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Kalman filters and observers are two main classes of dynamic state estimation(DSE) routines. Power system DSE has been implemented by various Kalmanfilters, such as the extended Kalman filter (EKF) and the unscented Kalmanfilter (UKF). In this paper, we discuss two challenges for an effective powersystem DSE: (a) model uncertainty and (b) potential cyber attacks. To addressthis, the cubature Kalman filter (CKF) and a nonlinear observer are introducedand implemented. Various Kalman filters and the observer are then tested on the16-machine, 68-bus system given realistic scenarios under model uncertainty anddifferent types of cyber attacks against synchrophasor measurements. It isshown that CKF and the observer are more robust to model uncertainty and cyberattacks than their counterparts. Based on the tests, a thorough qualitativecomparison is also performed for Kalman filter routines and observers.

Comparing Kalman Filters and Observers for Power System Dynamic State Estimation with Model Uncertainty and Malicious Cyber Attacks