Abstract: Hydrogen energy storage plays a key role in effectively alleviating the consumption of renewable energy generation and meeting the diverse energy demands of users. It is of great significance to optimize the hydrogen energy storage capacity configuration. Therefore, an optimization model for hydrogen energy storage capacity configuration that considers both photovoltaic power generation demand and user energy demand is proposed. First, the hydrogen energy storage system is constructed, and its fundamental model is developed. Secondly, photovoltaic revenue and consumption are used to form the photovoltaic demand function, while the user demand function is formulated based on user costs and satisfaction. Subsequently, a multi-objective optimization model for hydrogen energy storage capacity configuration is constructed by integrating the hydrogen energy storage revenue. Thirdly, the logistic chaotic mapping is utilized to initialize the population. A nonlinear strategy is employed to update the convergence factor, and positions are updated based on fitness value weights. An improved multi-objective grey wolf optimization algorithm is used as the solution method for the hydrogen storage capacity configuration optimization model. Finally, the effectiveness and reliability of the proposed optimization model are verified through case studies and comparative analyses using different algorithms. The results demonstrate that the proposed model is capable of meeting the requirements of photovoltaic systems, hydrogen energy storage, and users, effectively balancing the interests of all parties and achieving collaborative optimization of the energy system.