Research On A Method Of Fast Prediction To The Power System’s Transient Stability Based On The Local Real-Time Information Via Wide-Area Measurement

Transient stability is an important issue for the safe operation of power system, its accurate prediction is of great significance. The state prediction based on the wide-area measured phase information can avoid dependence on the accuracy of the system models and parameters, which is an effective way of transient stability prediction.First reviewed the traditional transient stability prediction of the time domain simulation method, the direct method and the hybrid method and the research status is presented in classify form in this paper. The structure, characteristics and application functions of WAMS (Wide Area Measurement System) are also introduced. The online transient stability prediction of multi-machine system is transformed into the transient stability of the by time-section two-machine system, according to the transform theory of complementary-cluster center-of-inertia relative motion, and use the dynamically updated WAMS data to realize the equivalents of the by time-section two cluster.As the small-scale fluctuations of WAMS measured data reduce the reliability of the system prediction model parameter identification, the angle curve extrapolation method ignores the operation mechanism of the system itself, which is lack of robustness. To improve the prediction reliability and robustness and based on the equation of motion for the two-machine system, identify the parameters of dynamic differential equations describing the system transient process and predict the disturbed trajectory. Compared with single machine infinite equivalents system (OMIB) parameter identification gained from RM changes, this method combines the equations of motion of the two clusters, which increase the effective constraint to the identified parameters and enhance the reliability of the identification of the slowly changing time-varying parameters. Compared with the curve fitting method, this approach is consistent with the physical laws of motion, which can identify the by time-section non time-varying parameters and simplify the prediction model and improve the robustness. It is meaningful for the quick identification of the transient stability. The two-machine system simulation results show that the method is a good predictor through a small amount of WAMS measured data.Make composite power angle and composite angular velocity a double criterion, according to the trajectory of the dominant mode and the relationship of the instability mode, composite power angle and composite angular velocity of each size of the gap to cluster. Use the complementary-cluster center-of-inertia relative motion to reduce the order of the system and combined with the above-mentioned the disturbed trajectory prediction method and existing trajectory bump nature transient stability criterion to achieve transient stability of the discrimination. The IEEE 10-machine 39-bus system simulation results show that the transient stability prediction method is guaranteed in speed and reliability.