Capacity Optimization Configuration of Hybrid Energy Storage System Considering Energy Storage Response Characteristics

With the continuous increase in the scale of new energy installations and their grid integration, the inherent randomness and volatility of new sources exacerbate grid frequency deviations and increase regulation pressure, posing a serious threat to system stability, security, and economic operation. To address this issue, this paper proposes a capacity optimization configuration strategy for hybrid energy storage systems (HESSs) that accounts for energy storage response characteristics and wind power fluctuation smoothing requirements. The method employs a HESS composed of advanced adiabatic compressed air energy storage (AA-CAES) and electrochemical energy storage. First, the input power of the HESS is decomposed using variational mode decomposition (VMD). To reduce the impact of mode mixing on the accuracy of power decomposition, the parameters of the VMD algorithm are optimized using a differential evolution (DE) algorithm. Next, based on the response speed of AA-CAES, preliminary allocation boundaries are defined. Further, a secondary allocation of the hybrid energy storage power is performed with the goal of minimizing the comprehensive cost of the system. Finally, the proposed method is validated through case simulations. The results show that the proposed method reduces mode mixing during power decomposition, achieves reasonable power allocation among different energy storage systems, leverages the operational characteristics of various energy storage components, smooths wind power fluctuations, optimizes the capacity configuration of the HESS, and enhances the economic efficiency.