Research on Residual Power Reconfiguration of Hybrid Energy Storage System Based on Microgrid

Abstract

In the photovoltaic hybrid energy storage microgrid system, in order to reduce the unreasonable value of decomposition mode number (K) and secondary penalty factor (a) in VMD affect the accuracy of system reconstruction power. A new intelligent algorithm called sooty tern optimization algorithm(STOA) is proposed for the K and a optimization analysis. The parameters of VMD are optimized by STOA to obtain the [K, a] optimal combination quickly and stably, and then the result is applied in VMD to decompose the residual power of microgrid system. So as to improve the coincidence degree between the reconstructed power and the original residual power signal and can allocate the residual power to hybrid energy storage system reasonably, which will be beneficial to optimize the initial power allocation and capacity allocation of hybrid energy storage. This paper analyzes the algorithm and compares it with the results of particle swarm optimization and gray wolf algorithm to verify the effectiveness and superiority of the method.