Xin Gong
School of Electrical Engineering, Wuhan University, Wuhan, 430072, China
Tao Lin
School of Electrical Engineering, Wuhan University, Wuhan, 430072, China
Binghua Su
Information School, Zhuhai College Beijing Institute of Technology, Zhuhai, 519085, China
ABSTRACT
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
URL: https://scialert.net/abstract/?doi=jas.2013.2891.2896
DOI: 10.3923/jas.2013.2891.2896
URL: https://scialert.net/abstract/?doi=jas.2013.2891.2896
REFERENCES
- Clement-Nyns, K., E. Haesen and J. Driesen, 2010. The impact of charging plug-in hybrid electric vehicles on a residential distribution grid. IEEE Trans. Power Syst., 25: 371-380.
CrossRef - Deilami, S., A.S. Masoum, P.S. Moses and M.A.S. Masoum, 2011. Real-time coordination of plug-in electric vehicle charging in smart grids to minimize power losses and improve voltage profile. IEEE Trans. Smart Grid, 2: 456-467.
CrossRef - Gan, L.W., U. Topcu and S. Low, 2011. Optimal decentralized protocol for electric vehicle charging. Proceedings of the 50th IEEE Decision and Control and European Control Conference, December 12-15, 2011, Orlando, FL., USA., pp: 5798-5804.
CrossRef - Fernandez, L.P., T.G.S. Roman, R. Cossent, C.M. Domingo and P. Frias, 2011. Assessment of the impact of plug-in electric vehicles on distribution networks. IEEE Trans. Power Syst., 26: 206-213.
CrossRef - Moura, S.J., H.K. Fathy, D.S. Callaway and J.L. Stein, 2011. A stochastic optimal control approach for power management in plug-in hybrid electric vehicles. IEEE Trans. Control Syst. Technol., 19: 545-555.
CrossRef - Mitra, P. and G.K. Venayagamoorthy, 2010. Wide area control for improving stability of a power system with plug-in electric vehicles. IET Gener. Transm. Distrib., 4: 1151-1163.
CrossRef - Ma, Z.D., D. Callaway and I. Hiskens, 2010. Decentralized charging control for large populations of plug-in electric vehicles. Proceedings of the 49th IEEE Conference on Decision and Control, December 15-17, 2010, Atlanta, GA., USA., pp: 206-212.
CrossRef - Vaya, M.G. and G. Andersson, 2012. Centralized and decentralized approaches to smart charging of plug-in vehicles. Proceedings of the Power and Energy Society General Meeting, July 22-26, 2012, San Diego, CA., USA., pp: 1-8.
CrossRef - Monderer, D. and L.S. Shapley, 1996. Potential games. Games Econ. Behav., 14: 124-143.
CrossRefDirect Link - Qian, K.J., C.K. Zhou, M. Allan and Y. Yue, 2011. Modeling of load demand due to EV battery charging in distribution systems. IEEE Trans. Power Syst., 26: 802-810.
CrossRef - Richardson, P., D. Flynn and A. Keane, 2012. Optimal charging of electric vehicles in low-voltage distribution systems. IEEE Trans. Power Syst., 27: 268-279.
CrossRef - Sortomme, E., M.M. Hindi, S.D.J. MacPherson and S.S. Venkata, 2011. Coordinated charging of plug-in hybrid electric vehicles to minimize distribution system losses. IEEE Trans. Smart Grid, 2: 198-205.
CrossRef - Zhao, J.H., F.S. Wen, Z.Y. Dong, Y.S. Xue and K.P. Wong, 2012. Optimal dispatch of electric vehicles and wind power using enhanced particle swarm optimization. IEEE Trans. Ind. Inform., 8: 889-899.
CrossRef