Prediction of critical generator buses in transient stability using synchrophasor data

Many interconnected power systems are constructed to meet the ever increasing electric power transfer demand and the integration of renewable energy. A disturbance anywhere in such a system will directly influence the power transfer capability of major transfer interfaces, as well as the transient stability margin of the system. An index is proposed to locate the critical buses, which will be used to monitor the transient stability of a power system. Furthermore, a real-time Artificial Neural Network-based prediction model is proposed to allow the operators to predict the post-fault transient oscillation of critical buses by using several samples after fault clearing. The Eastern North American Power System, which has a large penetration of renewable energy, is used as a platform to illustrate the proposed method.