Critical clearing time prediction using recurrent neural networks
Komla Agbenyo Folly, Paul Kehinde Olulope, Ganesh Kumar Venayagamoorthy · 2017
In this paper, recurrent neural networks (RNNs) are used in combination with phasor measurement units (PMUs) to predict the critical clearing time of a multi-machine power system in real-time. RNNs make use of real-time data from Phasor Measurement Unit (PMU). Simulation results are presented to show the effectiveness of the proposed approach in predicting the critical clearing time.