For photovoltaic-storage charging stations, the optimal configuration of photovoltaic (PV) systems, energy storage, and charging facilities is a crucial factor affecting the economic viability of the charging stations. First, a simulation of the electric vehicle charging situation at the stations over a day is conducted to obtain the daily charging curve. Then, based on the characteristics of PV output and considering time-of-use electricity pricing, considering both investor and user-side factors, a optimal configuration model for photovoltaic-storage charging stations is proposed. This model aims to minimize total social costs while constraining device utilization rates and queuing times. The quantum particle swarm algorithm is employed to solve this model, determining the configuration of additional PV and energy storage capacity for the charging stations and deriving various operational indicators based on queuing theory. Finally, the rationality of the configuration results is validated from multiple perspectives, including trends in costs as capacity change. Calculations and case analyses show that the proposed method can achieve a reasonable allocation of PV, energy storage, and charging facility capacity, thereby effectively reducing the amount of electricity purchased from the grid during peak periods and improving the economic efficiency of the charging stations.