2010 | OriginalPaper | Chapter
Vulnerable Load Bus Identification Using Radial Basis Neural Network
Authors : Gauri Shankar, Bhavik Suthar, R. Balasubramanian, Prince Ashok
Published in: Power Electronics and Instrumentation Engineering
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
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.