Article ID Journal Published Year Pages File Type
455125 Computers & Electrical Engineering 2012 8 Pages PDF
Abstract

Self-organizing feature map (SOFM) in conjunction with radial basis function (RBF) has been applied in this paper to determine and classify the voltage stability states of a multi-bus power network. Simulations were carried out on a real 203-bus system of an Indian power utility considering load changes and contingencies. The data collected from simulations are then used as inputs to the SOFM which acts as a classifier to classify the voltage stability states of the system under test. To augment the effectiveness of the proposed method, the initial classification results were improved with the application of RBF technique. Studies show that the SOFM–RBF combination delivers high classification accuracy in the order of almost 100% and can be considered an effective soft-computing tool to ease the operation of large-multi bus power network under variable operating conditions.

Graphical abstractFigure optionsDownload full-size imageDownload as PowerPoint slideHighlights► Power system operating states have been classified based on voltage stability. ► Kohonen’s self organizing feature map (SOFM) was used as a classification tool. ► The initial classification results were improved with the application of RBF. ► Studies show that the SOFM–RBF combination delivers high classification accuracy. ► The method could be a useful tool for on-line power system operators.

Related Topics
Physical Sciences and Engineering Computer Science Computer Networks and Communications
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