Voltage stability analysis using artificial neural network / Norul Janah Ahmad

Voltage stability problems have been one of the major concern for electric utilities as a result of heavy loading. This thesis presents the applications of artificial neural network in voltage stability analysis. A multi layer feed forward artificial neural network with error back propagation and me...

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Main Author:	Ahmad, Norul Janah
Format:	Thesis
Language:	English
Published:	1999
Subjects:	Back propagation (Artificial intelligence)
Online Access:	https://ir.uitm.edu.my/id/eprint/78082/1/78082.pdf
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id	my-uitm-ir.78082
record_format	uketd_dc
spelling	my-uitm-ir.780822023-07-25T01:31:17Z Voltage stability analysis using artificial neural network / Norul Janah Ahmad 1999 Ahmad, Norul Janah Back propagation (Artificial intelligence) Voltage stability problems have been one of the major concern for electric utilities as a result of heavy loading. This thesis presents the applications of artificial neural network in voltage stability analysis. A multi layer feed forward artificial neural network with error back propagation and memory-based feed forwards networks based on the estimation probability density functions, general regression neural network are proposed for calculation of voltage stability. Back propagation using three layers and four layers i.e input layer, one hidden layer and output layer while four layer i.e input layer, two hidden layer and output layer are use. General regression using four layers i.e. input layer, hidden layer, division & summation layer and output layer are being applied in predicting voltage stability. Both methods used same sets of data in training process and same other sets of data for testing process. All those sets of data are generated by Fast-Decoupled Load Flow Simulation using fifteen bus system. Real and reactive power at all buses and real and reactive power outputs of generator were applied as inputs to artificial neural network. Test are carried out and the results for this two method are compared. From thr result, it shows that artificial neural network can be used to predict voltage stability of power system. The result also shows that General Regression are more accurate compare to Back propagation method. Back propagation using one hidden layer show good value compare to back propagation using two hidden layer. 1999 Thesis https://ir.uitm.edu.my/id/eprint/78082/ https://ir.uitm.edu.my/id/eprint/78082/1/78082.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Hamzah, Noraliza
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Hamzah, Noraliza
topic	Back propagation (Artificial intelligence)
spellingShingle	Back propagation (Artificial intelligence) Ahmad, Norul Janah Voltage stability analysis using artificial neural network / Norul Janah Ahmad
description	Voltage stability problems have been one of the major concern for electric utilities as a result of heavy loading. This thesis presents the applications of artificial neural network in voltage stability analysis. A multi layer feed forward artificial neural network with error back propagation and memory-based feed forwards networks based on the estimation probability density functions, general regression neural network are proposed for calculation of voltage stability. Back propagation using three layers and four layers i.e input layer, one hidden layer and output layer while four layer i.e input layer, two hidden layer and output layer are use. General regression using four layers i.e. input layer, hidden layer, division & summation layer and output layer are being applied in predicting voltage stability. Both methods used same sets of data in training process and same other sets of data for testing process. All those sets of data are generated by Fast-Decoupled Load Flow Simulation using fifteen bus system. Real and reactive power at all buses and real and reactive power outputs of generator were applied as inputs to artificial neural network. Test are carried out and the results for this two method are compared. From thr result, it shows that artificial neural network can be used to predict voltage stability of power system. The result also shows that General Regression are more accurate compare to Back propagation method. Back propagation using one hidden layer show good value compare to back propagation using two hidden layer.
format	Thesis
qualification_level	Bachelor degree
author	Ahmad, Norul Janah
author_facet	Ahmad, Norul Janah
author_sort	Ahmad, Norul Janah
title	Voltage stability analysis using artificial neural network / Norul Janah Ahmad
title_short	Voltage stability analysis using artificial neural network / Norul Janah Ahmad
title_full	Voltage stability analysis using artificial neural network / Norul Janah Ahmad
title_fullStr	Voltage stability analysis using artificial neural network / Norul Janah Ahmad
title_full_unstemmed	Voltage stability analysis using artificial neural network / Norul Janah Ahmad
title_sort	voltage stability analysis using artificial neural network / norul janah ahmad
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Electrical Engineering
publishDate	1999
url	https://ir.uitm.edu.my/id/eprint/78082/1/78082.pdf
_version_	1783736207921905664

Voltage stability analysis using artificial neural network / Norul Janah Ahmad

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