Capacity Optimization Configuration of Hybrid Energy Storage System Using a Modified Grey Wolf Optimization

Aiming at the randomness and intermittent characteristics of renewable energy power generation, a capacity optimization method of a hybrid energy storage system is proposed to ensure the economical and reliable operation of wind and solar power supply systems. The optimization method takes the minimum life cycle cost of the hybrid energy storage system as the optimization goal, takes the load power shortage rate and the energy storage capacity as the constraints, and establishes the optimal configuration model of the hybrid energy storage capacity. Based on this model, the modified gray wolf algorithm (MGWO) is used to solve the optimal capacity configuration of the hybrid energy storage system. Finally, the optimization results of MGWO are compared with the basic GWO and particle swarm algorithm (GWO) through a numerical example, and it is verified that MGWO can configure the hybrid energy storage capacity more reasonably.