Intelligent charging strategy for PHEVs in a parking station based on Multi-objective optimization in smart grid

被引:0
|
作者
Tong, Jingjing [1 ]
Zhao, Tianyang [1 ]
Yang, Xu [1 ]
Zhang, Jianhua [1 ]
机构
[1] North China Elect Power Univ, Sch Elect & Elect Engn, Beijing, Peoples R China
来源
2014 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO (ITEC) ASIA-PACIFIC 2014 | 2014年
关键词
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暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
With the increasing popularity of Plug-in Hybrid Electric Vehicles (PHEVs), the public charging infrastructure construction such as charging station and PHEV charging enabled parking station has also appeared. The problem of scheduling large-scale of PHEVs in such centralized charging infrastructure should be considered to avoid adverse effects on the power system because of their uncontrolled charging. For example, lots of PHEVs' charging simultaneously at period of peak-load may pose a wide pressure on the grid's peak regulation. In this paper, an intelligent charging strategy which can decide each PHEV's charging power at each time step is proposed for a cluster of PHEVs in a parking station based on time of use (TOU) price. A mathematic optimal model with the muti-objective function (i.e. minimizing the charging cost and minimizing load variance) is also given considering several constraints such as the chargers' power limit and charging efficiency. The proposed strategy only considers PHEVs as controllable load, but it's also applicable to situations where other controllable load are added in the future. In this paper, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the optimization problem and the matlab calculation results validate the effectiveness of the proposed strategy.
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页数:6
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