Detection and Classification of Power Quality Disturbances Using Discrete Wavelet Transform and Rule Based Decision Tree

This paper presents a method for the detection and classification of power quality (PQ) disturbances using discrete wavelet transform (DWT) based decision tree. The power quality disturbances are generated with the help of MATLAB using the mathematical relations as per IEEE Standard-1159. The investigated PQ disturbances include pure sine wave, voltage sag, voltage swell, momentary interruption, harmonics, oscillatory transient, impulsive transient and notch. These power quality signals are decomposed using discrete wavelet transform with db4 as mother wavelet up to third level of decomposition. The detail coefficients and approximation coefficients are used for the detection of PQ disturbances. The features extracted from these coefficients are fed to the rule-based decision tree for classification purpose. The effectiveness of proposed algorithm has been established by testing the 30 data sets of each PQ disturbance obtained by varying the parameters.