Gaussian Mixture Model Clustering Based Optimal Location of EV Charging Stations

Abstract:

Building enough charging stations is the only way to let new energy vehicles come into our daily life. While, the cost of building a charging station is very expensive. Therefore, spatial optimal location of charging stations has to be dealt with. The main purpose of this paper is to investigate the spatial optimal location of charging stations using Gaussian Mixture Model clustering and charging requirement spots are taken as the clustering benchmark. The clustering procedure of charging station spatial optimal location is programmed using m-language. Finally, simulation results show the validity of proposed method.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 3400-3403
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.3400
• Online since: August 2013
• Authors: Qing Sheng Shi, Yi Cao
• Keywords: Charging Stations, Electric Vehicle (EV), Gaussian Mixture Model, Optimal Location

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