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Distributed Anomaly Detection in Modern Power Systems: A Penalty-based Mitigation Approach

arXiv.org, 2024-02

2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2402.07884

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  • Title:
    Distributed Anomaly Detection in Modern Power Systems: A Penalty-based Mitigation Approach
  • Author: Abadi, Erfan Mehdipour ; Nazari, Masoud H
  • Subjects: Algorithms ; Anomalies ; Computer Science - Systems and Control ; Distributed generation ; Energy sources
  • Is Part Of: arXiv.org, 2024-02
  • Description: The evolving landscape of electric power networks, influenced by the integration of distributed energy resources require the development of novel power system monitoring and control architectures. This paper develops algorithm to monitor and detect anomalies of different parts of a power system that cannot be measured directly, by applying neighboring measurements and a dynamic probing technique in a distributed fashion. Additionally, the proposed method accurately assesses the severity of the anomaly. A decision-making algorithm is introduced to effectively penalize anomalous agents, ensuring vigilant oversight of the entire power system's functioning. Simulation results show the efficacy of algorithms in distributed anomaly detection and mitigation.
  • Publisher: Ithaca: Cornell University Library, arXiv.org
  • Language: English
  • Identifier: EISSN: 2331-8422
    DOI: 10.48550/arxiv.2402.07884
  • Source: arXiv.org
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