摘要
针对电动汽车保有量持续增长、充电设施匮乏难以满足用户需求的问题,提出一种基于GPS轨迹数据的电动出租车充电站选址规划方案。首先利用出租车GPS数据分析用户潜在充电需求并提取需求分布;其次提出一种基于网格密度分区的DBSCAN聚类方法,与传统算法相比DB指数由0.34降为0.30,对需求进行聚类和划分需求密集区,设置预选站址;最后,构建集合覆盖模型实现站址优化。利用此方案对北京大兴区出租车轨迹数据进行仿真,得出了合理的选址结果,即该方案可为电动出租车充电站规划提供参考。
A location planning scheme for electric taxi charging stations based on GPS trajectory data is proposed to address the problem of continuous growth in the number of electric vehicles and insufficient charging facilities to meet user needs.Firstly,the potential charging needs of users are analyzed using the taxi GPS data and demand distribution is extracted.Secondly,a DBSCAN clustering method based on the grid density partitioning is proposed,which reduces the DB index from 0.34 to 0.30 compared to traditional algorithms.The demand is clustered and divided into demand intensive areas,and pre-selected station locations are set.Finally,a set coverage model is developed to achieve site optimization.Using this scheme to simulate Daxing District,Beijing and taxi trajectory data,a reasonable site selection result is obtained,and the results can provide reference for the planning of electric taxi charging stations.
作者
任丹萍
王茜茜
陈湘国
邓玉静
REN Danping;WANG Xixi;CHEN Xiangguo;DENG Yujing(School of Information and Electrical Engineering,Hebei University of Engineering,Handan,Hebei 056038,China;Hebei Key Laboratory of Security Protection Information Sensing and Processing,Hebei University of Engineering,Handan,Hebei 056038,China)
出处
《河北工程大学学报(自然科学版)》
CAS
2024年第4期98-102,112,共6页
Journal of Hebei University of Engineering:Natural Science Edition
基金
河北省自然科学基金资助项目(F2022402007)。
关键词
充电站选址
电动出租车
GPS轨迹数据
密度聚类
charging station location
electric taxi
GPS trajectory data
density clustering