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Article

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

by
Moisés Antón García
1,
Ana Isabel Martínez García
1,
Stylianos Karatzas
2,*,
Athanasios Chassiakos
2 and
Olympia Ageli
2
1
Department of Technology, ETRA, 46018 Valencia, Spain
2
Civil Engineering Department, University of Patras, 26500 Rio, Greece
*
Author to whom correspondence should be addressed.
Energies 2023, 16(5), 2489; https://doi.org/10.3390/en16052489
Submission received: 9 February 2023 / Revised: 25 February 2023 / Accepted: 2 March 2023 / Published: 6 March 2023

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.
Keywords: electromobility; EV charging; SGAM framework; electricity grids electromobility; EV charging; SGAM framework; electricity grids

Share and Cite

MDPI and ACS Style

García, M.A.; García, A.I.M.; Karatzas, S.; Chassiakos, A.; Ageli, O. SGAM-Based Analysis for the Capacity Optimization of Smart Grids Utilizing e-Mobility: The Use Case of Booking a Charge Session. Energies 2023, 16, 2489. https://doi.org/10.3390/en16052489

AMA Style

García MA, García AIM, Karatzas S, Chassiakos A, Ageli O. SGAM-Based Analysis for the Capacity Optimization of Smart Grids Utilizing e-Mobility: The Use Case of Booking a Charge Session. Energies. 2023; 16(5):2489. https://doi.org/10.3390/en16052489

Chicago/Turabian Style

García, Moisés Antón, Ana Isabel Martínez García, Stylianos Karatzas, Athanasios Chassiakos, and 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 16, no. 5: 2489. https://doi.org/10.3390/en16052489

APA Style

García, M. A., García, A. I. M., Karatzas, S., Chassiakos, A., & Ageli, O. (2023). SGAM-Based Analysis for the Capacity Optimization of Smart Grids Utilizing e-Mobility: The Use Case of Booking a Charge Session. Energies, 16(5), 2489. https://doi.org/10.3390/en16052489

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