基于鲁棒优化的电动汽车充电站点流融合选址模型OA北大核心CSSCICSTPCD

With the development of battery technology,the range of electric vehicles(EVs)has greatly increased.As a result,EV users choose to charge near their destination instead of on-route.It can be seen that the charging demand of EVs has formed a kind of node-demand-based,flow-demand-assisted comprehensive demand pattern.Therefore,it is very necessary to take both node-based and flow-based demand into account in the deployment of the fast-charging station,so that the facility layout can fully match the charging demand pattern and improve their utilization.By combining the set covering location model and flow capturing location model(FCLM),this paper proposes a node-flow fusion location model that can serve the comprehensive charging demand.Considering the uncertainty of charging demand,it uses robust optimization to minimize the total planning cost of charging facilities and takes into account the grid restrictions and capacity expansion costs of power equipment.It establishes a robust location model under uncertain demand and solves it by equivalent dual transformation.Finally,it conducts numerical analysis on two numerical experiments.The result demonstrates that compared with classic models,the node-flow fusion model proposed can effectively reduce the overall planning cost of charging facilities while fully covering different types of charging needs.