基于供需特征的充电基础设施选址–路径–分配协同优化研究

Research on Collaborative Optimization of LocationRoutingAllocation for Charging Infrastructure Based on SupplyDemand Characteristics

摘要: 针对城市充电设施利用率不均、局部排队与闲置并存的供需错配问题，构建综合考虑车辆续航可达性、站点容量及需求满足水平的混合整数线性规划模型，实现充电设施选址、路径选择与负荷分配协同优化。以设施建设、车辆出行及充电服务加权总成本最小化为目标，通过多模型对比与灵敏度分析验证模型有效性。结果表明，最优方案建设6座充电站，需求满足率达97.4%；相比需求密度优先法，充电服务成本和系统总成本分别降低17.1%和3.1%；相比容量约束选址、p-median及最大覆盖模型，系统总成本分别降低2.0%、6.9%和7.2%。研究表明，协同优化能够有效改善充电设施供需匹配，提高充电网络整体运行效率。

Abstract: To address the uneven utilization and supply-demand mismatch of urban electric vehicle charging facilities, a mixed-integer linear programming model is developed to jointly optimize station location, route selection, and charging load allocation under driving range, station capacity, and demand satisfaction constraints. The model minimizes the weighted total cost of construction, travel, and charging services. Comparative and sensitivity analyses demonstrate their effectiveness. Results show that the optimal solution deploys six charging stations with a demand satisfaction rate of 97.4%. Compared with the demand-density priority method, charging service costs and total system costs decrease by 17.1% and 3.1%, respectively. Total costs are further reduced by 2.0%, 6.9%, and 7.2% compared with the capacitated location, p-median, and maximal covering models, respectively. The proposed approach improves supply-demand matching and overall charging network efficiency.