Energy retrieval from electric vehicles' discharging through multi-objective optimization - 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision Access content directly
Conference Papers Year : 2022

Energy retrieval from electric vehicles' discharging through multi-objective optimization

Ghimar Merhy
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Nazih Moubayed
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Abstract

Taking into consideration the huge pollution extent that keeps getting cumulated over time, particularly due to the transportation sector and the huge amount of greenhouse gases that it emits, the adoption of electric vehicles keeps expanding worldwide. Therefore, researchers have been consistently investigating the electrification of vehicles that partakes in several sectors where energy could be stored and retrieved based on the supply and demand of electricity, particularly because the storage of huge quantities of electrical energy remains extremely challenging. Hence, this study focuses on the retrieval of energy from the electric vehicle's battery in order to supply the grid, homes or buildings. This restitution generally occurs whenever the demand exceeds the electricity supply. So, whenever there's a lack of supply compared to the electricity demand, the discharging of vehicles would be launched, and then, the exceeding energy stored in the batteries could be, besides the vehicles' personal use, retrieved back to the grid or to supply houses. Subsequently, this study focuses on the retrieval of energy process where the electric vehicles would be discharging, aiming to optimize this process in a way that the houses would be purely supplied by the vehicle's stored energy assisted by renewable sources, hence omitting the supply by the grid. Thus, the energy retrieval is proposed through a multi-objective optimization of the flow of energy leaving the vehicle during its discharging process. It is carried out using a multi-objective optimization model aiming to minimize the battery's state of charge, the vehicles' discharging time and losses, and to maximize the battery's life time. The optimization is studied using the genetic algorithm approach, and is then verified by a Matlab simulation through the gamultiobj solver. Besides, a regulation algorithm is been proposed and simulated in order to manage the vehicles' discharging to tighten the difference margin between electricity consumption and production without over-consuming the vehicles' batteries.
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Dates and versions

hal-03597203 , version 1 (04-03-2022)

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  • HAL Id : hal-03597203 , version 1

Cite

Ghimar Merhy, Ahmed Nait-Sidi-Moh, Nazih Moubayed. Energy retrieval from electric vehicles' discharging through multi-objective optimization. 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, INSA Lyon, Feb 2022, Villeurbanne - Lyon, France. ⟨hal-03597203⟩
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