DocumentCode :
2574464
Title :
Decentralized charging control for large populations of plug-in electric vehicles
Author :
Ma, Zhongjing ; Callaway, Duncan ; Hiskens, Ian
Author_Institution :
Center for Sustainable Syst. (CSS), Univ. of Michigan, Ann Arbor, MI, USA
fYear :
2010
fDate :
15-17 Dec. 2010
Firstpage :
206
Lastpage :
212
Abstract :
The paper develops a novel decentralized charging control strategy for large populations of plug-in electric vehicles (PEVs). We consider the situation where PEV agents are rational and weakly coupled via their operation costs. At an established Nash equilibrium, each of the PEV agents reacts optimally with respect to the average charging strategy of all the PEV agents. Each of the average charging strategies can be approximated by an infinite population limit which is the solution of a fixed point problem. The control objective is to minimize electricity generation costs by establishing a PEV charging schedule that fills the overnight demand valley. The paper shows that under certain mild conditions, there exists a unique Nash equilibrium that almost satisfies that goal. Moreover, the paper establishes a sufficient condition under which the system converges to the unique Nash equilibrium. The theoretical results are illustrated through various numerical examples.
Keywords :
cost reduction; decentralised control; electric vehicles; fixed point arithmetic; game theory; minimisation; Nash equilibrium; decentralized charging control; electricity generation cost minimization; fixed point problem; plug in electric vehicle; Aggregates; Batteries; Convergence; Cost function; Electricity; Nash equilibrium; Trajectory; ‘Valley-filling’ charging strategy; Decentralized control; Nash equilibrium; Plug-in electric vehicles (PEVs);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
ISSN :
0743-1546
Print_ISBN :
978-1-4244-7745-6
Type :
conf
DOI :
10.1109/CDC.2010.5717547
Filename :
5717547
Link To Document :
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