Estimation of Optimal Locations for Electric Vehicle Charging Stations - Catalbas, Mehmet Cem; Yildirim, Merve; Gulten, Arif; Kurum, Hasan (Ieee, 2017)
Electric Vehicles (EV) have been commonly started to use due to some advantages such as less emission, lower noise pollution, maintenance requirement and power consumption. The number of charging stations have also increased based on rising the usage of EVs. Therefore, determination of optimal location for EV charge stations has a great importance for charging process. This localization is highly related with the range of EV and traffic density on areas. The distribution of charging stations is a basically optimization problem. For this reason, estimation of optimum locations for EV charging stations in Ankara, Turkey is realized by using data mining methods in this paper. Some parameters for determining of optimum locations which are the average number of EVs on the road and the average range are examined. Ankara road map is derived by using Mapbox Software obtained from the satellite via spectral clustering. Then, some of the image processing methods such as thresholding, erosion and dilation are used for eliminating clustering errors. Furthermore, optimal charging locations of EVs for Ankara are estimated by various clustering approaches such as spectral clustering and Gaussian Mixture Model (GMM) using a total number of charging stations. In conclusion, this paper is a novel study for Turkey which has not been worked in the literature and it can be easily applied to any region in the future works.
17th IEEE International Conference on Environment and Electrical Engineering (IEEE EEEIC) / 1st IEEE Industrial and Commercial Power Systems Europe Conference (IEEE I and CPS Europe) -- JUN 06-09, 2017 -- Milan, ITALY
Keywords: electric vehicle; charging station; optimal location; spectral clustering; gaussian mixture model