Available transfer capability determination using artificial neural network

Open access to the transmission systems places a new emphasis on the more intensive shared use of the interconnected networks reliably by utilities and independent power producers. Therefore, as a measure of the network capability for further commercial activity over and above already committed uses...

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Main Author:	Habibuddin, Mohd. Hafiz
Format:	Thesis
Language:	English
Published:	2003
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/42613/1/MohdHafizHabibuddinFKE2003.pdf
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id	my-utm-ep.42613
record_format	uketd_dc
spelling	my-utm-ep.426132017-10-19T10:45:24Z Available transfer capability determination using artificial neural network 2003 Habibuddin, Mohd. Hafiz TK Electrical engineering. Electronics Nuclear engineering Open access to the transmission systems places a new emphasis on the more intensive shared use of the interconnected networks reliably by utilities and independent power producers. Therefore, as a measure of the network capability for further commercial activity over and above already committed uses, the concept of available transfer capability (ATC) was proposed and defined by the Federal Energy Regulatory Commission (FERC) in 1995. This study proposes the use of an Artificial Neural Networks (ANN) to determine ATC in an interconnected power system. The ANN is a multilayer feedforward network employing LevenbergMarquardt training algorithm. Newton-Raphson load flow solution incorporating Continuation Power Flow (CPF) method was used to gather the training and test data. The inputs to the ANN are the load level and line flow in the power system. Only thermal limits are taken into consideration. The method was tested with 4 buses system and TNB Southern Region 25 buses system. Comparison with CPF method shows that the ANN is a feasible alternative method to determine ATC. 2003 Thesis http://eprints.utm.my/id/eprint/42613/ http://eprints.utm.my/id/eprint/42613/1/MohdHafizHabibuddinFKE2003.pdf application/pdf en public http://libraryopac.utm.my/client/en_AU/main/search/detailnonmodal/ent:$002f$002fSD_ILS$002f0$002fSD_ILS:334298/one?qu=Available+transfer+capability+determination+using+artificial+neural+network masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Habibuddin, Mohd. Hafiz Available transfer capability determination using artificial neural network
description	Open access to the transmission systems places a new emphasis on the more intensive shared use of the interconnected networks reliably by utilities and independent power producers. Therefore, as a measure of the network capability for further commercial activity over and above already committed uses, the concept of available transfer capability (ATC) was proposed and defined by the Federal Energy Regulatory Commission (FERC) in 1995. This study proposes the use of an Artificial Neural Networks (ANN) to determine ATC in an interconnected power system. The ANN is a multilayer feedforward network employing LevenbergMarquardt training algorithm. Newton-Raphson load flow solution incorporating Continuation Power Flow (CPF) method was used to gather the training and test data. The inputs to the ANN are the load level and line flow in the power system. Only thermal limits are taken into consideration. The method was tested with 4 buses system and TNB Southern Region 25 buses system. Comparison with CPF method shows that the ANN is a feasible alternative method to determine ATC.
format	Thesis
qualification_level	Master's degree
author	Habibuddin, Mohd. Hafiz
author_facet	Habibuddin, Mohd. Hafiz
author_sort	Habibuddin, Mohd. Hafiz
title	Available transfer capability determination using artificial neural network
title_short	Available transfer capability determination using artificial neural network
title_full	Available transfer capability determination using artificial neural network
title_fullStr	Available transfer capability determination using artificial neural network
title_full_unstemmed	Available transfer capability determination using artificial neural network
title_sort	available transfer capability determination using artificial neural network
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2003
url	http://eprints.utm.my/id/eprint/42613/1/MohdHafizHabibuddinFKE2003.pdf
_version_	1747816812233359360

Available transfer capability determination using artificial neural network

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