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Distributed resilient multi-event cooperative triggered mechanism based discrete sliding-mode control for wind-integrated power systems under denial of service attacks

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  • Huo, Zhihong
  • Wang, Bing

Abstract

In wind-integrated power systems (WIPSs), denial of service (DoS) attacks bring about time delays and packages dropout in system data transmission, it may even deteriorate system performance. In order to maintain the reliability and safety of WIPSs, under the dynamical event triggered framework, a novel distributed resilient multi-event cooperative triggered scheme is derived to decrease the occupation of network channel. Furthermore, considering the random load disturbance of WIPSs and wind speed fluctuation, the resilient triggered scheme based H∞ load frequency sliding-mode control strategy is proposed. Based on Lyapunov stability theory, the controller is obtained by solving linear matrix inequality. Compared with the traditional event triggered mechanism, the proposed distributed resilient multi-event cooperative triggered mechanism based sliding-mode controller provides stronger robustness, higher wind energy capture efficiency for WIPSs under DoS attacks. Meanwhile, the resilient triggered scheme improves the utilization efficiency of network resources. A four-area WIPSs is investigated and the numerical analysis shows the proposed strategy is feasibility and effectiveness.

Suggested Citation

  • Huo, Zhihong & Wang, Bing, 2023. "Distributed resilient multi-event cooperative triggered mechanism based discrete sliding-mode control for wind-integrated power systems under denial of service attacks," Applied Energy, Elsevier, vol. 333(C).
    • Handle: RePEc:eee:appene:v:333:y:2023:i:c:s0306261922018931
    DOI: 10.1016/j.apenergy.2022.120636
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    References listed on IDEAS

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    1. Shang-Guan, Xingchen & He, Yong & Zhang, Chuanke & Jiang, Lin & Spencer, Joseph William & Wu, Min, 2020. "Sampled-data based discrete and fast load frequency control for power systems with wind power," Applied Energy, Elsevier, vol. 259(C).
    2. Yang, Hongming & Liang, Rui & Yuan, Yuan & Chen, Bowen & Xiang, Sheng & Liu, Junpeng & Zhao, Huan & Ackom, Emmanuel, 2022. "Distributionally robust optimal dispatch in the power system with high penetration of wind power based on net load fluctuation data," Applied Energy, Elsevier, vol. 313(C).
    3. Deyin Yao & Hamid Reza Karimi & Yiyong Sun & Qing Lu, 2014. "Robust Model Predictive Control of Networked Control Systems under Input Constraints and Packet Dropouts," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-11, July.
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    1. Wang, Jingyao & Li, Yao & Bian, Jiayu & Yu, Zhiyong & Zhang, Min & Wang, Cheng & Bi, Tianshu, 2023. "Multi-stage resilient operation strategy of urban electric–gas system against rainstorms," Applied Energy, Elsevier, vol. 348(C).

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