Congestion Probability Balanced Electric Vehicle Charging Strategy in Smart Grid

被引:0
|
作者
Tang, Qiang [1 ,2 ]
Yang, Kun [3 ]
Luo, Yuan-sheng [1 ,2 ]
Liu, Yu-yan [4 ]
机构
[1] Changsha Univ Sci & Technol, Hunan Prov Key Lab Intelligent Proc Big Data Tran, Changsha, Hunan, Peoples R China
[2] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha, Hunan, Peoples R China
[3] Univ Essex, Sch Comp Sci & Elect Engn, Colchester, Essex, England
[4] Changsha Univ Sci & Technol, Sch Econ & Managent, Changsha, Hunan, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Congestion probability; Charging cost; Voltage level; Electric vehicle; Smart grid; POWER-SYSTEMS; COORDINATION; ALGORITHM;
D O I
10.1007/978-3-319-61813-5_19
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a coordinated charging strategy CCCS (Charging Congestion probability based Charging Strategy) is proposed, which considers the congestion probabilities of the charging stations (CSs), the charging costs of the electric vehicles (EVs), the distance between EV and charging station and EV users' satisfactions. The coordinated charging issue is formulated as a convex optimization problem, which can be solved to get the distributed charging algorithms, based on which the communication system is further proposed. In order to illustrate the performance, we put forward three benchmarks. In the simulation, we combine the power grid i.e. MATPOWER and the charging module together to build the simulation platform. Simulation results show that CCCS performs well in terms of balancing the congestion probabilities, reducing charging costs, and mitigating the impacts on the power grid voltage.
引用
收藏
页码:192 / 201
页数:10
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