Measurement and Classification of Power Quality Disturbances Using Wavelet Based Neural Network

Vol. 3  Issue 4
Year: 2016
Issue:Nov-Jan
Title:Measurement and Classification of Power Quality Disturbances Using Wavelet Based Neural Network
Author Name:S. Deb and S. Patra
Synopsis:

This paper presents an approach for measuring and classifying power quality disturbances using discrete wavelet transform and artificial neural network. The various power quality events are considered they are voltage sag, swell, harmonics, sag with harmonics, swell with harmonics and interruption. Due to the power quality disturbances, the signal is distorted. The energy of the distorted signal is first evaluated with the help of the Multi-Resolution Analysis (MRA) technique of Discrete Wavelet Transform (DWT) and the Parseval's theorem. Second, the energy deviation of the distorted signal with respect to pure sinusoidal signal is at different levels calculated. From these energy features and transient duration the artificial neural network classifies and identifies the disturbances.