An App-based Algorithmic Approach for Harvesting Local and Renewable Energy using Electric Vehicles

Antoine Dubois, Antoine Wehenkel, Raphael Fonteneau, Frédéric Olivier, Damien Ernst

Abstract

The emergence of electric vehicles (EVs), combined with the rise of renewable energy production capacities, will strongly impact the way electricity is produced, distributed and consumed in the very near future. This position paper focuses on the problem of optimizing charging strategies for a fleet of EVs in the context where a significant amount of electricity is generated by (distributed) renewable energy. It exposes how a mobile application may offer an efficient solution for addressing this problem. This app can play two main roles. Firstly, it would incite and help people to play a more active role in the energy sector by allowing photovoltaic (PV) panel owners to sell their electrical production directly to consumers, here the EVs’ agents. Secondly, it would help distribution system operators (DSOs) or transmission system operators (TSOs) to modulate more efficiently the load by allowing them to influence EV charging behaviour in real time. Finally, the present paper advocates for the introduction of a two-sided market-type model between EV drivers and electricity producers.

References

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Paper Citation


in Harvard Style

Dubois A., Wehenkel A., Fonteneau R., Olivier F. and Ernst D. (2017). An App-based Algorithmic Approach for Harvesting Local and Renewable Energy using Electric Vehicles . In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-219-6, pages 322-327. DOI: 10.5220/0006250803220327


in Bibtex Style

@conference{icaart17,
author={Antoine Dubois and Antoine Wehenkel and Raphael Fonteneau and Frédéric Olivier and Damien Ernst},
title={An App-based Algorithmic Approach for Harvesting Local and Renewable Energy using Electric Vehicles},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2017},
pages={322-327},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006250803220327},
isbn={978-989-758-219-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - An App-based Algorithmic Approach for Harvesting Local and Renewable Energy using Electric Vehicles
SN - 978-989-758-219-6
AU - Dubois A.
AU - Wehenkel A.
AU - Fonteneau R.
AU - Olivier F.
AU - Ernst D.
PY - 2017
SP - 322
EP - 327
DO - 10.5220/0006250803220327