Abstract
This paper presents a study on effectiveness of artificial neural network in estimating the voltage instability. An ANN model based on radial basis function is designed to predict accurately the voltage collapse phenomenon. In the present study, L-index is used as the voltage collapse proximity indicators. ANN model using radial basis function is trained to identify vulnerable buses in power system which contributes maximally in bringing system to the point of voltage collapse. Modeling is done using a sample 5-bus system and results obtained are quite promising with minimum error in predicting voltage collapse.
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Shankar, G., Suthar, B., Balasubramanian, R., Ashok, P. (2010). Vulnerable Load Bus Identification Using Radial Basis Neural Network. In: Das, V.V., Stephen, J., Thankachan, N. (eds) Power Electronics and Instrumentation Engineering. PEIE 2010. Communications in Computer and Information Science, vol 102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15739-4_16
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DOI: https://doi.org/10.1007/978-3-642-15739-4_16
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