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IEEE Systems Journal
Article . 2020 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
PolyPublie
Article . 2020
Data sources: PolyPublie
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A Game Theoretic Model for the Multiperiodic Smart Grid Demand Response Problem

Authors: Slim Belhaiza; Uthman Baroudi; Issmail Elhallaoui;

A Game Theoretic Model for the Multiperiodic Smart Grid Demand Response Problem

Abstract

Today's smart grid faces many challenges due to the rapid evolution of generation, distribution, and storage means which enable users to produce, store, and sell energy back to the providers. Demand response management plays a key role in achieving the objective of balancing electricity supply and demand efficiently. It also helps leveling consumption during peak hours. To do so, this paper proposes a game theoretic model for the multiperiodic smart grid demand side management problem with shifted demand. The proposed model has two major sets of players: Homeowners and electricity providers. We develop a 0–1 mixed linear programming approach to compute the Nash equilibria of the proposed game. We analyze the structure of the Nash equilibria to maintain the viability of the smart grid infrastructure. We also discuss the order relations between the users and the providers utility coefficients. Finally, we conduct extensive experiments on smart grid demand response synthetic data with different size. The obtained results demonstrate the scalability of the proposed game model.

Country
Canada
  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    15
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Average
Top 10%