The authors present an automatic classification of different power quality (PQ) disturbances using

wavelet packet transform (WPT) and fuzzy k-nearest neighbour (FkNN) based classifier. The training data

samples are generated using parametric models of the PQ disturbances. The features are extracted using

some of the statistical measures on the WPT coefficients of the disturbance signal when decomposed upto

the fourth level. These features are given to the fuzzy k-NN for effective classification.