基于多源数据的充电站三阶段选址优化决策  

Three-stage Location Optimization Decision of Charging Station Based on Multi-source Data

作　　者：李永竞 裴文卉 LI Yongjing;PEI Wenhui(School of Information Science and Electrical Engineering,Shandong Jiaotong University,Jinan 250357,China)

机构地区：[1]山东交通学院信息科学与电气工程学院,山东济南250357

出　　处：《控制工程》2023年第9期1648-1657,共10页Control Engineering of China

基　　金：国家自然科学基金资助项目(61803230);山东省高等学校科技计划项目(J18KA348,J18KA330,J18KB144);山东省高校优秀青年创新团队支持计划项目(2019KJN023);山东省重点研发计划项目(2019GSF109076)。

摘　　要：为满足日益增长的充电需求,提出一种计及选址影响因素和建设成本的充电站三阶段规划方案,实现了选址评估-预选址-站点增扩的有机结合。第一阶段,通过多源数据对影响因素展开分析,利用层次分析法建立选址评价体系。第二阶段,从用户和企业的角度出发,建立以成本最小为目标的选址优化模型,同时,提出了一种改进的免疫粒子群优化(immune particle swarm optimization,IPSO)算法,用以实现解在空间范围内的自适应搜索。第三阶段,考虑到充电站的增扩问题,设计了一种利用Voronoi图确定新增站点的方法。最后,以某市为研究对象,通过仿真验证了所提模型的有效性与合理性,为充电站的科学选址提供了必要的决策参考。In order to meet the growing charging demand,a three-stage charging station planning scheme is proposed that considers both site selection influencing factors and construction costs.The scheme combines site evaluation,pre-site selection and station expansion.In the first stage,the analysis of influencing factors is carried out based on multi-source data,and the site selection evaluation system is established using analytic hierarchy process.In the second stage,a site selection optimization model with the objective of cost minimization is established from the perspective of users and enterprises.An improved immune particle swarm algorithm is also proposed to realize the adaptive search of the solution in the spatial range.In the third stage,considering the problem of increasing and expanding charging stations,a method is designed to determine the additional stations using Voronoi diagram.Finally,taking a city as the research object,the validity and rationality of the model are verified by simulation,which provides a necessary decision reference for the scientific location of the charging station.

关 键 词：充电站选址 免疫粒子群优化算法 VORONOI图 层次分析法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] U491.8[自动化与计算机技术—控制科学与工程]