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Application of artificial neural network (ANN) for reactive power dispatch / Siti Rokiah Ramli

Recently research has shown that ANN is promising solution to many applications especially for non-linear problem in power system, which is difficult for conventional technique. The potential of application of ANN as an alternative approach for solving certain difficult power system problem where co...

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Main Author: Ramli, Siti Rokiah
Format: Thesis
Language:English
Published: 2003
Subjects:
Nonlinear theories
Online Access:https://ir.uitm.edu.my/id/eprint/77989/1/77989.pdf
https://ir.uitm.edu.my/id/eprint/77989/
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spelling my.uitm.ir.779892023-07-26T00:33:37Z https://ir.uitm.edu.my/id/eprint/77989/ Application of artificial neural network (ANN) for reactive power dispatch / Siti Rokiah Ramli Ramli, Siti Rokiah Nonlinear theories Recently research has shown that ANN is promising solution to many applications especially for non-linear problem in power system, which is difficult for conventional technique. The potential of application of ANN as an alternative approach for solving certain difficult power system problem where conventional methods have not achieved desired speed couldn't be understated. This report presents the study of reactive power dispatch problem, for the power system to operate in a reliable and economic way. In this study, artificial neural network (ANN) with multilayer feed forward and error back propagation is used. The feed forward network programmed was developed using the MATLAB version 6.1. The proposed technique is tested on IEEE 14 bus system. The result shows that the proposed ANN technique is highly accurate and capable to predict at faster rate. 2003 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/77989/1/77989.pdf Application of artificial neural network (ANN) for reactive power dispatch / Siti Rokiah Ramli. (2003) Degree thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Nonlinear theories
spellingShingle Nonlinear theories
Ramli, Siti Rokiah
Application of artificial neural network (ANN) for reactive power dispatch / Siti Rokiah Ramli
description Recently research has shown that ANN is promising solution to many applications especially for non-linear problem in power system, which is difficult for conventional technique. The potential of application of ANN as an alternative approach for solving certain difficult power system problem where conventional methods have not achieved desired speed couldn't be understated. This report presents the study of reactive power dispatch problem, for the power system to operate in a reliable and economic way. In this study, artificial neural network (ANN) with multilayer feed forward and error back propagation is used. The feed forward network programmed was developed using the MATLAB version 6.1. The proposed technique is tested on IEEE 14 bus system. The result shows that the proposed ANN technique is highly accurate and capable to predict at faster rate.
format Thesis
author Ramli, Siti Rokiah
author_facet Ramli, Siti Rokiah
author_sort Ramli, Siti Rokiah
title Application of artificial neural network (ANN) for reactive power dispatch / Siti Rokiah Ramli
title_short Application of artificial neural network (ANN) for reactive power dispatch / Siti Rokiah Ramli
title_full Application of artificial neural network (ANN) for reactive power dispatch / Siti Rokiah Ramli
title_fullStr Application of artificial neural network (ANN) for reactive power dispatch / Siti Rokiah Ramli
title_full_unstemmed Application of artificial neural network (ANN) for reactive power dispatch / Siti Rokiah Ramli
title_sort application of artificial neural network (ann) for reactive power dispatch / siti rokiah ramli
publishDate 2003
url https://ir.uitm.edu.my/id/eprint/77989/1/77989.pdf
https://ir.uitm.edu.my/id/eprint/77989/
_version_ 1772815546483474432
score 13.211869

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