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An Effective Hybrid-Energy Framework for Grid Vulnerability Alleviation under Cyber-Stealthy Intrusions

Author

Listed:
  • Abdulaziz Almalaq

    (Department of Electrical Engineering, Engineering College, University of Ha’il, Ha’il 55476, Saudi Arabia)

  • Saleh Albadran

    (Department of Electrical Engineering, Engineering College, University of Ha’il, Ha’il 55476, Saudi Arabia)

  • Amer Alghadhban

    (Department of Electrical Engineering, Engineering College, University of Ha’il, Ha’il 55476, Saudi Arabia)

  • Tao Jin

    (Department of Electrical Engineering, Fuzhou University, Fuzhou 350116, China)

  • Mohamed A. Mohamed

    (Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61519, Egypt)

Abstract

In recent years, the occurrence of cascading failures and blackouts arising from cyber intrusions in the underlying configuration of power systems has increasingly highlighted the need for effective power management that is able to handle this issue properly. Moreover, the growing use of renewable energy resources demonstrates their irrefutable comparative usefulness in various areas of the grid, especially during cascading failures. This paper aims to first identify and eventually protect the vulnerable areas of these systems by developing a hybrid structure-based microgrid against malicious cyber-attacks. First, a well-set model of system vulnerability indices is presented to indicate the generation unit to which the lines or buses are directly related. Indeed, we want to understand what percentage of the grid equipment, such as the lines, buses, and generators, are vulnerable to the outage of lines or generators arising from cyber-attacks. This can help us make timely decisions to deal with the reduction of the vulnerability indices in the best way possible. The fact is that employing sundry renewable resources in efficient areas of the grid can remarkably improve system vulnerability mitigation effectiveness. In this regard, this paper proposes an outstanding hybrid-energy framework of AC/DC microgrids made up of photovoltaic units, wind turbine units, tidal turbine units, and hydrogen-based fuel cell resources, all of which are in grid-connect mode via the main grid, with the aim to reduce the percentage of the system that is vulnerable. To clearly demonstrate the proposed solution’s effectiveness and ease of use in the framework, a cyber-attack of the false data injection (FDI) type is modeled and developed on the studied system to corrupt information (for instance, via settings on protective devices), leading to cascading failures or large-scale blackouts. Another key factor that can have a profound impact on the unerring vulnerability analysis concerns the uncertainty parameters that are modeled by the unscented transform (UT) in this study. From the results, it can be inferred that vulnerability percentage mitigation can be achieved by the proposed hybrid energy framework based on its effectiveness in the system against the modeled cyber-attacks.

Suggested Citation

  • Abdulaziz Almalaq & Saleh Albadran & Amer Alghadhban & Tao Jin & Mohamed A. Mohamed, 2022. "An Effective Hybrid-Energy Framework for Grid Vulnerability Alleviation under Cyber-Stealthy Intrusions," Mathematics, MDPI, vol. 10(14), pages 1-20, July.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:14:p:2510-:d:866253
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    References listed on IDEAS

    as
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    Cited by:

    1. Abdulaziz Almalaq & Saleh Albadran & Mohamed A. Mohamed, 2022. "Deep Machine Learning Model-Based Cyber-Attacks Detection in Smart Power Systems," Mathematics, MDPI, vol. 10(15), pages 1-16, July.
    2. Abdulaziz Almalaq & Saleh Albadran & Mohamed A. Mohamed, 2023. "An Adoptive Miner-Misuse Based Online Anomaly Detection Approach in the Power System: An Optimum Reinforcement Learning Method," Mathematics, MDPI, vol. 11(4), pages 1-22, February.

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