Citizen centric optimal electric vehicle charging stations locations in a full city: case of Malaga

TL;DR

This paper addresses optimal placement of EV charging stations in Malaga city using metaheuristics to minimize citizen travel distance, demonstrating effective solutions that outperform current installations.

Contribution

It introduces the EV-CSL problem and applies genetic algorithms and VNS to optimize station locations in a real city scenario.

Findings

Metaheuristics find competitive solutions for station placement.

Genetic Algorithm outperforms other methods statistically.

Proposed solutions significantly improve current Malaga station setup.

Abstract

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.