Detection of voltage disturbances in power quality using wavelet transforms

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...

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Main Author: Ramlee, Nor Asrina
Format: Thesis
Language:English
Published: 2012
Subjects:
TK Electrical engineering
Electronics Nuclear engineering
Online Access:http://eprints.uthm.edu.my/2340/1/24p%20NOR%20ASRINA%20RAMLEE.pdf
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id my-uthm-ep.2340
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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

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