Electric vehicle charging stations’ location in urban transportation networks: A heuristic methodology.

The lack of public charging infrastructure has been one of the main barriers preventing the technological transition from traditional vehicles to electric vehicles. To accelerate this technological transition, it is necessary to elaborate optimal charging station location strategies to increase the...

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Autores:
Torres Franco, Sebastian
Durán Tovar, Ivan Camilo
Suárez Pradilla, Mónica Marcela
Marulanda Guerra, Agustin
Tipo de recurso:
Article of investigation
Fecha de publicación:
2021
Institución:
Escuela Colombiana de Ingeniería Julio Garavito
Repositorio:
Repositorio Institucional ECI
Idioma:
eng
OAI Identifier:
oai:repositorio.escuelaing.edu.co:001/1944
Acceso en línea:
https://repositorio.escuelaing.edu.co/handle/001/1944
Palabra clave:
Vehículos eléctricos
Algoritmos heurísticos
Estaciones de carga de batería (Vehículos eléctricos)
Electric vehicles
Heuristic algorithms
Battery charging stations (Electric vehicles)
Rights
openAccess
License
© 2021 The Authors
Description
Summary:The lack of public charging infrastructure has been one of the main barriers preventing the technological transition from traditional vehicles to electric vehicles. To accelerate this technological transition, it is necessary to elaborate optimal charging station location strategies to increase the user confidence, and maintain investment costs within acceptable levels. However, the existing works for this purpose are often based on multipath considerations or multi-objective functions, that result in taxing computational efforts for urban transportation networks. This article presents a heuristic methodology for urban transportation networks, that considers the deployment of the charging stations for coverage purposes, and the fulfilment of user preferences and constraints as two separated processes. In this methodology, a Reallocation Algorithm is formulated to prioritize the selection of Locations of Interest, and to reduce the number of stations with overlapping covering areas. The methodology results are compared to those drawn from a Greedy Algorithm based on a multipath consideration, in an extensive metropolitan transportation network. The results show that the proposed methodology significantly reduce the computational time required for solving the location problem, and furthermore, allows for similar results to those obtained when considering k = 2 and k = 3 deviation paths.