Abstract
The problem of transient stability of power system is one of the most actively studied nowadays. Classifiers have been applied to the transient stability assessment (TSA) and shown great potential. This paper proposed an adaptive combined classifier based on back-propagation neural network (BPNN) and support vector machine (SVM). In this method, gray area with low accuracy was found by output of BPNN, but it can be improved in SVM. Experiment results on New England system demonstrate the accuracy and speed of proposed classifier.
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