Citizen centric optimal electric vehicle charging stations locations in a full city: case of Malaga
This addresses the practical issue of inefficient EV charging infrastructure for city residents, but it is incremental as it applies existing metaheuristics to a specific urban case.
The study tackled the problem of locating electric vehicle charging stations in Malaga, Spain, to minimize travel distances for citizens, using genetic algorithms and variable neighborhood search, with GA providing statistically the best results and dramatically improving the current installation.
This article presents the problem of locating electric vehicle (EV) charging stations in a city by defining the Electric Vehicle Charging Stations Locations (EV-CSL) problem. The idea is to minimize the distance the citizens have to travel to charge their vehicles. EV-CSL takes into account the maximum number of charging stations to install and the electric power requirements. Two metaheuristics are applied to address the relying optimization problem: a genetic algorithm (GA) and a variable neighborhood search (VNS). The experimental analysis over a realistic scenario of Malaga city, Spain, shows that the metaheuristics are able to find competitive solutions which dramatically improve the actual installation of the stations in Malaga. GA provided statistically the best results.