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

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...

Full description

Saved in:
Bibliographic Details
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:
EVs
GIS
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-33947
record_format dspace
spelling my.uniten.dspace-339472024-10-14T11:17:29Z An integrated GIS, MIF, and TOPSIS approach for appraising electric vehicle charging station suitability zones in Mumbai, India Rane N.L. Achari A. Saha A. Poddar I. Rane J. Pande C.B. Roy R. 57219453239 58165906700 57222261542 58713368400 58316635400 57193547008 57222031738 Air pollution Charging infrastructure EVs Geographic information system Multi-criteria decision-making Site selection India Maharashtra Mumbai Air pollution Charging (batteries) Climate change Decision making Electric vehicles Fossil fuels Information systems Information use Site selection 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 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 Final 2024-10-14T03:17:29Z 2024-10-14T03:17:29Z 2023 Article 10.1016/j.scs.2023.104717 2-s2.0-85162174411 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85162174411&doi=10.1016%2fj.scs.2023.104717&partnerID=40&md5=a5e2781272becab1c99a4218712b9c38 https://irepository.uniten.edu.my/handle/123456789/33947 97 104717 Elsevier Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Air pollution
Charging infrastructure
EVs
Geographic information system
Multi-criteria decision-making
Site selection
India
Maharashtra
Mumbai
Air pollution
Charging (batteries)
Climate change
Decision making
Electric vehicles
Fossil fuels
Information systems
Information use
Site selection
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
spellingShingle Air pollution
Charging infrastructure
EVs
Geographic information system
Multi-criteria decision-making
Site selection
India
Maharashtra
Mumbai
Air pollution
Charging (batteries)
Climate change
Decision making
Electric vehicles
Fossil fuels
Information systems
Information use
Site selection
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
Rane N.L.
Achari A.
Saha A.
Poddar I.
Rane J.
Pande C.B.
Roy R.
An integrated GIS, MIF, and TOPSIS approach for appraising electric vehicle charging station suitability zones in Mumbai, India
description 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
author2 57219453239
author_facet 57219453239
Rane N.L.
Achari A.
Saha A.
Poddar I.
Rane J.
Pande C.B.
Roy R.
format Article
author Rane N.L.
Achari A.
Saha A.
Poddar I.
Rane J.
Pande C.B.
Roy R.
author_sort Rane N.L.
title An integrated GIS, MIF, and TOPSIS approach for appraising electric vehicle charging station suitability zones in Mumbai, India
title_short An integrated GIS, MIF, and TOPSIS approach for appraising electric vehicle charging station suitability zones in Mumbai, India
title_full An integrated GIS, MIF, and TOPSIS approach for appraising electric vehicle charging station suitability zones in Mumbai, India
title_fullStr An integrated GIS, MIF, and TOPSIS approach for appraising electric vehicle charging station suitability zones in Mumbai, India
title_full_unstemmed An integrated GIS, MIF, and TOPSIS approach for appraising electric vehicle charging station suitability zones in Mumbai, India
title_sort integrated gis, mif, and topsis approach for appraising electric vehicle charging station suitability zones in mumbai, india
publisher Elsevier Ltd
publishDate 2024
_version_ 1814061158971211776
score 13.214268