Suitable Site Selection of Public Charging Stations: A Fuzzy TOPSIS MCDA Framework on Capacity Substation Assessment

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversity Polytechnic Salesiana-
Autor(es): dc.contributorCentrosur Electric Distribution Utility-
Autor(es): dc.creatorChumbi, Wilson Enrique-
Autor(es): dc.creatorMartínez-Minga, Roger-
Autor(es): dc.creatorZambrano-Asanza, Sergio-
Autor(es): dc.creatorLeite, Jonatas B.-
Autor(es): dc.creatorFranco, John Fredy-
Data de aceite: dc.date.accessioned2025-08-21T15:31:53Z-
Data de disponibilização: dc.date.available2025-08-21T15:31:53Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-07-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/en17143452-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/309913-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/309913-
Descrição: dc.descriptionThe number of electric vehicles (EVs) continues to increase in the automobile market, driven by public policies since they contribute to the global decarbonization of the transportation sector. Still, the main challenge to increasing EV adoption is charging infrastructure. Therefore, the site selection of public EV charging stations should be made very carefully to maximize EV usage and address the population’s range anxiety. Since electricity demand for charging EVs introduces new load shapes, the interrelationship between the location of charging stations and long-term electrical grid planning must be addressed. The selection of the most suitable site involves conflicting criteria, requiring the application of multi-criteria analysis. Thus, a geographic information system-based Multicriteria Decision Analysis (MCDA) approach is applied in this work to address the charging station site selection, where the demographic criteria and energy density are taken into account to formulate an EV increase model. Several methods, including Fuzzy TOPSIS, are applied to validate the selection of suitable sites. In this evaluation, the impact of the EV charging station on the substation capacity is assessed through a high EV penetration scenario. The proposed method is applied in Cuenca, Ecuador. Results show the effectiveness of MCDA in assessing the impact of charging stations on power distribution systems ensuring suitable system operation under substation capacity reserves.-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University—UNESP, SP-
Descrição: dc.descriptionDepartment of Electrical Engineering–Research Group on Energy Transition (GITE) University Polytechnic Salesiana-
Descrição: dc.descriptionDepartment of Planning Centrosur Electric Distribution Utility-
Descrição: dc.descriptionDepartment of Electrical Engineering São Paulo State University—UNESP, SP-
Idioma: dc.languageen-
Relação: dc.relationEnergies-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectelectric vehicle charging station-
Palavras-chave: dc.subjectgeographic information systems-
Palavras-chave: dc.subjectgeographically weighted regression-
Palavras-chave: dc.subjectmulti-criteria decision making-
Palavras-chave: dc.subjectspatial interpolation-
Palavras-chave: dc.subjectsuitability analysis-
Título: dc.titleSuitable Site Selection of Public Charging Stations: A Fuzzy TOPSIS MCDA Framework on Capacity Substation Assessment-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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