Transient Stability Analysis Using MATLAB Simulink and Neural Network

In this paper a Neural Networks (NN) is proposed for transient stability prediction. Transient stability of a power system is first determined based on the generator relative rotor angles procured from time domain simulation outputs. Simulations were carried out on a single machine infinite bus system by considering three phase short circuit fault on the system. The data collected from the time domain simulations are then used as inputs to the NN in which NN is used as a classifier to determine whether the power system is stable or unstable. To verify the effectiveness of the proposed NN method, it is compared with the probabilistic Neural Networks (PNN) and the MultiLayer Perceptrons Neural Networks (MLP). Results show that the NN gives more accurate transient stability assessment compared to the probabilistic neural network and multilayer perceptrons neural networks in terms of classification results.