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Categorization of Attributes and Features for the Location of Electric Vehicle Charging Stations.

Authors :
Mazza, Andrea
Russo, Angela
Chicco, Gianfranco
Di Martino, Andrea
Colombo, Cristian Giovanni
Longo, Michela
Ciliento, Paolo
De Donno, Marco
Mapelli, Francesca
Lamberti, Francesco
Source :
Energies (19961073). Aug2024, Vol. 17 Issue 16, p3920. 32p.
Publication Year :
2024

Abstract

The location of Electric Vehicle Charging Stations (EVCSs) is gaining significant importance as part of the conversion to a full-electric vehicle fleet. Positive or negative impacts can be generated mainly based on the quality of service offered to customers and operational efficiency, also potentially involving the electrical grid to which the EVCSs are connected. The EVCS location problem requires an in-depth and comprehensive analysis of geographical, market, urban planning, and operational aspects that can lead to several potential alternatives to be evaluated with respect to a defined number of features. This paper discusses the possible use of a multi-criteria decision-making approach, considering the differences between multi-objective decision making (MODM) and multi-attribute decision-making (MADM), to address the EVCS location problem. The conceptual evaluation leads to the conclusion that the MADM approach is more suitable than MODM for the specific problem. The identification of suitable attributes and related features is then carried out based on a systematic literature review. For each attribute, the relative importance of the features is obtained by considering the occurrence and the dedicated weights. The results provide the identification of the most used attributes and the categorization of the selected features to shape the proposed MADM framework for the location of the electric vehicle charging infrastructure. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19961073
Volume :
17
Issue :
16
Database :
Academic Search Index
Journal :
Energies (19961073)
Publication Type :
Academic Journal
Accession number :
179354902
Full Text :
https://doi.org/10.3390/en17163920