Power system security assessment using artificial neural network / Mohd Fathi Zakaria

The management of power system has become more difficult than earlier because power system are closer to security limits, fewer operators are engaged in the supervision and operation of power system. Power system security assessment has become a major concern today to avoid the instability in power...

Full description

Saved in:

Bibliographic Details
Main Author:	Zakaria, Mohd Fathi
Format:	Thesis
Language:	English
Published:	2010
Subjects:	Power resources
Online Access:	https://ir.uitm.edu.my/id/eprint/85370/1/85370.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uitm-ir.85370
record_format	uketd_dc
spelling	my-uitm-ir.853702024-01-31T03:47:02Z Power system security assessment using artificial neural network / Mohd Fathi Zakaria 2010 Zakaria, Mohd Fathi Power resources Electric apparatus and materials. Electric circuits. Electric networks The management of power system has become more difficult than earlier because power system are closer to security limits, fewer operators are engaged in the supervision and operation of power system. Power system security assessment has become a major concern today to avoid the instability in power system occur. One of the most significant considerations in applying neural networks to power system security assessment is the proper selection of training features. Modern inter connected power systems often consist of thousands of pieces of equipment each of which may have an effect on the security of the system. Neural networks have shown great promise for their ability to quickly and accurately predict the system security when trained with data collected from a load flow using Newton Raphson technique. A case study is performed on the IEEE 6-bus system to illustrate the effectiveness of the proposed techniques. 2010 Thesis https://ir.uitm.edu.my/id/eprint/85370/ https://ir.uitm.edu.my/id/eprint/85370/1/85370.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Power resources Power resources
spellingShingle	Power resources Power resources Zakaria, Mohd Fathi Power system security assessment using artificial neural network / Mohd Fathi Zakaria
description	The management of power system has become more difficult than earlier because power system are closer to security limits, fewer operators are engaged in the supervision and operation of power system. Power system security assessment has become a major concern today to avoid the instability in power system occur. One of the most significant considerations in applying neural networks to power system security assessment is the proper selection of training features. Modern inter connected power systems often consist of thousands of pieces of equipment each of which may have an effect on the security of the system. Neural networks have shown great promise for their ability to quickly and accurately predict the system security when trained with data collected from a load flow using Newton Raphson technique. A case study is performed on the IEEE 6-bus system to illustrate the effectiveness of the proposed techniques.
format	Thesis
qualification_level	Bachelor degree
author	Zakaria, Mohd Fathi
author_facet	Zakaria, Mohd Fathi
author_sort	Zakaria, Mohd Fathi
title	Power system security assessment using artificial neural network / Mohd Fathi Zakaria
title_short	Power system security assessment using artificial neural network / Mohd Fathi Zakaria
title_full	Power system security assessment using artificial neural network / Mohd Fathi Zakaria
title_fullStr	Power system security assessment using artificial neural network / Mohd Fathi Zakaria
title_full_unstemmed	Power system security assessment using artificial neural network / Mohd Fathi Zakaria
title_sort	power system security assessment using artificial neural network / mohd fathi zakaria
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Electrical Engineering
publishDate	2010
url	https://ir.uitm.edu.my/id/eprint/85370/1/85370.pdf
_version_	1794192087531388928

Power system security assessment using artificial neural network / Mohd Fathi Zakaria

Similar Items