Electric vehicle charging stations emplacement using genetic algorithms and agent-based simulation

Abstract

The increasingly evident incorporation of the electric vehicle in urban environments is an already undeniable change. Electric vehicles are appearing on the market with more autonomy and lower prices, which is facilitating the progressive change of the vehicle fleet. However, the electric vehicle brings with it the need to provide enough charging stations distributed throughout the city, so that the autonomy of the vehicle is not a problem. This work presents how a genetic algorithm that analyzes the open data sources of a city is used to propose the most suitable locations for these stations. This proposal is the input for a series of experiments that simulate the impact that has the placement of these stations along the city, in order to measure the benefits of the solution proposed by the genetic algorithm. To do this, an agent-based simulation infrastructure was built around a fleet simulator.