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Integrated Location, Sizing, and Pricing for EV Charging Stations

In: Combinatorial Optimization and Applications

Author

Listed:
  • Miguel F. Anjos

    (University of Edinburgh
    GERAD, Polytechnique Montréal)

  • Ikram Bouras

    (Centre Inria de l’Université de Lille
    Université Ferhat Abbas)

  • Luce Brotcorne

    (Centre Inria de l’Université de Lille)

  • Alemseged G. Weldeyesus

    (University of Edinburgh)

  • Clémence Alasseur

    (EDF R&D)

  • Riadh Zorgati

    (EDF R&D)

Abstract

We propose a bilevel optimization model to support decision-making about locating, sizing and pricing of electric vehicle (EV) charging stations by taking into account the behaviour of EV users. This is done by adopting a preference-list or rank-based approach that characterizes users by a set of distinct ordered sets of predefined preferences or products. In the upper-level, the charging service provider is in charge of making decisions on the location, size and pricing of the charging stations to maximize its profit. In the lower level, EV users select their first available charging stations from their preference lists. We solve the bilevel optimization problem using a KKT-based single-level reformulation and provide extensive managerial insights on a randomly generated set of problem instances.

Suggested Citation

  • Miguel F. Anjos & Ikram Bouras & Luce Brotcorne & Alemseged G. Weldeyesus & Clémence Alasseur & Riadh Zorgati, 2024. "Integrated Location, Sizing, and Pricing for EV Charging Stations," International Series in Operations Research & Management Science, in: Teodor Gabriel Crainic & Michel Gendreau & Antonio Frangioni (ed.), Combinatorial Optimization and Applications, pages 431-448, Springer.
    • Handle: RePEc:spr:isochp:978-3-031-57603-4_18
    DOI: 10.1007/978-3-031-57603-4_18
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