DocumentCode :
1671087
Title :
Electric vehicles as flexible loads: Algorithms to optimize aggregate behavior
Author :
Xiaojun Geng ; Khargonekar, Pramod P.
Author_Institution :
Dept. of Electr. & Comput. Eng., California State Univ., Northridge, CA, USA
fYear :
2012
Firstpage :
430
Lastpage :
435
Abstract :
This paper considers load shifting for electric vehicles (EVs) to reduce the peak value of the total power consumption. Large numbers of EV charging requests are classified into relatively small number of load types so that the computational effort remains unchanged as number of loads increases. A twolayer optimization scheme is proposed to deal with tasks that may demand sequentially varying power levels, which further reduces the computational burden. These ideas are potentially useful in harnessing flexibility in electric loads.
Keywords :
electric vehicles; optimisation; EV charging requests; aggregate behavior optimization; electric loads; electric vehicles; flexible loads; load shifting; load types; peak value reduction; sequentially varying power levels; total power consumption; two-layer optimization scheme; Batteries; Electric vehicles; Linear programming; Load modeling; Power demand; Schedules; Sociology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Smart Grid Communications (SmartGridComm), 2012 IEEE Third International Conference on
Conference_Location :
Tainan
Print_ISBN :
978-1-4673-0910-3
Electronic_ISBN :
978-1-4673-0909-7
Type :
conf
DOI :
10.1109/SmartGridComm.2012.6486022
Filename :
6486022
Link To Document :
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