Open AccessDetection of False Data Injection Attacks Based on Kalman Filter and Controller Design in Power System LFC
Author(s) -
Rujun Zhu,
Chongxin Huang,
Song Deng,
YiChen Li
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1861/1/012120
Subject(s) - kalman filter , computer science , matlab , controller (irrigation) , electric power system , filter (signal processing) , power (physics) , real time computing , control theory (sociology) , control (management) , artificial intelligence , operating system , physics , quantum mechanics , agronomy , biology , computer vision
False data injection attacks pose a great threat to the safe and stable operation of power systems. Therefore, the detection and defense of false data injection attacks in LFC systems is becoming more and more important. First, based on the equivalent model of the LFC system and the Kalman filter algorithm, this paper proposes a false data injection attack detection method; secondly, a robust controller is used to reduce load disturbances according to the operating characteristics of the LFC system; then the idea of switching links is proposed to reduce the impact of cyberattack on the system; finally, MATLAB/Simulink software is used to carry out simulation tests. The test results verify the effectiveness of the false data injection attack detection method and switch link defense method proposed in this paper.