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V2G-based Smart Autonomous Vehicle For Urban Mobility using Renewable Energy
- Publication Year :
- 2015
-
Abstract
- IRSEEM is coordinator of a research program Savemore [19] aiming to develop and demonstrate the viability and effectiveness of systems for electrical transport and urban logistics based on autonomous robotic electric vehicles operating within a smart grid electrical power distribution framework. As a part of this project, our work focuses on the study of the coupling of electric vehicles with renewable energy. At the scale of a city, electric vehicles can be considered as a means of intermittent storage of electric power which can be distributed to the network when it is required (e.g., at times of the date when demand spikes). When these vehicles belong to a controlled and intelligent fleet, network organization is dynamic and leads to a smart grid. The widespread use of electric vehicles in cities coupled with renewable energy appears as a powerful tool to help local and regional authorities in the implementation of the European Agenda for low-carbon, reduced air pollution and encourage energy savings. In this paper, we present a Vehicle to Grid model which implements the interaction between an electric vehicle and a smart grid. The model takes into account several kinds of parameters related to the battery, the charging station, the size of the fleet and the power grid as the expansion coefficient. A statistical approach is adopted for the setting of these parameters to determine the significant parameters. Several simulations are performed to validate the model. In first step, we have studied the behavior of the model on a typical day of a person who has traveled from his home to work (in France). As a second step, and in order to study the power consumption behavior of the model, we have tested it during several seasons. The results show the effectiveness of the model developed.
Details
- Database :
- OAIster
- Notes :
- V2G-based Smart Autonomous Vehicle For Urban Mobility using Renewable Energy
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.ocn944225683
- Document Type :
- Electronic Resource