Electric Vehicle Charging Stations Optimal Location Based on Fuzzy C-Means Clustering

Qing Sheng Shi; Xiao Zhen Zheng

doi:10.4028/www.scientific.net/AMM.556-562.3972

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Electric Vehicle Charging Stations Optimal...

Electric Vehicle Charging Stations Optimal Location Based on Fuzzy C-Means Clustering

Abstract:

As plug-in hybrid electric vehicles and battery electric vehicle ownership is expanding, there is a growing need for widely distributed publicly accessible charging stations. Building a charging station cost too much. Therefore, optimal location of charging stations has to be dealt with. The main purpose of this paper is to investigate the optimal location of charging stations using fuzzy C-means clustering method. Preliminary of fuzzy C-means clustering method is introduced first followed by the procedure of charging station optimal location using Fuzzy C-means Clustering. Finally, simulation results show the validity of proposed method.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

3972-3975

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.3972

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Online since:

May 2014

Authors:

Qing Sheng Shi*, Xiao Zhen Zheng

Keywords:

Charging Stations, Electric Vehicle (EV), Fuzzy C-Means Clustering, Optimal Location

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* - Corresponding Author

References

[1] C. C. Chan and K. T. Chau. Modern electric vehicle technology[M]. Oxford University Press, (2001).

Google Scholar

[2] Zhang Xiang, Wang Jia and Yang Jianzhong, etc. Prospects of New Energy Vehicles for China Market, Hybrid and Eco-Friendly Vehicle Conference, 2008, Page(s): 1 – 11.

DOI: 10.1049/cp:20081055

Google Scholar

[3] Shi Qing Sheng, Cao Yi. Gaussian mixture model clustering based optimal location of EV charging stations, Applied Mechanics and Materials, v 380-384, pp.3400-3403, (2013).

DOI: 10.4028/www.scientific.net/amm.380-384.3400

Google Scholar

[4] J. C. Dunn (1973): A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters, Journal of Cybernetics 3: 32-57.

DOI: 10.1080/01969727308546046

Google Scholar

[5] J. C. Bezdek (1981): Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press, New York.

Google Scholar

[6] Andy Ip, Simon Fong, Elaine Liu. Optimization for Allocating BEV Recharging Stations in Urban Areas by Using Hierarchical Clustering, Proceedings of the 2nd International Conference on Data Mining and Intelligent Information Technology Applications, 2010, 460-465.

Google Scholar