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Dynamic game-based defensive primary frequency control system considering intelligent attackers

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  • Ding, Zhetong
  • Chen, Chunyu
  • Cui, Mingjian
  • Bi, Wenjun
  • Chen, Yang
  • Li, Fangxing

Abstract

Due to cyber security vulnerabilities of electrical cyber physical systems, cyber attacks against frequency-active power controllers become an emerging problem. Cyber attack-tolerant frequency control strategies are thus presented to reduce abnormal frequency excursions. These strategies mainly treat attackers as ‘dumb’ agents. However, attackers in some situations are more like ‘intelligent’ agents with initiative, who can actively and purposefully respond by considering actions of defenders. In this paper, this actively confrontational interaction is modeled by a dynamic game. We propose two types of game scenarios in the primary frequency control system. Improved Nash equilibrium-based defending strategies are studied using reinforcement learning algorithms. By testing the proposed dynamic game-based strategies on the benchmark system, the validity is verified. The proposed analytical procedure concerning dynamic games can also be extended to the study of other industrial control applications.

Suggested Citation

  • Ding, Zhetong & Chen, Chunyu & Cui, Mingjian & Bi, Wenjun & Chen, Yang & Li, Fangxing, 2021. "Dynamic game-based defensive primary frequency control system considering intelligent attackers," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:reensy:v:216:y:2021:i:c:s0951832021004774
    DOI: 10.1016/j.ress.2021.107966
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    References listed on IDEAS

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    Cited by:

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    2. Berghout, Tarek & Benbouzid, Mohamed, 2022. "EL-NAHL: Exploring labels autoencoding in augmented hidden layers of feedforward neural networks for cybersecurity in smart grids," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    3. Liu, Xuan & Meng, Huixing & An, Xu & Xing, Jinduo, 2024. "Integration of functional resonance analysis method and reinforcement learning for updating and optimizing emergency procedures in variable environments," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    4. Diao, Xiaoxu & Zhao, Yunfei & Smidts, Carol & Vaddi, Pavan Kumar & Li, Ruixuan & Lei, Hangtian & Chakhchoukh, Yacine & Johnson, Brian & Blanc, Katya Le, 2024. "Dynamic probabilistic risk assessment for electric grid cybersecurity," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    5. Zhang, Xi & Liu, Dong & Tu, Haicheng & Tse, Chi Kong, 2022. "An integrated modeling framework for cascading failure study and robustness assessment of cyber-coupled power grids," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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