Estimation of Electric Demand from Electric Vehicles Using Spatial Regressions

Abstract

The acquisition of electric vehicles depends on socioeconomic factors and does not occur homogeneously in the different zones of urban areas for the early years of the electric vehicles penetrations. The concentration of these vehicles can be found by spatial regressions that correlate statically the electric vehicles rate by subarea with the socioeconomic factors of their neighboring regions. Such correlation allows characterizing the influence of the inhabitants in neighboring regions to the purchase of electric vehicles. Therefore, this work aims to show how spatial regressions can provide useful information to determine the load growth by the electric vehicles recharging. To exemplify the information quality, provide from such regression classes, the application of two regressions is performed for a medium-sized city in Brazil in order to determine the best location of charging stations for electric vehicles and the maximum diversified demand in each subarea.