An integrated GIS, MIF, and TOPSIS approach for appraising electric vehicle charging station suitability zones in Mumbai, India

• Main Authors: Rane N.L., Achari A., Saha A., Poddar I., Rane J., Pande C.B., Roy R.
• Other Authors: 57219453239
• Format: Article
• Published: Elsevier Ltd 2024
• Subjects: Air pollution; Charging infrastructure; EVs; Geographic information system; Multi-criteria decision-making; Site selection; India; Maharashtra; Mumbai; Charging (batteries); Climate change; Decision making; Electric vehicles; Fossil fuels; Information systems; Information use; Charging infrastructures; Charging station; Electric vehicle charging; Factor weight; Geographical information; Multi criteria decision-making; Multicriteria decision-making; Multicriterion decision makings; Suitability index; Technique for order preference by similarities to ideal solutions; atmospheric pollution; decision making; electric vehicle; GIS; site selection; technology adoption; transportation infrastructure; Geographic information systems
• Institution: Universiti Tenaga Nasional

Fossil fuels cause air pollution and climate change, impacting human health. Mumbai imports and spends heavily on petroleum. Therefore, to reduce the amount of fossil fuel and for mitigating environmental issues, the use of electric vehicles (EVs) is an effective solution. The first priority towards supporting the widespread adoption of EVs is the availability of convenient charging stations. This research aims to delineate the optimal places for new electric vehicle charging stations (EVCS) in study area. The interrelationship of thirteen parameters have been used to determine the Multi Influencing Factor (MIF) weights. These MIF weights were then integrated into Geographical Information System (GIS) for weighted overlay analysis. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) used to assign ranks based on suitability index values. The result shows that the zone falling between 297.587 to 488.520 suitability index has suitability for EVCS. The proposed methodology offers a more precise solution for EVCS problems with a high level of uncertainty and assists policymakers and administrators in making effective decisions for future planning and strategies. � 2023 Elsevier Ltd