电动汽车
计算机科学
网格
蒙特卡罗方法
调度(生产过程)
充电站
电网
汽车工程
数学优化
功率(物理)
工程类
数学
几何学
量子力学
统计
物理
作者
Ruoyu Jiang,Zhenyuan Zhang,Jian Li,Yuxin Zhang,Qi Huang
出处
期刊:2017 2nd International Conference on Power and Renewable Energy (ICPRE)
日期:2017-09-01
卷期号:: 823-827
被引量:19
标识
DOI:10.1109/icpre.2017.8390649
摘要
With the rapid growth of electric vehicles (EV), the uncoordinated charging will jeopardize the power grid. In order to reduce the impacts of the uncoordinated charging, in this paper, a multi-objective optimization algorithm based coordinated EVs charging strategy has been proposed, which considers both user level and system level benefits simultaneously. According to the actual driving pattern data of EV users, the charging demand of EVs is established by Monte Carlo method. On the basis of the difference for electrical charging cost on peak/valley of power grid, the charging patterns are refined by multi-objective optimization scheduling model. A case study also been provided on the paper to verify the effectiveness of the proposed method.
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