EV aggregation modeling based on improved K-means

Abstract

An improved K-means clustering algorithm based on the initial clustering center is used to cluster the charging data of electric vehicles. The multi-classification method is studied, and the clustering effect of different number of clusters is analyzed with the contour coefficient as the evaluation standard. The simulation results show that this method can properly cluster the group characteristics of electric vehicles