Abstract:

This study has proposed a methodology to optimally locate charging stations (CSs) through a multi-objective approach, by minimizing the electrical losses and the charging zone center deviation.  It applies a hierarchical clustering method to define CS service zones, considering both technical and mobility aspects. Besides, it considers uncertainties related to the EV load profile to determine the CS capacity, based on the user's charging behavior. A Pareto Frontier method is deployed to support the decision-making process on CS optimal location, considering utility and EV users’ preferences. The results indicate that the best CS locations for mid-term EV penetration can also fit into long-term planning, with higher EV charging demand. Thus, these locations would be good candidates for the power utility to make initial investments, regarding both planning horizons. A real distribution system case is used to demonstrate the applicability of the results.