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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Wilson Enrique Chumbi & Roger Martínez-Minga & Sergio Zambrano-Asanza & Jonatas B. Leite & John Fredy Franco, 2024. "Suitable Site Selection of Public Charging Stations: A Fuzzy TOPSIS MCDA Framework on Capacity Substation Assessment," Energies, MDPI, vol. 17(14), pages 1-27, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:14:p:3452-:d:1434600
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    References listed on IDEAS

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    1. Guo, Sen & Zhao, Huiru, 2015. "Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective," Applied Energy, Elsevier, vol. 158(C), pages 390-402.
    2. Huiru Zhao & Nana Li, 2016. "Optimal Siting of Charging Stations for Electric Vehicles Based on Fuzzy Delphi and Hybrid Multi-Criteria Decision Making Approaches from an Extended Sustainability Perspective," Energies, MDPI, vol. 9(4), pages 1-22, April.
    3. Namdeo, A. & Tiwary, A. & Dziurla, R., 2014. "Spatial planning of public charging points using multi-dimensional analysis of early adopters of electric vehicles for a city region," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 188-200.
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