Electric bus charging station location selection problem with slow and fast charging

被引:4
作者
Gkiotsalitis, Konstantinos [1 ]
Rizopoulos, Dimitrios [1 ]
Merakou, Marilena [1 ]
Iliopoulou, Christina [2 ]
Liu, Tao [3 ,4 ]
Cats, Oded [5 ]
机构
[1] Natl Tech Univ Athens, Sch Civil Engn, Dept Transportat Planning & Engn, 9 Iroon Polytech Str,Zografou Campus, Athens 15780, Greece
[2] Univ Patras, Dept Civil Engn, Rion 26504, Greece
[3] Southwest Jiaotong Univ, Natl Engn Lab Integrated Transportat Big Data Appl, Chengdu 611756, Peoples R China
[4] Southwest Jiaotong Univ, Sch Transportat & Logist, Natl United Engn Lab Integrated & Intelligent Tran, Chengdu 611756, Peoples R China
[5] Delft Univ Technol, Fac Civil Engn & Geosci, Bldg 23,Stevinweg 1, NL-2628 CN Delft, Netherlands
关键词
Electric buses; Charging station location selection; Minimum deadheading; Charging time slots; Mixed-integer programming; INFRASTRUCTURE; OPTIMIZATION; NETWORK;
D O I
10.1016/j.apenergy.2024.125242
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
To facilitate the shift from conventional to electric buses, the required charging infrastructure must be deployed. This study models the charging station location selection problem for fixed-line public transport services consisting of electric buses. The model considers the deadheading time of electric buses between the final stop of their trip and the locations of the potential charging stations with the objective of minimizing vehicle running costs. The problem is solved at a strategic level; therefore, several parameters of day-to-day operations, such as deadheading distances, are included as aggregate data considering their average values. In addition, it considers different charger types (slow and fast), which are subject to a day-ahead scheduling of the charging sessions of the buses. The developed model is a mixed-integer nonlinear program, which is reformulated as a mixed-integer linear program and can be solved efficiently for large networks with more than 1940 bus trips and 336 charging installation options. The model is applied in the Athens metropolitan area, demonstrating its potential as a decision support tool for selecting charging station locations and charger types in large public transport networks.
引用
收藏
页数:16
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