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Research Article

Two Approaches for Coordination of Electric Vehicle Charging and the Comparison

Xin Gong, Tao Lin and Binghua Su
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A large population of Electric Vehicles (EVs) will have a significant impact on the power grid if the charging of EVs is left uncontrolled. It is necessary to design optimal charging approach for Evs. In this study, we propose two optimal approaches for EV charging. They are congestion game-based centralized optimal approach and learning theory of game-based decentralized optimal approach. The objective of two approaches is to minimize the charging cost of each EV and meanwhile to flatten the total load profile. Under the approach based on congestion game, the problem of EV charging is described as a congestion game which solves the problem of EV acceptance that other centralized approaches have. Howerver, when there are high penetration of EVs, this approach requires significant computational capability. To develop a more practical approach, we propose the approach based on learning theory of game, where the optimized charging strategies are made locally and directly by EVs through learning in a repeated process. With the IEEE 33-bus case as the test system, results show that both approaches can flatten the total load profile, optimize power losses and improve voltage regulation effectively compared with the uncoordinated scenario.

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  How to cite this article:

Xin Gong, Tao Lin and Binghua Su , 2013. Two Approaches for Coordination of Electric Vehicle Charging and the Comparison. Journal of Applied Sciences, 13: 2891-2896.

DOI: 10.3923/jas.2013.2891.2896


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