Three Phase Power Quality Disturbance Classification Using S-transform

In this paper s-transform is introduced as an effective method for power quality disturbance recognition. S-transform is a time-frequency analyzes technique that bridges the gap between the short-time Fourier transform and wavelet transform. The features obtained from ST are distinct, understandable and immune to noise. In proposed method by use of s-transform and a decision making algorithm, thirteen types of single Power Quality (PQ) disturbances like sag, swell, interrupt, harmonic, spike, notch, noise, oscillatory transient, flicker, sub-harmonic, DC, inter- harmonic, unbalancy, and two complex disturbances are well recognized. The waves extracted from s-transform let us to investigate PQ disturbances in three phases simultaneously. Therefore disturbances like unbalancy and different sag types can be well recognized. After extracting three features from disturbance signals by means of S-transform, ten distinct indices for each signal will be extracted. By means of these indices and a rule-based decision algorithm various types of PQ disturbances can be classified. For simulation purpose disturbances with random parameters has been produced and for better achiving real conditions they are mixed with noises with different SNR values. It shows that this method can be used for real applications