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Authors: Hala Alsalloum 1 ; Leila Merghem-Boulahia 2 and Rana Rahim-Amoud 3

Affiliations: 1 LTRM / EDST, Lebanese University, Lebanon, ICD / ERA, University of Technology of Troyes and France ; 2 ICD / ERA, University of Technology of Troyes and France ; 3 LTRM / EDST, Lebanese University, Lebanon, Faculty of Science, Lebanese University and Lebanon

ISBN: 978-989-758-350-6

Keyword(s): Energy Trading, Optimization, Sellers, Buyers, Energy Management, Game Theory, Genetic Algorithm GA, Agents.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Multi-Agent Systems ; Software Engineering ; Symbolic Systems

Abstract: An essential element in the smart grid is the existence of prosumers, i.e. the consumers who can also produce and sell the energy. They will become one of the stakeholders of the future grid. Their active behavior is helpful on different sides: the environmental, economical and social sides. In fact, integrating the prosumers will result in selling the surplus of energy to the grid or other consumers. However, the interactions between prosumers and the grid need to be defined in order to maximize the profit of each stakeholder. This paper proposes an energy-trading algorithm based on game theory and genetic optimization in order to optimize the satisfaction of prosumers. In our solution, buyers can afford their demands from different sellers taking into consideration the distance, the price and the amount of energy traded and needed. Simulation results indicate the effectiveness of our proposed approach in terms of minimization the total cost and maximization each prosumer satisfactio n i.e. minimization the buyer’s bills and maximization the seller’s revenues. (More)

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Paper citation in several formats:
ALSALLOUM, H.; Merghem-Boulahia, L. and Rahim-Amoud, R. (2019). Energy Trading in the Smart Grid: Poly-sellers Decision based on Game Theory.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-350-6, pages 218-225. DOI: 10.5220/0007405002180225

@conference{icaart19,
author={ALSALLOUM, H. and Leila Merghem{-}Boulahia. and Rana Rahim{-}Amoud.},
title={Energy Trading in the Smart Grid: Poly-sellers Decision based on Game Theory},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2019},
pages={218-225},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007405002180225},
isbn={978-989-758-350-6},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Energy Trading in the Smart Grid: Poly-sellers Decision based on Game Theory
SN - 978-989-758-350-6
AU - ALSALLOUM, H.
AU - Merghem-Boulahia, L.
AU - Rahim-Amoud, R.
PY - 2019
SP - 218
EP - 225
DO - 10.5220/0007405002180225

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