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Fully decentralized multi-agent coordination scheme in smart distribution restoration: Multilevel consensus

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  • Sadeghi, M.
  • Kalantar, M.

Abstract

Multi-agent systems (MAS) are emerging as a promising approach for smart power system restoration. After a fault has been detected and isolated, the maximum out-of-service loads should be restored in a timely manner. This study aims to develop reliable restoration through autonomous, rapid, and stable communication. For this purpose, a multilevel consensus is suggested to coordinate MAS in a fully decentralized fashion. System dynamics emerge in a distributed manner based on the state vectors of the agent and its proximate neighbors. The information matrix (IM) is used by the agents to accumulate and exchange state vectors encompassing common variable interests. In order to weight the influence of agents on voting, an optimized weighting model (Optw) is proposed. The parameters are bound by Lyapunov's assessment to ensure consensus and then optimized for quick convergence. The proposed multilevel topology supports parallel information discovery in local bunches and provides extremely quick convergence. The suggested one-by-one communication architecture facilitates the exchange of information since each agent only interacts with four of its neighbors. The redundant communication prevents a single point of failure. These achievements make it suitable for application in large-scale power systems. The effectiveness of the affirmation method is revealed through numerical simulation in various scenarios.

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  • Sadeghi, M. & Kalantar, M., 2023. "Fully decentralized multi-agent coordination scheme in smart distribution restoration: Multilevel consensus," Applied Energy, Elsevier, vol. 350(C).
    • Handle: RePEc:eee:appene:v:350:y:2023:i:c:s0306261923009704
    DOI: 10.1016/j.apenergy.2023.121606
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    2. Luo, Zhiqiang & Liu, Hui & Wang, Ni & Zhao, Teyang & Tian, Jiarui, 2024. "Optimal adaptive decentralized under-frequency load shedding for islanded smart distribution network considering wind power uncertainty," Applied Energy, Elsevier, vol. 365(C).

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