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

Wilson Enrique Chumbi (), Roger Martínez-Minga, Sergio Zambrano-Asanza, Jonatas B. Leite and John Fredy Franco
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Wilson Enrique Chumbi: Department of Electrical Engineering, São Paulo State University—UNESP, Ilha Solteira 15385000, SP, Brazil
Roger Martínez-Minga: Department of Electrical Engineering–Research Group on Energy Transition (GITE), University Polytechnic Salesiana, Cuenca 010102, Ecuador
Sergio Zambrano-Asanza: Department of Planning, Centrosur Electric Distribution Utility, Cuenca 010209, Ecuador
Jonatas B. Leite: Department of Electrical Engineering, São Paulo State University—UNESP, Ilha Solteira 15385000, SP, Brazil
John Fredy Franco: Department of Electrical Engineering, São Paulo State University—UNESP, Ilha Solteira 15385000, SP, Brazil

Energies, 2024, vol. 17, issue 14, 1-27

Abstract: The 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.

Keywords: electric vehicle charging station; geographic information systems; geographically weighted regression; multi-criteria decision making; spatial interpolation; suitability analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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