ABSTRACT
In this chapter, an original, easy approach is proposed based on probabilistic neural network and discrete wavelet transform for categorization of different switching transients. A precise and consistent power transient classifier is established to classify such transient signals. DWT is used to calculate the level 1 (Qdet1) and 3 (Qdet3) comprehensive reactive power utilized as the artificial neural network model input. A probabilistic neural network is utilized as classifier. Its reliability as well as the validity of numerous case studies are tested, which indicates that this method is ideal for classifying the transients in power system networks.
