Locating and Sizing Electric Vehicle Chargers Considering Multiple Technologies

被引:6
|
作者
Schettini, Tommaso [1 ]
dell'Amico, Mauro [2 ]
Fumero, Francesca [3 ]
Jabali, Ola [4 ]
Malucelli, Federico [4 ]
机构
[1] HEC Montreal, Ecole Technol Super, GERAD, Montreal, PQ H3T 2A7, Canada
[2] Univ Modena & Reggio Emilia, Dept Sci & Methods Engn, I-42122 Modena, Italy
[3] Politecn Milan, Dipartimento Ingn Gestionale, I-20133 Milan, Italy
[4] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, I-20133 Milan, Italy
关键词
charging station location; charging infrastructure planning; electric vehicles; facility location; CHARGING STATIONS; OPTIMIZATION; MODEL;
D O I
10.3390/en16104186
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In order to foster electric vehicle (EV) adoption rates, the availability of a pervasive and efficient charging network is a crucial requirement. In this paper, we provide a decision support tool for helping policymakers to locate and size EV charging stations. We consider a multi-year planning horizon, taking into account different charging technologies and different time periods (day and night). Accounting for these features, we propose an optimization model that minimizes total investment costs while ensuring a predetermined adequate level of demand coverage. In particular, the setup of charging stations is optimized every year, allowing for an increase in the number of chargers installed at charging stations set up in previous years. We have developed a tailored heuristic algorithm for the resulting problem. We validated our algorithm using case study instances based on the village of Gardone Val Trompia (Italy), the city of Barcelona (Spain), and the country of Luxembourg. Despite the variability in the sizes of the considered instances, our algorithm consistently provided high-quality results in short computational times, when compared to a commercial MILP solver. Produced solutions achieved optimality gaps within 7.5% in less than 90 s, often achieving computational times of less than 5 s.
引用
收藏
页数:16
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