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Hierarchical system model for the energy management in the smart grid: A game theoretic approach

Abstract : Nowadays, Demand Side Management (DSM) in the Smart Grids (SG) opens new perspectives on the management of the prosumers’ demands. The use of Information and Communication Technologies (ICT) empowers SG with the capability of supporting two-way energy and information flows, facilitating the integration of renewable energy into the grid and empowering the consumer with tools for optimizing energy consumption and costs. Many researches have highlighted on the active role of consumers in the DSM. However, they limited their role to either negotiating with the providers about the unit energy price, or trading their surplus of energy, if any, with other prosumers or providers. In this paper, we introduce a hierarchical system model where multiple providers and prosumers interact to define the best price and demands. We highlight the capacity of a prosumer to produce energy and minimize the dependency on the providers in the overall proposed energy management. The latter will be able to maximize his satisfaction by trading energy, first, with other prosumers with a suitable price, and by interacting with the providers, if any remaining energy needed, in a distributed way. Hence, we optimize the price and demands while considering multiple constraints and different providers and prosumers by establishing a Stackelberg game to model two types of interactions: (1) prosumer-prosumer and (2) provider-consumer. We prove that a unique equilibrium solution exists and simulation results show that our proposed approach optimizes energy consumption and price.
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Contributor : Jean-Baptiste VU VAN Connect in order to contact the contributor
Submitted on : Tuesday, March 10, 2020 - 3:52:53 PM
Last modification on : Sunday, June 26, 2022 - 4:38:29 AM

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Hala Alsalloum, Leila Merghem-Boulahia, Rana Rahim. Hierarchical system model for the energy management in the smart grid: A game theoretic approach. Sustainable Energy, Grids and Networks, Elsevier, 2020, pp.100329. ⟨10.1016/j.segan.2020.100329⟩. ⟨hal-02504279⟩



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