Classification of power system disturbances through fuzzy neural network

Electric power utilities have launched comprehensive data collection programs to evaluate the power quality problems in their systems. Computerized classification and characterization of the data will help in dealing with voluminous quantities of monitored data. An artificial neural network (ANN) approach with and without a fuzzy system for classifying the disturbances in a power system is developed and tested. The results obtained demonstrate the power of neural networks in classifying the commonly encountered disturbances of sags, swells, waveform distortions, interruptions and impulses and the effect of the fuzzy system on the network.<
>