Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad

Power Quality disturbances problems have gained widespread interest worldwide due to the proliferation of power electronic load such as adjustable speed drives, computer, industrial drives, communication and medical equipments. This paper presents a technique based on wavelet and probabilistic neura...

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Main Authors:	Hamzah, Noraliza, W. Abdullah, W. Norainin, Mohd Arsad, Pauziah
Format:	Article
Language:	English
Published:	Institute of Research, Development and Commercialisation (IRDC) 2005
Subjects:	Wavelets (Mathematics) Malaysia
Online Access:	http://ir.uitm.edu.my/id/eprint/12803/ http://ir.uitm.edu.my/id/eprint/12803/1/AJ_NORALIZA%20HAMZAH%20SRJ%2005%201.pdf

id	uitm-12803
recordtype	eprints
spelling	uitm-128032016-05-26T06:52:06Z http://ir.uitm.edu.my/id/eprint/12803/ Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad Hamzah, Noraliza W. Abdullah, W. Norainin Mohd Arsad, Pauziah Wavelets (Mathematics) Malaysia Power Quality disturbances problems have gained widespread interest worldwide due to the proliferation of power electronic load such as adjustable speed drives, computer, industrial drives, communication and medical equipments. This paper presents a technique based on wavelet and probabilistic neural network to detect and classify power quality disturbances, which are harmonic, voltage sag, swell and oscillatory transient. The power quality disturbances are obtained from the waveform data collected from premises, which include the UiTM Sarawak, Faculty of Science Computer in Shah Alam, Jati College, Menara UiTM, PP Seksyen 18 and Putra LRT. Reliable Power Meter is used for data monitoring and the data is further processed using the Microsoft Excel software. From the processed data, power quality disturbances are detected using the wavelet technique. After the disturbances being detected, it is then classified using the Probabilistic Neural Network. Sixty data has been chosen for the training of the Probabilistic Neural Network and ten data has been used for the testing of the neural network. The results are further interfaced using matlab script code. Results from the research have been very promising which proved that the wavelet technique and Probabilistic Neural Network is capable to be used for power quality disturbances detection and classification. Institute of Research, Development and Commercialisation (IRDC) 2005 Article PeerReviewed text en http://ir.uitm.edu.my/id/eprint/12803/1/AJ_NORALIZA%20HAMZAH%20SRJ%2005%201.pdf Hamzah, Noraliza and W. Abdullah, W. Norainin and Mohd Arsad, Pauziah (2005) Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad. Scientific Research Journal, 2 (2). pp. 25-34. ISSN 1675-7009
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Wavelets (Mathematics) Malaysia
spellingShingle	Wavelets (Mathematics) Malaysia Hamzah, Noraliza W. Abdullah, W. Norainin Mohd Arsad, Pauziah Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad
description	Power Quality disturbances problems have gained widespread interest worldwide due to the proliferation of power electronic load such as adjustable speed drives, computer, industrial drives, communication and medical equipments. This paper presents a technique based on wavelet and probabilistic neural network to detect and classify power quality disturbances, which are harmonic, voltage sag, swell and oscillatory transient. The power quality disturbances are obtained from the waveform data collected from premises, which include the UiTM Sarawak, Faculty of Science Computer in Shah Alam, Jati College, Menara UiTM, PP Seksyen 18 and Putra LRT. Reliable Power Meter is used for data monitoring and the data is further processed using the Microsoft Excel software. From the processed data, power quality disturbances are detected using the wavelet technique. After the disturbances being detected, it is then classified using the Probabilistic Neural Network. Sixty data has been chosen for the training of the Probabilistic Neural Network and ten data has been used for the testing of the neural network. The results are further interfaced using matlab script code. Results from the research have been very promising which proved that the wavelet technique and Probabilistic Neural Network is capable to be used for power quality disturbances detection and classification.
format	Article
author	Hamzah, Noraliza W. Abdullah, W. Norainin Mohd Arsad, Pauziah
author_facet	Hamzah, Noraliza W. Abdullah, W. Norainin Mohd Arsad, Pauziah
author_sort	Hamzah, Noraliza
title	Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad
title_short	Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad
title_full	Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad
title_fullStr	Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad
title_full_unstemmed	Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad
title_sort	classification and identification of power system disturbances using wavalet and artificial neural network technique / noraliza hamzah, w. norainin w. abdullah and pauziah mohd arsad
publisher	Institute of Research, Development and Commercialisation (IRDC)
publishDate	2005
url	http://ir.uitm.edu.my/id/eprint/12803/ http://ir.uitm.edu.my/id/eprint/12803/1/AJ_NORALIZA%20HAMZAH%20SRJ%2005%201.pdf
first_indexed	2023-09-18T22:49:27Z
last_indexed	2023-09-18T22:49:27Z
_version_	1777417445946949632

Classification and identification of power system disturbances using wavalet and artificial neural network technique / Noraliza Hamzah, W. Norainin W. Abdullah and Pauziah Mohd Arsad

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