Open AccessElectric vehicle charging stations’ location in urban transportation networks: A heuristic methodology
Author(s) -
Torres Franco Sebastian,
Durán Tovar Ivan Camilo,
Suárez Pradilla Mónica Marcela,
Marulanda Guerra Agustin
Publication year - 2021
Publication title -
iet electrical systems in transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 26
eISSN - 2042-9746
pISSN - 2042-9738
DOI - 10.1049/els2.12011
Subject(s) - heuristic , metropolitan area , transport engineering , computer science , software deployment , greedy algorithm , flow network , multipath propagation , operations research , electric vehicle , point of interest , investment (military) , mathematical optimization , engineering , telecommunications , geography , power (physics) , physics , quantum mechanics , artificial intelligence , channel (broadcasting) , mathematics , archaeology , algorithm , politics , law , political science , operating system
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.