Power quality events analysis using wavelet transform
With an increasing usage of sensitive electronic equipment, power quality studies had grown to perform power quality data analysis. Wavelet transformation technique was founded to be more appropriate to analyze the various types of power quality events.This project compares the use of various typ...
محفوظ في:
| المؤلف الرئيسي: | |
|---|---|
| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2012
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://eprints.uthm.edu.my/2406/1/24p%20SHIRLEY%20ANAK%20RUFUS.pdf |
| الوسوم: |
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| الملخص: | With an increasing usage of sensitive electronic equipment, power quality studies
had grown to perform power quality data analysis. Wavelet transformation technique
was founded to be more appropriate to analyze the various types of power quality
events.This project compares the use of various types of wavelets at different scales
and levels of decomposition on analyzing real recorded Power quality (PQ) events
from Skudai 22kV distribution system. Voltage sag, voltage swell and transient event
have been tested. PQ events data were extracted by RPM Power Analysis
Softwarebased on a standard curve called as CBEMA curve. Background and
indicators in CBEMA curve were studied, hence various PQ events were able to
identify and analyze. This project also applied the 1-D WPT and 1-D SWTD of
Matlab wavelet toolbox for further analysis the recorded PQ events. In 1-D WPT,
four (4) types of wavelets with Shannon entropy based are applied and aim to
determine the most appropriate mother wavelet for better compression and analyzed
the recorded data of PQ event. Compression of voltage sag and swell waveforms
were carried out with low energy loss capability was verified in order to preserve the
original waveform of PQ event feature for further analysis. Performance of the 1-D
WPT in compression on both voltage sag and swell events is compared based on
Retain Energy (RE) and Number of Zeros (NZ) in percentage for all proposed
wavelets at different scales and levels of decomposition. Ratio of energy loss per
percentage of zero of compressed PQ events was also demonstrated. Compression
using WT was also conducted for comparison.Presence of noise in the PQ events
were de-noised using different mother wavelets at level 3 by varied three (3) types of
noise structure available in 1-D SWTD. Effectiveness of using 1-D SWTD for
analyzing transient, voltage sag and swell events with 3 different noise structures has
been demonstrated by comparing the dispersion and distributionComparison of denoised
waveform
from
WT
was
also
demonstrated. |
|---|