ABSTRACT

Electrical Power quality (EPQ) or more appropriate word is EPQ disturbances (EPQDs has become a big concern in the recent years with the growing utilization of non-linear loads and power PEs) equipment. EPQ concerns utility and consumers equa11y. The various types of EPQDs are defined and guided by IEEE standards 1159- 2009 in terms of their frequency, magnitude and duration.
In order to improve or to mitigate EPQ problems the detection and classification must be done first. But it is the fact that EPQD varies in a broad range of time-frequency, which makes automatic detection and classification of PQ problems very difficult. Literature indicates that the automatic detection of EPQDs is the most important hot and fashionable area of research in electrical power system.
Nowadays harmonic and transient analysis are very imperative topic in electrical power quality (EPQ) issue. Power system harmonics (PSH) are among very common PQDs and are analyzed with the help of fast Fourier transform (FFT) based index; known as total harmonic distortion (THD) very well.
In signal processing technique, the FFT a11ows signals mapping from time to frequency domain, where signal is decomposed into several components of frequency. In the result time information is totally lost but accuracy of frequency components remains very high. Hence FFT is not suitable for time varying signals like transient (non-stationary signals) where both frequency and time data are required simultaneously. Wavelet Transform (WT) generally offers this facility of time-frequency domain analysis.
In this work power quality analyzer (PQA) has been used to collect the real data of harmonics and transient in order to develop the software models using Matlab/Simulink. These software models are investigated by applying time-frequency technique of discrete wavelet transforms (DWT) with multiresolution analysis (MRA) algorithm and Daubechies (db) as mother wavelet.
This methodology proposes the feature index of WT, named as maximum peak (MP) instead of THD index of FFT, in order to detect the harmonics and transients disturbances. The components of WT based index MP with FFT based index THD show simplicity, accw-acy, and supremacy for the analysis of power quality disturbances.