Performance of SAG events using Artificial Neural Network (ANN) / Norfarizani Nordin

This work presents about the performance of voltage sag events by using Artificial Neural Network (ANN). Voltage sag is one of the Power Quality problems which can occur in equipments or even in the transmission line of power system. Voltage sag may occur in many reasons. In Malaysia, the main cause...

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Main Author:	Nordin, Norfarizani
Format:	Thesis
Language:	English
Published:	2013
Online Access:	https://ir.uitm.edu.my/id/eprint/84478/1/84478.pdf
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id	my-uitm-ir.84478
record_format	uketd_dc
spelling	my-uitm-ir.844782024-03-12T06:55:00Z Performance of SAG events using Artificial Neural Network (ANN) / Norfarizani Nordin 2013 Nordin, Norfarizani This work presents about the performance of voltage sag events by using Artificial Neural Network (ANN). Voltage sag is one of the Power Quality problems which can occur in equipments or even in the transmission line of power system. Voltage sag may occur in many reasons. In Malaysia, the main cause of voltage sag to happen is because of lightning. When lightning strikes, it carries a very high current and may cause the voltage to drop. Hence, there will be an energy lost in the site or building. This energy lost and the severity of voltage sag can be measured by finding the value of energy lost and voltage sag score. The energy lost and sag score value in every sag events can be calculated. However, the validity of the calculated data is quite questionable. The performance of voltage sag is shown by the value of voltage sag score and energy lost values. Thus the purpose of this paper is to make comparison between the monitored and calculated data and to show the performance of sag score and energy lost in sag events using Artificial Neural Network (ANN)-MATLAB. In order to test the validity of sag score and energy lost, two methods were used in this project; first by calculating voltage sag score and its energy lost during sag event from monitored and captured data, and second method is by feeding the calculated data into the artificial neural network. The network is trained using the data on sag duration and three phase voltages Vi, V2 and V3 as the input, while the energy lost and voltage sag score are used to be the targeted output. Results of calculated data will be compared with the results obtained using ANN. It is hoped that the validity of the calculated sag score and energy lost during sag are accurate for monitoring purposes. 2013 Thesis https://ir.uitm.edu.my/id/eprint/84478/ https://ir.uitm.edu.my/id/eprint/84478/1/84478.pdf text en public degree Universiti Teknologi Mara (UiTM) Faculty Electrical Engineering Serwan, Mohd Salleh
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Serwan, Mohd Salleh
description	This work presents about the performance of voltage sag events by using Artificial Neural Network (ANN). Voltage sag is one of the Power Quality problems which can occur in equipments or even in the transmission line of power system. Voltage sag may occur in many reasons. In Malaysia, the main cause of voltage sag to happen is because of lightning. When lightning strikes, it carries a very high current and may cause the voltage to drop. Hence, there will be an energy lost in the site or building. This energy lost and the severity of voltage sag can be measured by finding the value of energy lost and voltage sag score. The energy lost and sag score value in every sag events can be calculated. However, the validity of the calculated data is quite questionable. The performance of voltage sag is shown by the value of voltage sag score and energy lost values. Thus the purpose of this paper is to make comparison between the monitored and calculated data and to show the performance of sag score and energy lost in sag events using Artificial Neural Network (ANN)-MATLAB. In order to test the validity of sag score and energy lost, two methods were used in this project; first by calculating voltage sag score and its energy lost during sag event from monitored and captured data, and second method is by feeding the calculated data into the artificial neural network. The network is trained using the data on sag duration and three phase voltages Vi, V2 and V3 as the input, while the energy lost and voltage sag score are used to be the targeted output. Results of calculated data will be compared with the results obtained using ANN. It is hoped that the validity of the calculated sag score and energy lost during sag are accurate for monitoring purposes.
format	Thesis
qualification_level	Bachelor degree
author	Nordin, Norfarizani
spellingShingle	Nordin, Norfarizani Performance of SAG events using Artificial Neural Network (ANN) / Norfarizani Nordin
author_facet	Nordin, Norfarizani
author_sort	Nordin, Norfarizani
title	Performance of SAG events using Artificial Neural Network (ANN) / Norfarizani Nordin
title_short	Performance of SAG events using Artificial Neural Network (ANN) / Norfarizani Nordin
title_full	Performance of SAG events using Artificial Neural Network (ANN) / Norfarizani Nordin
title_fullStr	Performance of SAG events using Artificial Neural Network (ANN) / Norfarizani Nordin
title_full_unstemmed	Performance of SAG events using Artificial Neural Network (ANN) / Norfarizani Nordin
title_sort	performance of sag events using artificial neural network (ann) / norfarizani nordin
granting_institution	Universiti Teknologi Mara (UiTM)
granting_department	Faculty Electrical Engineering
publishDate	2013
url	https://ir.uitm.edu.my/id/eprint/84478/1/84478.pdf
_version_	1794192005093392384

Performance of SAG events using Artificial Neural Network (ANN) / Norfarizani Nordin

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