Due to the dangerous effects of fossil fuels, policymakers tend to substitute fossil-fuel-based vehicles with electric ones. Thus, the optimal design of a charging station network providing convenient access for the users is of great importance. This paper presents a two-stage stochastic programming model for the problem of locating charging stations in urban areas. Parking lots around the buildings which may be visited by people during the day are considered as potential locations for charger installation. The model determines the parking lots that should be equipped with chargers and the number as well as the type of chargers that must be placed in each parking lot considering the demand as an uncertain parameter. The proposed model is examined on the dataset of a midtown area, taken from the literature, and an efficient heuristic algorithm based on Benders decomposition is utilized to solve the model. The results indicate that the heuristic method can find a near-optimal solution (with the optimality gap of at most 0.05%) in a short time.

由于化石燃料的危险影响，政策制定者倾向于用电动汽车替代基于化石燃料的车辆。因此，为用户提供方便访问的充电站网络的最佳设计非常重要。针对城市地区充电站的位置问题，本文提出了一个两阶段的随机规划模型。人们白天可能会参观的建筑物周围的停车场被视为安装充电器的潜在地点。该模型将需求作为不确定参数，确定应该配备充电器的停车场以及每个停车场必须放置的充电器的数量和类型。所提出的模型在市中心地区的数据集中进行了研究，该数据取自文献，并利用基于Benders分解的高效启发式算法对该模型进行求解。结果表明，启发式方法可以在很短的时间内找到接近最优的解决方案（最优间隙最大为0.05％）。