Naresh Kumar, Minakshi Hooda, Sunil Kumar
Abstract: This paper presents an ANN based model for predicting stability margin for an asynchronous machine power system prone to voltage instability. Such a model may be employed either for direct prediction of the stability margin based on the existing loading conditions or for forecasting the loading conditions for a future time period and then providing an estimate of the stability margin. The neural networks employed are the multi layer perceptron (MLP) with a second order learning rule and the radial basis function (RBF) network and feed forward neural network. The simulation results for a sample 5-bus system indicate that the ANN models provide a fairly accurate and fast prediction of the stability margin making them, suitable for application in an on-line energy management system.
Keywords: ANN, voltage instability, loading conditions, stability margin, radial basis function