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    Volume 1, Issue 3, Chinese Journal of Information Fusion
    Volume 1, Issue 3, 2024
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    Yulong Huang
    Yulong Huang
    Harbin Engineering University, China
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    Chinese Journal of Information Fusion, 2024, Volume 1, Issue 3: 212-225

    Free to Read | Research Article | 30 December 2024
    Robust Distributed State Estimation in Power Systems: A Multi-Estimator Data Fusion Approach to Counteract Cyber-Attacks
    by
    IECE Author Shiyu Jin 1
    IECE Author Wen Yang 1 *
    IECE Author Hongbo Yuan 1
    IECE Author Wenjie Ding 1
    IECE Author Han Wu 1
    IECE Author Jie Wang 1
    1 Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
    * Corresponding Author: Wen Yang, [email protected]
    DOI: https://doi.org/10.62762/CJIF.2024.740709
    Received: 11 November 2024, Accepted: 29 December 2024, Published: 30 December 2024  
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    Abstract
    Cyber security in power systems has become increasingly critical with the rise of network attacks such as Denial-of-Service (DoS) attacks and False Data Injection (FDI) attacks. These threats can severely compromise the integrity and reliability of state estimation, which are fundamental to the operation and control of power systems. In this manuscript, an estimation algorithm based on the fusion of information from multiple estimators is proposed to ensure that state estimation at critical buses can function properly in case of attacks. Our approach leverages a network of estimators that can dynamically adjust to maintain system stability and accuracy. Furthermore, a new detector is adopted based on Kullback-Leibler divergence to detect linear FDI attacks. To address stealthy attacks that may evade detection, we propose a novel weighting scheme that reduces the impact of attacks on estimation results. Numerical experiments demonstrate the effectiveness and accuracy of our proposed estimation algorithm under cyber attacks.
    Graphical Abstract
    Robust Distributed State Estimation in Power Systems: A Multi-Estimator Data Fusion Approach to Counteract Cyber-Attacks
    Keywords
    state estimation
    smart grid
    data fusion
    Kullback-Leibler divergence
    cyber attack
    Funding
    This work was supported in part by the National Key R&D Program of China under Grant 2023YFF1204805; in part by the National Natural Science Foundation of China under Grant 62336005, Grant 62122026; in part by the projects sponsored by the Programme of Introducing Talents of Discipline to Universities (the 111 Project) under Grant B17017; and in part by the Shuguang Program supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission.
    Cite This Article
    APA Style
    Jin, S., Yang, W., Yuan, H., Ding, W., Wu, H. & Wang, J. (2024). Robust Distributed State Estimation in Power Systems: A Multi-Estimator Data Fusion Approach to Counteract Cyber-Attacks. Chinese Journal of Information Fusion, 1(3), 212–225. https://doi.org/10.62762/CJIF.2024.740709
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    Chinese Journal of Information Fusion

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    ISSN: 2998-3371 (Online) | ISSN: 2998-3363 (Print)

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