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Secure Load Frequency Control of Smart Grids under Deception Attack: A Piecewise Delay Approach

Author

Listed:
  • Fei Zhao

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Jinsha Yuan

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Ning Wang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Zhang Zhang

    (State Grid Hebei Economic Research Institute, Shijiazhuang 050021, China)

  • Helong Wen

    (State Grid Handan Fengfeng Kuangqu Power Supply Company, Handan 056200, China)

Abstract

The problem of secure load frequency control of smart grids is investigated in this paper. The networked data transmission within the smart grid is corrupted by stochastic deception attacks. First, a unified Load frequency control model is constructed to account for both network-induced effects and deception attacks. Second, with the Lyapunov functional method, a piecewise delay analysis is conducted to study the stability of the established model, which is of less conservativeness. Third, based on the stability analysis, a controller design method is provided in terms of linear matrix inequalities. Finally, a case study is carried out to demonstrate the derived results.

Suggested Citation

  • Fei Zhao & Jinsha Yuan & Ning Wang & Zhang Zhang & Helong Wen, 2019. "Secure Load Frequency Control of Smart Grids under Deception Attack: A Piecewise Delay Approach," Energies, MDPI, vol. 12(12), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2266-:d:239557
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    References listed on IDEAS

    as
    1. Komboigo Charles & Naomitsu Urasaki & Tomonobu Senjyu & Mohammed Elsayed Lotfy & Lei Liu, 2018. "Robust Load Frequency Control Schemes in Power System Using Optimized PID and Model Predictive Controllers," Energies, MDPI, vol. 11(11), pages 1-18, November.
    2. Athanasios Dagoumas, 2019. "Assessing the Impact of Cybersecurity Attacks on Power Systems," Energies, MDPI, vol. 12(4), pages 1-23, February.
    3. Jun Yang & Zhili Zeng & Yufei Tang & Jun Yan & Haibo He & Yunliang Wu, 2015. "Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory," Energies, MDPI, vol. 8(3), pages 1-20, March.
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    Cited by:

    1. Wadi, Mohammed & Shobole, Abdulfetah & Elmasry, Wisam & Kucuk, Ismail, 2024. "Load frequency control in smart grids: A review of recent developments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Marcel Nicola & Claudiu-Ionel Nicola & Dan Selișteanu, 2022. "Improvement of the Control of a Grid Connected Photovoltaic System Based on Synergetic and Sliding Mode Controllers Using a Reinforcement Learning Deep Deterministic Policy Gradient Agent," Energies, MDPI, vol. 15(7), pages 1-32, March.
    3. Athira M. Mohan & Nader Meskin & Hasan Mehrjerdi, 2020. "A Comprehensive Review of the Cyber-Attacks and Cyber-Security on Load Frequency Control of Power Systems," Energies, MDPI, vol. 13(15), pages 1-33, July.
    4. Yixuan Ge & Guobao Liu & Guishu Zhao & Huai Liu & Ji Sun, 2022. "Observer-Based H ∞ Load Frequency Control for Networked Power Systems with Limited Communications and Probabilistic Cyber Attacks," Energies, MDPI, vol. 15(12), pages 1-16, June.
    5. Marcel Nicola & Claudiu-Ionel Nicola, 2021. "Fractional-Order Control of Grid-Connected Photovoltaic System Based on Synergetic and Sliding Mode Controllers," Energies, MDPI, vol. 14(2), pages 1-25, January.

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