Identification of power quality disturbances by using discrete wavelet transformation and RMS analysis
Abstract
This paper focuses on power quality event, detection and classification of power quality disturbances (PQD). The disturbance of interest includes sag, swell, interruption, transient, harmonics, flicker and noise. In order to classify the power disturbances, we use the combination of discrete Wavelet transformation and RMS (Root Mean Square) analysis. A rule-based system for power quality disturbance classification is also developed in which the knowledge base is composed using a set of rules in the form of expertise knowledge from a detailed analysis of the extracted features. The simulation results show that we can detect and identify disturbance quickly and accurately with this method.
Moraref