Optimal Location of Electrical Vehicle Charging Stations With Both Self-and Valet-Charging Service

Tianyi Zhao, Na Li, Nan Kong, Xiaoqing Xie

科研成果: 期刊稿件期刊论文


The inconvenience of charging is one of the major concern for potential electric vehicle (EV) users. In addition to building more charging facilities, electric vehicle charging assistance service has emerged for making EV charging more convenient to customers. In this paper, we consider an optimal EV charging station location problem with two types of customers. One is ordinary self-charging customers whereas the other is customers using a new service mode called valet-charging. We formulate the problem via bi-level location optimization model, where the lower level problem is a game model that characterizes customers’ station choice behaviors. To solve the hard nonlinear mixed-integer optimization problem, we design an adaptive large neighbourhood search (ALNS) algorithm for the upper level problem and a construct-improve heuristic for the lower level problem. We conduct numerical experiments to justify the efficiency of our solution method. We also conduct a need-inspired case study to derive practical insights which will help EV charging assistant service providers make strategic decisions. <italic>Note to Practitioners</italic>—The convenience of charging service is one major concern for EVs. In China, NIO Inc., NETA AUTO, and FAW-Volkswagen have started to provide valet-charging service. Charging station location problem becomes complicated while taking this service into account. We believe our work develops an effective tool for charging station planners to analyze station locations as well as the impact of valet charging services.
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期刊IEEE Transactions on Automation Science and Engineering
已出版 - 2023


Adaptive large neighborhood searches;Behavioral science;Bi-level optimization;Capacity problems;Charging station;Electric vehicle charging;Location-capacity problem;Optimization method;Urban areas;Valet-charging;


  • SCIE


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