A new optimal feature selection algorithm for classification of power quality disturbances using discrete wavelet transform and probabilistic neural network
Power quality disturbances are classified using optimal feature selection method. Discrete wavelet transform extracts the set of features successfully. Artificial bee colony has been proposed for the selection of optimal features. 16 types of single and multiple power quality disturbances are classified. Superior results are achieved as compared to the similar existing techniques.