A Data-Driven Approach for Generator Rejection Prediction to Prevent Transient Instability in Power System Using Wide-Area Measurements

Because calculating the total amount of generator rejection and assigning the optimal amount of tripping to each generating facility is a time-consuming process, using the optimal generator tripping calculation might be impractical for a real-life interconnected power system. Communication delays also deteriorate the efficiency of any wide-area remedial control action (RCA) in response to fault events, which quickly evolve into transient instability.

In a paper published in IEEE Access Volume 10, engineers from EPE presented a novel data-driven approach to predict generator rejection/tripping and prevent transient instability in power systems. The framework presented in the study predicted the optimal generator rejection for critical generators based on voltage data of generator terminals before and after the occurrence of the contingency. The obtained results showed the effectiveness of the proposed framework in responding to critical fault events in real-time.

Visit IEEE’s website to read more about the proposed framework.