Detection of Power Quality Disturbances Using Discrete Wavelet Transform

Abstract

Identification and classification of voltage and current disturbances in power systems are important tasks in the monitoring and protection of power system.Most power quality disturbances are non-stationary and transitory and the detection and classification have proved to be very demanding.The concept of discrete wavelet transform for feature extraction of power quality disturbance signal as a powerful tool for detecting of power quality disturbance.This paper employs a discrete wavelet transform (DWT) to have a better power quality disturbance detection accuracy.The disturbances of interest include voltage sag, voltage swell, transient, fluctuation, interruption and normal.The discrete wavelet transform has been used to detect and analyse the power quality disturbances.The disturbances of interest includes voltage sag, voltage swell, transient, interruption, fluctuation, and normal disturbance.The system is modelled using MATLAB Simulink.The disturbance voltage waveform is obtained from disturbance generation model.The DWT has been chosen for feature extraction.The outputs of the feature extraction are the DWT coefficients (detailed and approximate) represents the power quality disturbance signal at different levels in time and frequency domain.