Detection of False Data Injection Attack in PMU-based Power Grid Using Kalman Filter

Cyber-attacks have become a serious threat to the power grid by expanding the use of communication networks and cyber-physical systems in power systems. due to the connection between communication networks (cyber layer) and Power Grids (physical layer), state estimation of power systems is vulnerable to cyber- attacks. In this paper, state estimation in the power system without any cyber-attacks has occurred, then the detection of false data injection attack power grid when the measurements made by phasor measurement unit (PMU), and the dynamic estimation of the system state variables are estimated by Estimator Kalman. The attack is applied to the communication channels between the PMU and the state estimator. The proposed method which is based on the Kalman filter and the Euclidean distance detector has a good performance in detection of complex attacks such as a false data injection attack. The effectiveness of the proposed method is shown by simulating false data injection attacks on the IEEE 14-bus system. The impact of the FDI attack on the state estimation system and the effectiveness of the proposed method is shown detection of attacks in an IEEE 14-bus system is shown.