  Accurate and reliable dynamic state quantities of generators are very
important for real-time monitoring and control of the power system. The
emergence of cyber attacks has brought new challenges to the state estimation
of generators. Especially, false data injection (FDI) attacks deteriorate the
accuracy of state estimation by injecting the false data into the measurement
device. In this regard, this paper proposes for the first time an FDI attack
model based on the dynamic state estimation of generators. Firstly, Taylor's
formula was used to linearize the generator's measurement equation. Secondly,
according to the principle that the measurement residuals before and after the
FDI attack are equal, the expressions of the attack vectors were established,
and they were applied to the measurement quantities to avoid the conventional
bad data detection. Thereby, the FDI attacks were successfully implemented.
Then, three attack scenarios were set according to the degree of the FDI
attacks, and they were tested by the cubature Kalman filter (CKF) and the
robust cubature Kalman filter (RCKF). Finally, the simulation results of the
IEEE 9-bus system and the New England 16-machine 68-bus system verify the
effectiveness of the proposed FDI attacks.
