Optimal Electric Vehicle Charging Station Placement

被引:0
|
作者
Xiong, Yanhai [1 ]
Gan, Jiarui [2 ,3 ]
An, Bo [4 ]
Miao, Chunyan [4 ]
Bazzan, Ana L. C. [5 ]
机构
[1] Nanyang Technol Univ, Joint NTU UBC Res Ctr Excellence Act Living Elder, Singapore, Singapore
[2] Chinese Acad Sci, Key Lab Intelligent Informat Proc, ICT, Beijing, Peoples R China
[3] Univ Chinese Acad Sci, Beijing, Peoples R China
[4] Nanyang Technol Univ, Sch Comp Engn, Singapore, Singapore
[5] Univ Fed Rio Grande do Sul, Porto Alegre, RS, Brazil
基金
新加坡国家研究基金会;
关键词
CONGESTION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Many countries like Singapore are planning to introduce Electric Vehicles (EVs) to replace traditional vehicles to reduce air pollution and improve energy efficiency. The rapid development of EVs calls for efficient deployment of charging stations both for the convenience of EVs and maintaining the efficiency of the road network. Unfortunately, existing work makes unrealistic assumption on EV drivers' charging behaviors and focus on the limited mobility of EVs. This paper studies the Charging Station PLacement (CSPL) problem, and takes into consideration 1) EV drivers' strategic behaviors to minimize their charging cost, and 2) the mutual impact of EV drivers' strategies on the traffic conditions of the road network and service quality of charging stations. We first formulate the CSPL problem as a bilevel optimization problem, which is subsequently converted to a single-level optimization problem by exploiting structures of the EV charging game. Properties of CSPL problem are analyzed and an algorithm called OCEAN is proposed to compute the optimal allocation of charging stations. We further propose a heuristic algorithm OCEAN-C to speed up OCEAN. Experimental results show that the proposed algorithms significantly outperform baseline methods.
引用
收藏
页码:2662 / 2668
页数:7
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