  Accurate and reliable estimation of generator's dynamic state vectors in real
time are critical to the monitoring and control of power systems. A robust
Cubature Kalman Filter (RCKF) based approach is proposed for dynamic state
estimation (DSE) of generators under cyber attacks in this paper. First, two
types of cyber attacks, namely false data injection and denial of service
attacks, are modelled and thereby introduced into DSE of a generator by mixing
the attack vectors with the measurement data; Second, under cyber attacks with
different degrees of sophistication, the RCKF algorithm and the Cubature Kalman
Filter (CKF) algorithm are adopted to the DSE, and then the two algorithms are
compared and discussed. The novelty of this study lies primarily in our attempt
to introduce cyber attacks into DSE of generators. The simulation results on
the IEEE 9-bus system and the New England 16-machine 68-bus system verify the
effectiveness and superiority of the RCKF.
