Real-time power quality detection and classification system

The increasing number of power electronics equipment contributes to the poor quality of electrical power supply and has become a vital concern to electricity users at all levels of usage. The power quality signals can affect manufacturing process, malfunction of equipment and economic losses. Thus,...

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Main Author:	Abidullah, Noor Athira
Format:	Thesis
Language:	English English
Published:	2015
Subjects:	T Technology (General)
Online Access:	http://eprints.utem.edu.my/id/eprint/20608/1/Real-Time%20Power%20Quality%20Signal%20Detection%20And%20Classification%20System.pdf http://eprints.utem.edu.my/id/eprint/20608/2/Real%20time%20power%20quality%20detection%20and%20classification%20system.pdf
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id	my-utem-ep.20608
record_format	uketd_dc
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Abdullah, Abdul Rahim
topic	T Technology (General) T Technology (General)
spellingShingle	T Technology (General) T Technology (General) Abidullah, Noor Athira Real-time power quality detection and classification system
description	The increasing number of power electronics equipment contributes to the poor quality of electrical power supply and has become a vital concern to electricity users at all levels of usage. The power quality signals can affect manufacturing process, malfunction of equipment and economic losses. Thus, it is necessary to detect and classify different kind of power quality signals for rectify failures and ensure quality of power line signal. This research presents the analysis power quality signals using time-frequency distributions (TFDs) which are spectrogram, Gabor transform and S-transform for signals detection and classification. Since the signals consist of multi-frequency components and magnitude variation, the TFDs are very appropriate to be used that represent the signals, jointly, in time-frequency representation (TFR). From the TFR, parameters of the signals are estimated and then are used to identify the characteristics of the signals. Referring to IEEE Std. 1159-2009, the signal characteristics are obtained and then served as the input for signal classifier to classify power quality signals. Based on the analysis, the best TFD is identified in terms of accuracy of the signal characteristics, memory size and computation complexity of data processing and chosen for power quality signals detection and classification system. By simulating in MATLAB, the performance of the classification system is verified by generating and classifying 100 signals with various characteristics for each type of power quality signals. In addition, the system is also tested using 100 real signals which were recorded from a power line. The results show that, S-transform is the best TFD and the classification system gives 100 percent correct classification for all power quality signals. For the real signals, the system also presents 100 percent correct classification. Thus, the outcome of this research shows that the system is very appropriate to be implemented for power quality monitoring system.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Abidullah, Noor Athira
author_facet	Abidullah, Noor Athira
author_sort	Abidullah, Noor Athira
title	Real-time power quality detection and classification system
title_short	Real-time power quality detection and classification system
title_full	Real-time power quality detection and classification system
title_fullStr	Real-time power quality detection and classification system
title_full_unstemmed	Real-time power quality detection and classification system
title_sort	real-time power quality detection and classification system
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty Of Electrical Engineering
publishDate	2015
url	http://eprints.utem.edu.my/id/eprint/20608/1/Real-Time%20Power%20Quality%20Signal%20Detection%20And%20Classification%20System.pdf http://eprints.utem.edu.my/id/eprint/20608/2/Real%20time%20power%20quality%20detection%20and%20classification%20system.pdf
_version_	1747833985136852992
spelling	my-utem-ep.206082022-05-17T16:49:07Z Real-time power quality detection and classification system 2015 Abidullah, Noor Athira T Technology (General) TA Engineering (General). Civil engineering (General) The increasing number of power electronics equipment contributes to the poor quality of electrical power supply and has become a vital concern to electricity users at all levels of usage. The power quality signals can affect manufacturing process, malfunction of equipment and economic losses. Thus, it is necessary to detect and classify different kind of power quality signals for rectify failures and ensure quality of power line signal. This research presents the analysis power quality signals using time-frequency distributions (TFDs) which are spectrogram, Gabor transform and S-transform for signals detection and classification. Since the signals consist of multi-frequency components and magnitude variation, the TFDs are very appropriate to be used that represent the signals, jointly, in time-frequency representation (TFR). From the TFR, parameters of the signals are estimated and then are used to identify the characteristics of the signals. Referring to IEEE Std. 1159-2009, the signal characteristics are obtained and then served as the input for signal classifier to classify power quality signals. Based on the analysis, the best TFD is identified in terms of accuracy of the signal characteristics, memory size and computation complexity of data processing and chosen for power quality signals detection and classification system. By simulating in MATLAB, the performance of the classification system is verified by generating and classifying 100 signals with various characteristics for each type of power quality signals. In addition, the system is also tested using 100 real signals which were recorded from a power line. The results show that, S-transform is the best TFD and the classification system gives 100 percent correct classification for all power quality signals. For the real signals, the system also presents 100 percent correct classification. Thus, the outcome of this research shows that the system is very appropriate to be implemented for power quality monitoring system. 2015 Thesis http://eprints.utem.edu.my/id/eprint/20608/ http://eprints.utem.edu.my/id/eprint/20608/1/Real-Time%20Power%20Quality%20Signal%20Detection%20And%20Classification%20System.pdf text en public http://eprints.utem.edu.my/id/eprint/20608/2/Real%20time%20power%20quality%20detection%20and%20classification%20system.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=106016&query_desc=kw%2Cwrdl%3A%20Real%20time%20power%20quality%20detection%20and%20classification%20system mphil masters Universiti Teknikal Malaysia Melaka Faculty Of Electrical Engineering Abdullah, Abdul Rahim 1. Abdullah, A. R. Nordin, N., Abidin, N. Q. Z., Aman, A., and Jopri, M. H., 2012. 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Real-time power quality detection and classification system

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