Adaptive distributed Kalman-like filter for power system with cyber attacks

This article investigates the distributed state estimation problem for large-scale power systems, where both false data injection (FDI) and denial-of-service (DoS) attacks are considered. The DoS attacks are compensated by using measurement predictor, while the FDI attacks are treated as uncertainties in measurements. Through neighborhood coordination, a posterior residual chi-square test method is applied in each subsystem to detect the FDI attacks in local measurement and edge measurement separately. Finally, by introducing two adaptive factors, an adaptive distributed state estimator (ADSE) is proposed, which can evaluate the credibility of the tampered measurements and mitigate the impact of FDI attacks. Simulation tests conducted on the IEEE 118-bus system verify the effectiveness of the attack detector and the ADSE in power system state estimation. (C) 2021 Elsevier Ltd. All rights reserved.