DocumentCode
2740650
Title
Deadline scheduling for large scale charging of electric vehicles with renewable energy
Author
Chen, Shiyao ; Ji, Yuting ; Tong, Lang
Author_Institution
Sch. of Electr. & Comput. Eng., Cornell Univ., Ithaca, NY, USA
fYear
2012
fDate
17-20 June 2012
Firstpage
13
Lastpage
16
Abstract
The problem of scheduling for the large scale charging of electric vehicles with renewable sources is considered. A new online charging algorithm referred to as Threshold Admission with Greedy Scheduling (TAGS) is proposed by formulating the charging problem as one of deadline scheduling with admission control and variable charging capacities. TAGS has low computation cost and requires no prior knowledge on the distributions of arrival traffic, battery charging (service) time, and available energy from renewable sources. It has a reserve dispatch algorithm designed to compensate the intermittency of renewable sources. Performance of TAGS is compared with benchmark scheduling algorithms such as the Earliest Deadline First (EDF) and the First Come First Serve (FCFS) with aggressive and conservative reserve dispatch algorithms.
Keywords
battery powered vehicles; greedy algorithms; hybrid electric vehicles; load dispatching; renewable energy sources; scheduling; EDF; EV-PHEV charging; FCFS; TAGS; admission control; aggressive reserve dispatch algorithm; arrival traffic distributions; battery charging time; benchmark scheduling algorithms; conservative reserve dispatch algorithms; deadline scheduling; earliest deadline first; electric vehicle large scale charging; first come first serve; online charging algorithm; plug-in hybrid electric vehicles; renewable energy resources; threshold admission with greedy scheduling; variable charging capacity; Admission control; Optimal scheduling; Renewable energy resources; Schedules; Scheduling; Scheduling algorithms; EV/PHEV charging; deadline scheduling; demand response; renewable energy; smart grid;
fLanguage
English
Publisher
ieee
Conference_Titel
Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012 IEEE 7th
Conference_Location
Hoboken, NJ
ISSN
1551-2282
Print_ISBN
978-1-4673-1070-3
Type
conf
DOI
10.1109/SAM.2012.6250449
Filename
6250449
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