Spatial-Temporal model to estimate the load curves of charging stations for electric vehicles

Abstract

The use of electric vehicles in urban zones is an alternative to reduce the emission of gases that enhance the greenhouse effect. For promoting and encouraging this use, charging stations should be built due to the low autonomy of electric vehicles. Therefore, it is necessary to allocate these stations throughout the city, which will increase the load demand in the distribution system. In order to determine this increase, this paper presents a spatial-Temporal model based on multi-Agent systems. The results of the proposed model are the growth load on distribution feeders. The proposal was applied in a mid-sized city in Brazil with a penetration of 3.87% of EVs and ETs (3362) and the largest impact was an increase of 26.62% at peak load of a feeder. The determination of this growth is important information for the distribution utilities in order to perform the expansion planning of the distribution network.