Abstract: Due to the significant economic costs associated with purchasing and maintaining photovoltaic power generation and energy storage equipment, as well as the challenges posed by insufficient sunlight under certain weather for the operation of PV hydrogen storage systems, this paper proposes an optimization method for the configuration of PV hydrogen storage systems based on a multi -objective improved grey wolf optimization(IGWO) algorithm. The system is modeled, and two types of energy storage devices are added to ensure stable operation of the system. The proposed IGWO algorithm uses chaos theory for population initialization, allowing for a more thorough search of the solution space. Lévy trajectory is used to disturb the update of the wolf pack positions to expand the search range, making it less likely for the algorithm to get trapped in local optima. A greedy strategy is used to update the positions of individuals. Taking the economic cost, penalty cost for curtailment, and electricity cost for purchase of PV hydrogen storage system as optimization objectives, the proposed optimization algorithm is used to solve the configuration capacity of the system components, aiming to minimize these costs. The results indicate that the IGWO algorithm is more effective than the original method in reducing the economic costs, curtailment, and purchasing costs of the PV hydrogen storage system.