LOAD ESTIMATION TO THE PLANNING FOR ELECTRIC VEHICLE PUBLIC CHARGING STATIONS IN URBAN ZONES USING SPATIAL ANALYSIS AND TRAFFIC SIMULATIONS

Abstract

Reach anxiety can be defined as the fear of electric vehicle owners not reach their final destination. Planning of public charging stations is necessary for urban zones to reduce such fear. This work presents a methodology that estimates the state of charge's variation in urban zones' avenues, calculating the electric demand for charging stations' planning studies. The proposal is composed of two modules. The first module uses a spatial regression to identify EVs travel' origins. The second module considers a technology exchange in the OD matrix available in the urban planning department to insert input data in the traffic simulator. The proposal's output is a heat map that shows the SOC variation by the study area's main avenues. The proposed method was applied in a metropolis in Brazil with 2,886,698 inhabitants and 675,450 private vehicles, considering two electric vehicle penetration scenarios. The proposal's output helps identify the regions with the most significant electric vehicle flow with low-level charges values. From this identification, it is possible to analyse the electrical networks' impacts and define charging stations' connection points with the distribution network.