Mitigate the range anxiety: Siting battery charging stations for electric vehicle drivers

•A compact mixed-integer programming model is developed.•Path deviation and drivers’ range anxiety are considered.•An outer-approximation method is proposed to solve the model.•Numerical experiments in a real-life Texas highway network are conducted. This study addresses the location problem of elec...

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Bibliographic Details
Published in:Transportation research. Part C, Emerging technologies Vol. 114; pp. 164 - 188
Main Authors: Xu, Min, Yang, Hai, Wang, Shuaian
Format: Journal Article
Language:English
Published: Elsevier Ltd 01.05.2020
Subjects:
Compact formulation
EV charging station location
Outer-approximation algorithm
Path deviation
Range anxiety
EV charging station location
Path deviation
Outer-approximation algorithm
Range anxiety
Compact formulation
ISSN:0968-090X, 1879-2359
Online Access:Get full text
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Summary:•A compact mixed-integer programming model is developed.•Path deviation and drivers’ range anxiety are considered.•An outer-approximation method is proposed to solve the model.•Numerical experiments in a real-life Texas highway network are conducted. This study addresses the location problem of electric vehicle charging stations considering drivers’ range anxiety and path deviation. The problem is to determine the optimal locations of EV charging stations in a network under a limited budget that minimize the accumulated range anxiety of concerned travelers over the entire trips. A compact mixed-integer nonlinear programming model is first developed for the problem without resorting to the path and detailed charging pattern pre-generation. After examining the convexity of the model, we propose an efficient outer-approximation method to obtain the ε-optimal solution to the model. The model is then extended to incorporate the charging impedance, e.g., the charging time and cost. Numerical experiments in a 25-node benchmark network and a real-life Texas highway network demonstrate the efficacy of the proposed models and solution method and analyze the impact of the battery capacity, path deviation tolerance, budget and the subset of OD pairs on the optimal solution and the performance of the system.
ISSN:0968-090X
1879-2359
DOI:10.1016/j.trc.2020.02.001