Interurban charging station network: An evolutionary approach

• Published in: Neurocomputing (Amsterdam) 2023-04, Vol.529, p.214-221
• Main Authors: Jordán, Jaume, Martí, Pasqual, Palanca, Javier, Julian, Vicente, Botti, Vicente
• Format: Article
• Language: English
• Subjects: Charging station; Electric vehicle; Genetic algorithm; Interurban mobility
• ISSN: 0925-2312; 1872-8286
• DOI: 10.1016/j.neucom.2023.01.068

•Optimal location of interurban electric vehicle charging station infrastructure.•Multi-objective genetic algorithm to improve stalls utility and stations coverage.•Experimental results in the USA improve the current infrastructure. In recent years, there has been a strong desire to meet the challenge of electrification of vehicles in order to achieve the decarbonization objective. However, as sales of electric vehicles have increased, there is a significant lack of infrastructure to support the charging of this type of vehicle. The infrastructural deficiencies are even more evident in the interurban environment, where the autonomy in kilometers of the battery is a critical issue. To minimize the substantial economic costs involved in installing sufficient charging points to ensure any interurban journey, it is necessary to establish mechanisms that evaluate appropriate locations to deploy the necessary stations. Accordingly, this paper proposes using an evolutionary approach to calculate the most suitable locations in an interurban environment for electric charging stations. For this purpose, different input information is taken into account in the allocation process. The proposed algorithm has been tested using real data from the USA. The results assess the current infrastructure and show the advantages of the locations proposed by the algorithm.