Rotor Angle Stability Prediction using Temporal and Topological Embedding Deep Neural Network Based on Grid-Informed Adjacency Matrix
Published in Get the paper Journal of Modern Power Systems and Clean Energy, 2023
Recommended citation: P.Y. Sun, L. Huo, X. Chen, S.Y. Liang, "Rotor Angle Stability Prediction using Temporal and Topological Embedding Deep Neural Network Based on Grid-Informed Adjacency Matrix," Journal of Modern Power Systems and Clean Energy, 2023.
In this paper we made use of different DL models, trained them using linear power grid model IEEE-39. Then we performed prediction on both linear and nonlinear power grid model, compared the perfromance of different DL models and chose the best one as the final model. In the end, we deployed the chosen model on a larger power grid model IEEE-118 and the results were also great, which proved the generality of our method.