Optimization of Grid Energy Balance Using Vehicle-to-Grid Network System

Carlos Armenta-Déu () and Laura Demas
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Carlos Armenta-Déu: Department of Matter Structure, Thermal Physics and Electronics, Faculty of Physics Sciences, Complutense University of Madrid, 28040 Madrid, Spain
Laura Demas: Polytechnical Institute, Université Clermont Auvergne, Campus Universitaire de Cézeaux, 2, Avenue Blaise-Pascal, TSA 60206-CS 60026, 63178 Aubière, France

Energies, 2024, vol. 17, issue 5, 1-28

Abstract: This paper proposes a methodological way to compensate for the imbalance between energy generation and consumption using a battery block from electric vehicles as an energy reservoir through the well-known vehicle-to-grid system (V2G). This method is based on a simulation process developed by the authors that takes into consideration the daily fluctuations in energy consumption as well as the power level generated by an energy source, either conventional, renewable, or hybrid. This study shows that for very large electric vehicle fleets, the system is rendered non-viable, since the remaining energy in the battery block that allows the electric vehicle to be usable during the daytime avoids having to compensate for the energy grid imbalance, only allowing it to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. This method allows for predicting the optimum size of an electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance, and size of the electric vehicle fleet.

Keywords: electric grid; energy balance; vehicle to grid (V2G); electric vehicle; battery (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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