@inproceedings{e788a39b267d4a248a9dbba60a1ced1c,
title = "Electric Vehicle Charging Scheduling Algorithm Based on Online Multi-objective Optimization",
abstract = "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.",
keywords = "Chargingscheduling, Electric vehicle, Internet of things, Multi-objectiveoptimization, New energy",
author = "Tao Hong and Jihan Cao and Weiting Zhao and Mingshu Lu",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 17th IEEE International Wireless Communications and Mobile Computing, IWCMC 2021 ; Conference date: 28-06-2021 Through 02-07-2021",
year = "2021",
doi = "10.1109/IWCMC51323.2021.9498595",
language = "英语",
series = "2021 International Wireless Communications and Mobile Computing, IWCMC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1141--1146",
booktitle = "2021 International Wireless Communications and Mobile Computing, IWCMC 2021",
address = "美国",
}