Could petrol stations play a key role in transportation electrification? A GIS-based coverage maximization of fast EV chargers in urban environment

I. Safak Bayram, Usman Zafar, Sertac Bayhan

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Abstract

To achieve net-zero in the transportation sector, there is a need to deploy public electric vehicle (EV) fast chargers to boost customer confidence. Currently, charge point operators and EV manufacturers focus on deploying chargers to cover highway networks and the progress in urban environments is inadequate. This is becoming an obstacle for potential EV buyers who do not have access to dedicated chargers or cannot afford expensive EVs with larger battery packs. Since mainstream combustion engine vehicle drivers are accustomed to using petrol stations, this paper examines the suitability of such sites as candidate locations to deploy fast chargers. Spatial analysis is carried out by comparing their coverage performance with existing locations of the fast chargers. More specifically, the location problem is modelled as a maximum coverage location problem (MCLP) and solved using a geographic information system (GIS) based platform. The spatial optimization problem is solved using a linear-programming relaxation based MCLP algorithm developed in Python. Five cities with growing populations, namely San Clara, CA, Salt Lake City, UT, Raleigh, NC, Denver, CO, and Los Angeles, CA, are chosen as case studies. The location analysis is carried out with two demand metrics (population and road traffic) using actual GIS data collected from public authorities. The results show that deploying fast chargers at existing fuel stations significantly increases the coverage needed for EVs. This study will provide useful insights into EV fast charging station planning in urban cities, as the related research is still in its infancy.
Original languageEnglish
Pages (from-to)17318-17329
Number of pages12
JournalIEEE Access
Volume10
DOIs
Publication statusPublished - 7 Feb 2022

Keywords

  • electric vehicles
  • fast chargers
  • GIS systems
  • location analysis
  • petrol stations

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