Electric Vehicle Charging Scheduling Algorithm Based on Online Multi-objective Optimization

被引:3
作者
Hong, Tao [1 ,2 ]
Cao, Jihan [2 ]
Zhao, Weiting [3 ]
Lu, Mingshu [4 ]
机构
[1] BUAA, Yunnan Innovat, Kunming, Yunnan, Peoples R China
[2] Beihang Univ, Sch Elect & Informat Engn, Beijing, Peoples R China
[3] State Grid Shandong Elect Power Co, Informat & Telecommun Co, Jinan, Peoples R China
[4] Univ Calif Irvine, Irvine, CA USA
来源
IWCMC 2021: 2021 17TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC) | 2021年
关键词
Internet of Things; new energy; electric vehicle; charging scheduling; multi-objective optimization; SDN;
D O I
10.1109/IWCMC51323.2021.9498595
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The volatility of green energy power generation and the randomness of electric vehicle's charging will affect the safe operation of the grid seriously. Therefore, the joint scheduling of green energy and electric vehicles is of great significance, however, the existing charging scheduling algorithms have problems such as the single optimization objective and the complex calculation. Applying the Internet of Things technology to the traditional power industry can improve the management level of the grid effectively. Based on the prediction of green energy power, this paper established the multi-objective optimization model for the joint scheduling of green energy and electric vehicles and designed an online charging scheduling algorithm. Then the charging behavior of electric vehicles in urban scenarios is analyzed, user's charging behavior simulation method based on Monte Carlo is designed, the effectiveness of the scheduling algorithm is verified by processing the simulation data.
引用
收藏
页码:1141 / 1146
页数:6
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