Online Charging Scheduling Algorithms of Electric Vehicles in Smart Grid: An Overview

被引:49
|
作者
Tang, Wanrong [1 ]
Bi, Suzhi [2 ]
Zhang, Ying Jun [1 ,3 ]
机构
[1] Chinese Univ Hong Kong, Dept Informat Engn, Ma Liu Shui, Hong Kong, Peoples R China
[2] Shenzhen Univ, Coll Informat Engn, Shenzhen, Guangdong, Peoples R China
[3] Chinese Univ Hong Kong, Shenzhen Res Inst, Ma Liu Shui, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
DEMAND; MODEL;
D O I
10.1109/MCOM.2016.1600346CM
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
As an environment-friendly substitute for conventional fuel-powered vehicles, EVs and their components have been widely developed and deployed worldwide. The large-scale integration of EVs into power grid brings both challenges and opportunities to the system performance. On one hand, the load demand from EV charging imposes a heavey impact on the stability and efficiency of power grid. On the other hand, EVs could potentially act as mobile energy storage systems to improve the power network performance, such as load flattening, fast frequency control, and facilitating renewable energy integration. Evidently, uncontrolled EV charging could lead to inefficient power network operation or even security issues. This has spurred on enormous research interest in designing charging coordination mechanisms. A key design challenge here lies in the lack of complete knowledge of events that occur in the future. Indeed, the amount of knowledge of future events significantly impacts the design of efficient charging control algorithms. This article focuses on introducing online EV charging scheduling techniques that deal with different degrees of uncertainty and randomness of future knowledge. In addition, we highlight the promising future research directions for EV charging control.
引用
收藏
页码:76 / 83
页数:8
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