Detection of voltage disturbances in power quality using wavelet transforms
Power quality has cause a great concern to electric utilities with the growing use of sensitive and susceptive electronic and computing equipment. The best analysis on power quality is vital to provide better service to customers. This paper presents the detection of voltage sag and voltage swell...
Saved in:
主要作者: | |
---|---|
格式: | Thesis |
語言: | English |
出版: |
2012
|
主題: | |
在線閱讀: | http://eprints.uthm.edu.my/2340/1/24p%20NOR%20ASRINA%20RAMLEE.pdf |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
id |
my-uthm-ep.2340 |
---|---|
record_format |
uketd_dc |
spelling |
my-uthm-ep.23402022-02-03T01:48:51Z Detection of voltage disturbances in power quality using wavelet transforms 2012-07 Ramlee, Nor Asrina TK Electrical engineering. Electronics Nuclear engineering TK1001-1841 Production of electric energy or power. Powerplants. Central stations Power quality has cause a great concern to electric utilities with the growing use of sensitive and susceptive electronic and computing equipment. The best analysis on power quality is vital to provide better service to customers. This paper presents the detection of voltage sag and voltage swell event using four types of mother wavelet namely Haar, Dmey, Daubechies and Symlet to identify the most accurate mother. The method is developed by applying time domain signal analysis using Discrete Wavelet Transform (DWT) as a detection tool in MATLAB. The actual interrupted signals were obtained from 22kv transmission line in Skudai, Johor Bahru. They will be decomposed through the wavelet mothers. The best mother is the one that capable to detect the time location of the event accurately 2012-07 Thesis http://eprints.uthm.edu.my/2340/ http://eprints.uthm.edu.my/2340/1/24p%20NOR%20ASRINA%20RAMLEE.pdf text en public mphil masters Universiti Tun Hussein Malaysia Fakulti Kejuruteraan Elektrik dan Elektronik |
institution |
Universiti Tun Hussein Onn Malaysia |
collection |
UTHM Institutional Repository |
language |
English |
topic |
TK Electrical engineering Electronics Nuclear engineering TK Electrical engineering Electronics Nuclear engineering |
spellingShingle |
TK Electrical engineering Electronics Nuclear engineering TK Electrical engineering Electronics Nuclear engineering Ramlee, Nor Asrina Detection of voltage disturbances in power quality using wavelet transforms |
description |
Power quality has cause a great concern to electric utilities with the growing use of
sensitive and susceptive electronic and computing equipment. The best analysis on
power quality is vital to provide better service to customers. This paper presents the
detection of voltage sag and voltage swell event using four types of mother wavelet
namely Haar, Dmey, Daubechies and Symlet to identify the most accurate mother.
The method is developed by applying time domain signal analysis using Discrete
Wavelet Transform (DWT) as a detection tool in MATLAB. The actual interrupted
signals were obtained from 22kv transmission line in Skudai, Johor Bahru. They will
be decomposed through the wavelet mothers. The best mother is the one that capable
to detect the time location of the event accurately |
format |
Thesis |
qualification_name |
Master of Philosophy (M.Phil.) |
qualification_level |
Master's degree |
author |
Ramlee, Nor Asrina |
author_facet |
Ramlee, Nor Asrina |
author_sort |
Ramlee, Nor Asrina |
title |
Detection of voltage disturbances in power quality using wavelet transforms |
title_short |
Detection of voltage disturbances in power quality using wavelet transforms |
title_full |
Detection of voltage disturbances in power quality using wavelet transforms |
title_fullStr |
Detection of voltage disturbances in power quality using wavelet transforms |
title_full_unstemmed |
Detection of voltage disturbances in power quality using wavelet transforms |
title_sort |
detection of voltage disturbances in power quality using wavelet transforms |
granting_institution |
Universiti Tun Hussein Malaysia |
granting_department |
Fakulti Kejuruteraan Elektrik dan Elektronik |
publishDate |
2012 |
url |
http://eprints.uthm.edu.my/2340/1/24p%20NOR%20ASRINA%20RAMLEE.pdf |
_version_ |
1747830941939662848 |