Optimal Electric Vehicle Fast Charging Station Placement Based on Game Theoretical Framework

被引:142
|
作者
Xiong, Yanhai [1 ]
Gan, Jiarui [2 ]
An, Bo [3 ]
Miao, Chunyan [3 ]
Bazzan, Ana L. C. [4 ]
机构
[1] Nanyang Technol Univ, Joint NTU UBC Res Ctr Excellence Act Living Elder, Interdisciplinary Grad Sch, Singapore 639798, Singapore
[2] Univ Oxford, Dept Comp Sci, Oxford OX1 2JD, England
[3] Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore 639798, Singapore
[4] Univ Fed Rio Grande do Sul, Inst Informat, BR-90040060 Porto Alegre, RS, Brazil
基金
新加坡国家研究基金会;
关键词
Electric vehicle charging station; congestion game; facility placement; CONGESTION; OPTIMIZATION; IMPACT;
D O I
10.1109/TITS.2017.2754382
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
To reduce the air pollution and improve the energy efficiency, many countries and cities (e.g., Singapore) are on the way of introducing electric vehicles (EVs) to replace the vehicles serving in current traffic system. Effective placement of charging stations is essential for the rapid development of EVs, because it is necessary for providing convenience for EVs and ensuring the efficiency of the traffic network. However, existing works mostly concentrate on the mileage anxiety from EV users but ignore their strategic and competitive charging behaviors. To capture the competitive and strategic charging behaviors of the EV users, we consider that an EV user's charging cost, which is dependent on other EV users' choices, consists of the travel cost to access the charging station and the queuing cost in charging stations. First, we formulate the Charging Station Placement Problem (CSPP) as a bilevel optimization problem. Then, by exploiting the equilibrium of the EV charging game, we convert the bilevel optimization problem to a single-level one, following which we analyze the properties of CSPP and propose an algorithm Optimizing eleCtric vEhicle chArging statioN (OCEAN) to compute the optimal allocation of charging stations. Due to OCEAN's scalability issue, we furthermore present a heuristic algorithm OCEAN with Continuous variables to deal with large-scale real-world problems. Finally, we demonstrate and discuss the results of the extensive experiments we did. It is shown that our approach outperform baseline methods significantly.
引用
收藏
页码:2493 / 2504
页数:12
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