调度(生产过程)
计算
网格
地铁列车时刻表
计算机科学
拓扑(电路)
控制理论(社会学)
电气工程
算法
数学优化
工程类
数学
几何学
操作系统
控制(管理)
人工智能
作者
Nanduni Nimalsiri,Elizabeth L. Ratnam,David B. Smith,Chathurika P. Mediwaththe,Saman Halgamuge
出处
期刊:IEEE Transactions on Intelligent Transportation Systems
[Institute of Electrical and Electronics Engineers]
日期:2022-07-01
卷期号:23 (7): 7653-7665
被引量:31
标识
DOI:10.1109/tits.2021.3071686
摘要
In this paper, we propose two decentralized Electric Vehicle (EV) charge scheduling schemes for shaping the load curve of residential communities connected to the electric grid. The first scheme is designed for Coordinated Valley-Filling (C-VF) of the load curve via only EV charging. The second scheme is designed for Coordinated Valley-Filling and Peak-Shaving (C-VF-PS) of the load curve via both EV charging and discharging. In both schemes, a set of grid-connected EVs referred to as an ‘EV Group’ (EVG) coordinates their charge (and discharge) schedules by means of an iterative routine. Specifically, at each iteration of the respective routine, each EV in the EVG updates its charge (and discharge) schedule using a water-filling based algorithm that is specifically tailored for load curve shaping. To accommodate heterogeneous EV arrival times, which are often non-deterministic, each of C-VF and C-VF-PS is implemented in two methods, which differ in the way the EVG is formed. The first method requires all the grid-connected EVs to reschedule at designated time intervals, whereas the second method requires each EV to schedule only once, yielding lower computation and communication overheads. Numerical simulation results confirm that, compared to uncoordinated EV charging, C-VF and C-VF-PS reduce the load variance (flattens the load curve) by 47% and 65%, respectively. Furthermore, Method 2 is shown to be more effective than Method 1, in terms of computation and communication overheads.
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