Optimal Scheduling Analysis of Wind Farm Group Considering False Data Injection Attack

As a part of the automatic dispatching system, the deep coupling of the information layer and the physical layer makes the operation and control of the dispatching system more and more dependent on the data collected on the information side. Cyber attacks on the information side can change the optimal active power allocation of scheduling, and even affect the stability of power system. In view of this, based on the existing wind farm group scheduling model, this paper uses Gaussian white noise to simulate False Data Injection Attack. Through data comparison, it is concluded that the power fluctuation of wind farm group is aggravated, the distribution proportion imbalance and other negative effects are obtained. In view of this negative effect, a defense scheme that is weakened in three aspects of prediction, predistribution and model adjustment is proposed. Finally, the feasibility and effectiveness of this scheme are verified by simulation of a wind farm group scheduling system in Northeast China.