Analysis on classification of power quality disturbances using wavelet transform / Yasmin Ahmad Kushairi

• Main Author: Ahmad Kushairi, Yasmin
• Format: Thesis
• Language: English
• Published: 2011
• Online Access: https://ir.uitm.edu.my/id/eprint/84606/1/84606.pdf; https://ir.uitm.edu.my/id/eprint/84606/

This paper presents Wavelet Transform as one of the method to classify power quality disturbances. The objectives of conducting this project are to characterize and classify the power quality disturbances and also to study that Wavelet Transform can characterize and classify power quality disturbances. This technique is using Symlets and Daubechies Wavelet family to extract the signal of the disturbance for classification process. The types of disturbance that is being analyzed in this project are transients and voltage sags. The data which contain power quality disturbances has been analyzed to show the effectiveness of the proposed technique. The proposed technique involves Discrete Wavelet Transform (DWT) analysis and the process of multilevel decomposition and reconstruction at level 3. The result obtained shows that wavelet transform manage to characterize and classify the power quality disturbances and have the accuracy of 87.5% in characterizing and classifying power quality disturbances.