Allocation of Electric Vehicle Charging Stations in Urban Areas Using GIS

The current EV charging points can be inadequately equipped to meet the rapidly increasing battery charging demand of EVs. Therefore, in this paper, a Geographic Information System (GIS)-based Multiplecriteria decision analysis (MCDA) approach is adopted to help providing a solution of charging points location problem. Furthermore, the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are used to select the optimal charging station site. A five-step approach is developed: determination of 14 criteria across four perspectives, spatial analysis using QGIS, criteria prioritization with AHP, site ranking in use of TOPSIS, and site capacity estimation. By integrating these methodologies, optimal charging point locations can be identified while ensuring effective deployment and utilization of EV charging infrastructure. Through a complete and considerate analysis, the study identifies the three most appropriate alternative locations for EVs including photovoltaic power.

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Publication Details

Journal
SPIRE - Sciences Po Institutional REpository
Published
2025-05-21
DOI
https://doi.org/10.34746/epe2025-0319
Primary Topic
Forest Ecology and Biodiversity Studies
Type
article
Field-Weighted Citation Impact
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article

Allocation of Electric Vehicle Charging Stations in Urban Areas Using GIS

SPIRE - Sciences Po Institutional REpository
Forest Ecology and Biodiversity Studies
article

Allocation of Electric Vehicle Charging Stations in Urban Areas Using GIS

article en

Abstract

The current EV charging points can be inadequately equipped to meet the rapidly increasing battery charging demand of EVs. Therefore, in this paper, a Geographic Information System (GIS)-based Multiplecriteria decision analysis (MCDA) approach is adopted to help providing a solution of charging points location problem. Furthermore, the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are used to select the optimal charging station site. A five-step approach is developed: determination of 14 criteria across four perspectives, spatial analysis using QGIS, criteria prioritization with AHP, site ranking in use of TOPSIS, and site capacity estimation. By integrating these methodologies, optimal charging point locations can be identified while ensuring effective deployment and utilization of EV charging infrastructure. Through a complete and considerate analysis, the study identifies the three most appropriate alternative locations for EVs including photovoltaic power.

SPIRE - Sciences Po Institutional REpository
Université de Technologie de Compiègne (FR)
Industry, innovation and infrastructure
Openalex Percentile: Top 51%
Forest Ecology and Biodiversity Studies
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Allocation of Electric Vehicle Charging Stations in Urban Areas Using GIS · SPIRE - Sciences Po Institutional REpository (2025) | TGRS Research Map | TGRS