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SGAM-Based Analysis for the Capacity Optimization of Smart Grids Utilizing e-Mobility: The Use Case of Booking a Charge Session

Author

Listed:
  • Moisés Antón García

    (Department of Technology, ETRA, 46018 Valencia, Spain)

  • Ana Isabel Martínez García

    (Department of Technology, ETRA, 46018 Valencia, Spain)

  • Stylianos Karatzas

    (Civil Engineering Department, University of Patras, 26500 Rio, Greece)

  • Athanasios Chassiakos

    (Civil Engineering Department, University of Patras, 26500 Rio, Greece)

  • Olympia Ageli

    (Civil Engineering Department, University of Patras, 26500 Rio, Greece)

Abstract

The description of the functionality of a smart grid’s architectural concept, analyzing different Smart Grid (SG) scenarios without disrupting the smooth operation of the individual processes, is a major challenge. The field of smart energy grids has been increasing in complexity since there are many stakeholder entities with diverse roles. Electric Vehicles (EVs) can transform the stress on the energy grid into an opportunity to act as a flexible asset. Smart charging through an external control system can have benefits for the energy sector, both in grid management and environmental terms. A suitable model for analyzing and visualizing smart grid use cases in a technology-neutral manner is required. This paper presents a flexible architecture for the potential implementation of electromobility as a distributed storage asset for the grid’s capacity optimization by applying the Use Case and Smart Grid Architecture Model (SGAM) methodologies. The use case scenario of booking a charge session through a mobile application, as part of the TwinERGY Horizon 2020 project, is deployed to structure the SGAM framework layers and investigate the applicability of the SGAM framework in the integration of electromobility as a distributed storage asset into electricity grids with the objective of enhanced flexibility and decarbonization.

Suggested Citation

  • Moisés Antón García & Ana Isabel Martínez García & Stylianos Karatzas & Athanasios Chassiakos & Olympia Ageli, 2023. "SGAM-Based Analysis for the Capacity Optimization of Smart Grids Utilizing e-Mobility: The Use Case of Booking a Charge Session," Energies, MDPI, vol. 16(5), pages 1-17, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2489-:d:1088773
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    References listed on IDEAS

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