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Optimal Management of Energy Communities Hosting a Fleet of Electric Vehicles

Author

Listed:
  • Giovanni Gino Zanvettor

    (Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Università di Siena, 53100 Siena, Italy)

  • Marco Casini

    (Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Università di Siena, 53100 Siena, Italy)

  • Antonio Giannitrapani

    (Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Università di Siena, 53100 Siena, Italy)

  • Simone Paoletti

    (Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Università di Siena, 53100 Siena, Italy)

  • Antonio Vicino

    (Dipartimento di Ingegneria dell’Informazione e Scienze Matematiche, Università di Siena, 53100 Siena, Italy)

Abstract

In this paper, we study the problem of managing an energy community hosting a fleet of electric vehicles for rent. On the day ahead, service requests for electric vehicles are submitted to the community. Then, the optimal request-to-vehicle assignment has to be found, as well as the optimal charging schedule of vehicle batteries. A suitable model is presented and included in an existing energy community architecture. The overall community management problem is formulated as a bi-level model, featuring two nested optimization problems. The optimal request-to-vehicle assignment requires the solution of a mixed-integer linear program. To reduce the computational complexity, a heuristic solution to the assignment problem is presented. Numerical results show that participation in the community grants a remarkable reduction in the electric vehicle charging cost. The adoption of the heuristic assignment solution provides a dramatic reduction in the computation time required to solve the bi-level model. At the same time, the level of suboptimality introduced appears to be negligible, being less than 1% in most of the considered cases.

Suggested Citation

  • Giovanni Gino Zanvettor & Marco Casini & Antonio Giannitrapani & Simone Paoletti & Antonio Vicino, 2022. "Optimal Management of Energy Communities Hosting a Fleet of Electric Vehicles," Energies, MDPI, vol. 15(22), pages 1-16, November.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8697-:d:977747
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    References listed on IDEAS

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    1. Gonzalez Venegas, Felipe & Petit, Marc & Perez, Yannick, 2021. "Active integration of electric vehicles into distribution grids: Barriers and frameworks for flexibility services," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    2. Sara Hsaini & Mounir Ghogho & My El Hassan Charaf, 2022. "An OCPP-Based Approach for Electric Vehicle Charging Management," Energies, MDPI, vol. 15(18), pages 1-14, September.
    3. Cornélusse, Bertrand & Savelli, Iacopo & Paoletti, Simone & Giannitrapani, Antonio & Vicino, Antonio, 2019. "A community microgrid architecture with an internal local market," Applied Energy, Elsevier, vol. 242(C), pages 547-560.
    4. Bertrand Corn'elusse & Iacopo Savelli & Simone Paoletti & Antonio Giannitrapani & Antonio Vicino, 2018. "A Community Microgrid Architecture with an Internal Local Market," Papers 1810.09803, arXiv.org, revised Feb 2019.
    5. Robin Sudhoff & Sebastian Schreck & Sebastian Thiem & Stefan Niessen, 2022. "Operating Renewable Energy Communities to Reduce Power Peaks in the Distribution Grid: An Analysis on Grid-Friendliness, Different Shares of Participants, and Economic Benefits," Energies, MDPI, vol. 15(15), pages 1-18, July.
    6. Marszal-Pomianowska, Anna & Heiselberg, Per & Kalyanova Larsen, Olena, 2016. "Household electricity demand profiles – A high-resolution load model to facilitate modelling of energy flexible buildings," Energy, Elsevier, vol. 103(C), pages 487-501.
    7. Andu Dukpa & Boguslaw Butrylo, 2022. "MILP-Based Profit Maximization of Electric Vehicle Charging Station Based on Solar and EV Arrival Forecasts," Energies, MDPI, vol. 15(15), pages 1-14, August.
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    Cited by:

    1. Giovanni Gino Zanvettor & Marco Casini & Antonio Vicino, 2024. "Optimal Operation of Energy Storage Facilities in Incentive-Based Energy Communities," Energies, MDPI, vol. 17(11), pages 1-20, May.
    2. Giulia Palma & Leonardo Guiducci & Marta Stentati & Antonio Rizzo & Simone Paoletti, 2024. "Reinforcement Learning for Energy Community Management: A European-Scale Study," Energies, MDPI, vol. 17(5), pages 1-19, March.

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