Detection and classification of power quality disturbances using wavelet transform, fuzzy logic and neural network

This paper presents an approach for detection and classification of power quality disturbances using wavelet transform, fuzzy logic and neural network. The total harmonic distortion (THD) and energy of the disturb signals are used for classification. A maiden attempt is made to apply a new tool called neuro solution for artificial neural network (ANN) in the field of power quality disturbance classification. A comparison of fuzzy logic and neural network for disturbance classification has been made. Comparison of these two techniques reveals that ANN is more accurate and efficient than the fuzzy logic.