A Power Quality monitoring system using Neural Network

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This paper presents a neural network technology for the detection and classification of the various types of power quality disturbances. Power quality phenomena are short-time problems and of many varieties. Particularly, the transients happen during very short durations to the nano- and microsecond. Thus, a method for detecting ·md classifying transient signals at the same time and in an automatic combines the properties of the wavelet transform and the advantages of neural networks. We test two neural network and compare the results of Backpropagation Neural (BPN) network with Radial basis function network (RBFN). RBFN is more useful to detect and classify than BPN. The configuration of the hardware of PQ-DAS and some case studies are described.