A game theory approach with dynamic pricing to optimize smart grid operation

Abstract : Smart Grids components include scalable metering,energy prediction (both production and consumption) and pricing. One of their goals consists to attract consumers to use green energy, to promote periods of low consumption and to dissuade customers from using their greedy devices during peak periods. The objective consists to determine the optimal suggested prices by the energy operator and the optimal demands of consumers. In this paper, we propose a theoretical model based on Stackelberg game to adjust prices of green energy. The proposed game is composed by a leader represented by the operator, and multiple followers represented by consumers. A Nash/Stackelberg equilibrium solution is found. Performance results confirm the uniqueness of Nash equilibrium and that a "best reply" dynamics for the repeated game converges to this equilibrium
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International Journal of Smart Grid and Clean Energy (IJSGCE), 2015, 4 (3), pp.186 - 198. 〈10.12720/sgce.4.3.186-198 〉
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https://hal.archives-ouvertes.fr/hal-01255130
Contributeur : Médiathèque Télécom Sudparis & Institut Mines-Télécom Business School <>
Soumis le : mercredi 13 janvier 2016 - 11:14:24
Dernière modification le : jeudi 11 janvier 2018 - 06:15:41

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Makhlouf Hadji, Marc Girod-Genet, Hossam Afifi. A game theory approach with dynamic pricing to optimize smart grid operation. International Journal of Smart Grid and Clean Energy (IJSGCE), 2015, 4 (3), pp.186 - 198. 〈10.12720/sgce.4.3.186-198 〉. 〈hal-01255130〉

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