Analysis of Voltage Stability Margin and Prediction of Asynchronous Machine using ANN

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

How to Cite?: Naresh Kumar, Minakshi Hooda, Sunil Kumar, "Analysis of Voltage Stability Margin and Prediction of Asynchronous Machine using ANN", Volume 2 Issue 3, March 2013, International Journal of Science and Research (IJSR), Pages: 286-290, https://www.ijsr.net/getabstract.php?paperid=IJSRON2013565, DOI: https://dx.doi.org/10.21275/IJSRON2013565

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