Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Detection and Defense Method Against False Data Injection Attacks for Distributed Load Frequency Control System in Microgrid

1.School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China;2.School of Mathematics, Southeast University, Nanjing 211189, China;3.School of Electronic Information and Electrical Engineering, Chengdu University,, Chengdu 610106, China;4.Yonsei Frontier Laboratory, Yonsei University, Seoul 03722, South Korea;5.School of Electrical Engineering, Southeast University, Nanjing 210096, China;6.Department of Mathematics, Nazarbayev University,Nur-Sultan010000, Kazakhstan

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This work was supported in part by the National Natural Science Foundation of China (No. 61973078), in part by the Natural Science Foundation of Jiangsu Province of China (No. BK20231416), and in part by the Zhishan Youth Scholar Program from Southeast University (No. 2242022R40042).

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    In the realm of microgrid (MG), the distributed load frequency control (LFC) system has proven to be highly susceptible to the negative effects of false data injection attacks (FDIAs). Considering the significant responsibility of the distributed LFC system for maintaining frequency stability within the MG, this paper proposes a detection and defense method against unobservable FDIAs in the distributed LFC system. Firstly, the method integrates a bi-directional long short-term memory (BiLSTM) neural network and an improved whale optimization algorithm (IWOA) into the LFC controller to detect and counteract FDIAs. Secondly, to enable the BiLSTM neural network to proficiently detect multiple types of FDIAs with utmost precision, the model employs a historical MG dataset comprising the frequency and power variances. Finally, the IWOA is utilized to optimize the proportional-integral-derivative (PID) controller parameters to counteract the negative impacts of FDIAs. The proposed detection and defense method is validated by building the distributed LFC system in Simulink.

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  • Received:June 10,2023
  • Revised:August 05,2023
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  • Online: May 20,2024
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