Preprint
Fuzzy Ahp Multi-Criteria Decision Making and GIS Mapping for Ev Charging Infrastructure
Social Science Research Network (SSRN) , Vol.25 August 2024
Elsevier
2024
Abstract
The integration of Electric Vehicles (EVs) into the transportation network necessitates strategic planning for the establishment of an efficient and accessible charging infrastructure. This study presents a comprehensive approach that combines Fuzzy Analytic Hierarchy Process (AHP) Multi-Criteria Decision Making (MCDM) with Geographic Information System (GIS) mapping to identify optimal locations for EV charging stations in Melbourne City, Australia. In the recent decade, electric vehicles (EVs) have emerged as a clean and cost-efficient mode of transportation, offering an alternative to traditional gasoline-powered vehicles. To facilitate the broader acceptance of electric vehicles (EVs), the establishment of a corresponding charging infrastructure is imperative. While previous studies predominantly relied on programming models, this paper introduces a multi-criteria decision-making (MCDM) approach to assess various selected criteria. To account for uncertainties and the imprecision arising from the subjective judgments of decision-makers, this study employs the fuzzy Analytic Hierarchy Process (AHP) to determine the optimal location for Electric Vehicle Charging Station (EVCS) sites. Drawing insights from literature reviews, research reports, and expert insights across multiple domains, a weighted index system for EVCS site selection is devised from a sustainability standpoint. This system incorporates economic, social, and urban criteria, encompassing a total of six sub-criteria. Ultimately, the Fuzzy AHP method is utilized to pinpoint potential locations for EVCS sites. A study focusing on Melbourne is outlined, leading to the discovery of the best locations for Electric Vehicle Charging Stations (EVCS) according to the research results. This approach can enable urban planners and policymakers to make informed decisions that balance various competing interests in the deployment of EV charging infrastructure.
Details
- Title
- Fuzzy Ahp Multi-Criteria Decision Making and GIS Mapping for Ev Charging Infrastructure
- Authors
- Sagheer Ranjha - Swinburne University of TechnologyRezwanul Haque - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringMd Abdus Sattar (Corresponding Author) - Swinburne University of TechnologyPalaneeswaran Ekambaram - Swinburne University of TechnologyMohammad Islam Jahirul - Central Queensland UniversityN M S Hassan - Central Queensland University
- Publication details
- Social Science Research Network (SSRN) , Vol.25 August 2024
- Publisher
- Elsevier
- Date published
- 2024
- DOI
- 10.2139/ssrn.4936046
- ISSN
- 1556-5068
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991087897002621
- Output Type
- Preprint
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