Detection and Defense Method Against False Data Injection Attacks for Distributed Load Frequency Control System in Microgrid
Zhang Z. Hu J. Lu J. Yu J. Cao J. Kashkynbayev A.
1 May 2024State Grid Electric Power Research Institute Nanjing Branch
Journal of Modern Power Systems and Clean Energy
2024#12Issue 3913 - 924 pp.
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.
bi-directional long short-term memory (BiLSTM) neural network , detection and defense , false data injection attack , improved whale optimization algorithm (IWOA) , load frequency control , Microgrid
Text of the article Перейти на текст статьи
School of Cyber Science and Engineering, Southeast University, Nanjing, 210096, China
School of Mathematics, Southeast University, Nanjing, 211189, China
School of Electronic Information and Electrical Engineering, Chengdu University, Chengdu, 610106, China
School of Electrical Engineering, Southeast University, Nanjing, 210096, China
Yonsei University, Yonsei Frontier Laboratory, Seoul, 03722, South Korea
Nazarbayev University, Department of Mathematics, Nur-Sultan, 010000, Kazakhstan
School of Cyber Science and Engineering
School of Mathematics
School of Electronic Information and Electrical Engineering
School of Electrical Engineering
Yonsei University
Nazarbayev University
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026