对于光储充电站而言，光伏、储能及充电站的优化配置是影响充电站经济性的重要因素。首先，对一天内充电站的电动汽车充电情况进行模拟，得到充电站单日充电曲线；然后，根据某地光伏出力的特性并结合分时电价，综合考虑投资方和用户侧因素，提出以总社会成本最小为目标函数，装置利用率、排队时间等为约束条件的光储充电站容量优化配置模型，并采用量子粒子群算法进行求解，对充电站加设的光伏和储能容量进行配置，基于排队理论得到系统的各个运行指标；最后，从各项成本随容量变化的趋势等多个角度验证配置结果的合理性。计算和算例分析表明，所提出的方法能实现光伏、储能及充电桩容量的合理配置，从而有效减少充电站在峰时段从电网的购电量，提高充电站运行的经济性。

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.