A GIS-based optimal facility location framework for fast electric vehicle charging stations

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Zafar, Usman and Bayram, I. Safak and Bayhan, Sertac; (2021) A GIS-based optimal facility location framework for fast electric vehicle charging stations. In: 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE). IEEE International Symposium on Industrial Electronics (ISIE) . IEEE, Piscataway, NJ. ISBN 9781728190228 (https://doi.org/10.1109/ISIE45552.2021.9576448)

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Abstract

Deeper decarbonization of the transport sector requires building a wide coverage electric vehicle charging network that can meet driver's mobility patterns and refueling habits in a seamless manner. Currently, major market players mainly deploy chargers at existing public parking spaces at hotels, shopping centers, etc. On the other hand, gas/petroleum retail business is a century-old industry and “optimized” to serve the refueling needs of the drivers and they come to the forefront as “good” locations to site chargers. To that end, this paper addresses the fast charging station location problem in an urban environment. The optimization problem is formulated as a maximum coverage location problem (MCLP) and existing locations of petrol/fuel stations are considered as candidate locations. Using QGIS software, a geographic information system (GIS) based platform is developed and integrated with a linear-programming relaxation based MCLP algorithm developed in Python. The city of Raleigh, North Carolina with actual geo-spatial data is chosen as a case study. Both census population and highway traffic data are considered as demand metrics to mimic drivers without dedicated chargers and vehicles on highways who need a recharge. A number of evaluations are performed to explore the trade-off between the number of locations and the physical coverage space. Furthermore, comparative analysis show that locating fast chargers in existing petrol stations improve demand coverage by more than 50 % when compared to existing fast charging station locations.

ORCID iDs

Zafar, Usman, Bayram, I. Safak ORCID logoORCID: https://orcid.org/0000-0001-8130-5583 and Bayhan, Sertac;
  • Item type:Book Section
    ID code:76817
    Dates:
    Date
    Event
    1 November 2021
    Published
    17 April 2021
    Accepted
    Notes:© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:17 Jun 2021 10:40
    Last modified:21 Dec 2024 19:17
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/76817
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