD) and Variational Mode Decomposition (VMD) for the initial allocation of wind power, resulting in the smoothing power for hybrid energy storage and the grid integration power. Finally, considering the deviation between the current SOC of the storage units and the global average SOC, dynamic partitioning is used for multi-fuzzy control to adjust the initial power allocation, achieving SOC balancing control. Simulations of the control strategy were conducted using Matlab/Simulink, and the results indicate that the proposed approach effectively smooths wind power fluctuations, achieving stable grid integration power. It enables the SOC of the HESS to quickly align with the global average SOC, preventing the HESS from entering unhealthy SOC regions.

To address the instability of wind power caused by the randomness and intermittency of wind generation, as well as the challenges in power compensation by Hybrid Energy Storage Systems (HESS), this paper proposes a State of Charge (SOC) balancing control strategy based on Successive Variational Mode Decomposition and multi-fuzzy control. First, a consensus algorithm is used to enable communication between energy storage units to obtain the global average SOC. Then, the Secretary Bird Optimization Algorithm (SBOA) is applied to optimize the Successive Variational Mode Decomposition (SVMD) and Variational Mode Decomposition (VMD) for the initial allocation of wind power, resulting in the smoothing power for hybrid energy storage and the grid integration power. Finally, considering the deviation between the current SOC of the storage units and the global average SOC, dynamic partitioning is used for multi-fuzzy control to adjust the initial power allocation, achieving SOC balancing control. Simulations of the control strategy were conducted using Matlab/Simulink, and the results indicate that the proposed approach effectively smooths wind power fluctuations, achieving stable grid integration power. It enables the SOC of the HESS to quickly align with the global average SOC, preventing the HESS from entering unhealthy SOC regions.