Optimal Pricing for Efficient Electric Vehicle Charging Station Management

被引:0
作者
Xiong, Yanhai [1 ]
Gan, Jiarui [2 ]
An, Bo [2 ]
Miao, Chunyan [2 ]
Soh, Yeng Chai [3 ]
机构
[1] Nanyang Technol Univ, Joint NTU UBC Ctr Excellence Act Living Elderly, Singapore 639798, Singapore
[2] Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore
[3] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
来源
AAMAS'16: PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS & MULTIAGENT SYSTEMS | 2016年
基金
新加坡国家研究基金会;
关键词
Electric Vehicle; Charging Station; Pricing; Game Theory;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The rapid development of Electric Vehicles (EVs) seen in recent years has been drawing increasing attentions from the public, markets, decision-makers, and academia. Notwithstanding the progress, issues still remain. Because of the widely complained disadvantages of limited battery capacity and long charging time, charging convenience has become a top concern that greatly hinders the adoption of EVs. Specialized EV charging station, which provides more than 10 times faster charging speed than domestic charging, is therefore a critical element for successful EV promotion. While most existing researches focus on optimizing spatial placement of charging stations, they are inflexible and inefficient against rapidly changing urban structure and traffic pattern. Therefore, this paper approaches the management of EV charging stations from the pricing perspective as a more inflexible and adaptive complement to established charging station placement. In this paper, we build a realistic pricing model in consideration of residential travel pattern and EV drivers' self-interested charging behavior, traffic congestion, and operating expense of charging stations. We formulate the pricing problem as a mixed integer non-convex optimization problem, and propose a scalable algorithm to solve it. Experiments on both mock and real data are also conducted, which show scalability of our algorithm as well as our solution's significant improvement over existing approaches.
引用
收藏
页码:749 / 757
页数:9
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