Paper Info
Title
Decentralised online charging scheduling for large populations of electric vehicles: a cyber-physical system approach
Abstract
As the number of electric vehicles EVs grows, their electricity demands may have significant detrimental impacts on electric power grid when not scheduled properly. In this paper, we model an EV charging system as a cyber-physical system, and design a decentralised online EV charging scheduling algorithm for large populations of EVs, where the EVs can be highly heterogeneous and may join the charging system dynamically. The algorithm couples a clustering-based strategy that dynamically classifies heterogeneous EVs into multiple groups and a sliding-window iterative approach that schedules the charging demand for the EVs in each group in real time. Extensive simulation results demonstrate that our approach provides near-optimal solutions at significantly reduced complexity and communication overhead. It flattens the aggregated load on the power grid and reduces the costs of both the users and the utility.
Year
DOI
Venue
2013
10.1080/17445760.2012.658803
IJPEDS
Keywords
Field
DocType
large population,heterogeneous evs,scheduling algorithm,system dynamically,power grid,sliding-window iterative approach,algorithm couple,decentralised online,cyber-physical system,electric vehicles evs,cyber-physical system approach,electric power grid,decentralised online ev,sliding window,cyber physical systems,electric power,system dynamics,real time,scheduling
Electricity,Scheduling (computing),Computer science,Computer network,Power grid,Electric power grid,Cyber-physical system,Schedule,Cluster analysis,Vehicle-to-grid,Distributed computing
Journal
Volume
Issue
ISSN
28
1
1744-5760
Citations 
PageRank 
References 
8
0.80
3
Authors
4
Name
Order
Citations
PageRank
Ruofan Jin1988.27
Bing Wang228219.23
Peng Zhang3616.79
PeterB. Luh480.80