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Game Design and Analysis for Price based Demand Response: An Aggregate Game Approach

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  • Maojiao Ye
  • Guoqiang Hu

Abstract

In this paper, an aggregate game approach is proposed for the modeling and analysis of energy consumption control in smart grid. Since the electricity user's cost function depends on the aggregate load, which is unknown to the end users, an aggregate load estimator is employed to estimate it. Based on the communication among the users about their estimations on the aggregate load, Nash equilibrium seeking strategies are proposed for the electricity users. By using singular perturbation analysis and Lyapunov stability analysis, a local convergence result to the Nash equilibrium is presented for the energy consumption game that may have multiple Nash equilibria. For the energy consumption game with a unique Nash equilibrium, it is shown that the players' strategies converge to the Nash equilibrium non-locally. More specially, if the unique Nash equilibrium is an inner Nash equilibrium, then the convergence rate can be quantified. Energy consumption game with stubborn players is also investigated. Convergence to the best response strategies for the rational players is ensured. Numerical examples are provided to verify the effectiveness of the proposed methods.

Suggested Citation

  • Maojiao Ye & Guoqiang Hu, 2015. "Game Design and Analysis for Price based Demand Response: An Aggregate Game Approach," Papers 1508.02636, arXiv.org, revised Feb 2016.
  • Handle: RePEc:arx:papers:1508.02636
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    Cited by:

    1. Liang, Yile & Liu, Feng & Wang, Cheng & Mei, Shengwei, 2017. "Distributed demand-side energy management scheme in residential smart grids: An ordinal state-based potential game approach," Applied Energy, Elsevier, vol. 206(C), pages 991-1008.
    2. Xupeng Wei & Achilleas Anastasopoulos, 2021. "Mechanism Design for Demand Management in Energy Communities," Games, MDPI, vol. 12(3), pages 1-34, July.
    3. Alasseri, Rajeev & Tripathi, Ashish & Joji Rao, T. & Sreekanth, K.J., 2017. "A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 617-635.
    4. Raman, Gururaghav & Zhao, Bo & Peng, Jimmy Chih-Hsien & Weidlich, Matthias, 2022. "Adaptive incentive-based demand response with distributed non-compliance assessment," Applied Energy, Elsevier, vol. 326(C).
    5. Alasseri, Rajeev & Rao, T. Joji & Sreekanth, K.J., 2020. "Institution of incentive-based demand response programs and prospective policy assessments for a subsidized electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).

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