Cover Image

Voltage stability analysis using artificial neural network / Norol 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...

Full description

Saved in:
Bibliographic Details
Main Author: Ahmad, Norol Janah
Format: Thesis
Language:English
Published: 1999
Online Access:https://ir.uitm.edu.my/id/eprint/103545/1/103545.pdf
https://ir.uitm.edu.my/id/eprint/103545/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uitm.ir.103545
record_format eprints
spelling my.uitm.ir.1035452024-09-28T16:42:27Z https://ir.uitm.edu.my/id/eprint/103545/ Voltage stability analysis using artificial neural network / Norol Janah Ahmad Ahmad, Norol Janah 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 NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/103545/1/103545.pdf Voltage stability analysis using artificial neural network / Norol Janah Ahmad. (1999) Degree thesis, thesis, Universiti Teknologi MARA (UiTM). <http://terminalib.uitm.edu.my/103545.pdf>
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
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
author Ahmad, Norol Janah
spellingShingle Ahmad, Norol Janah
Voltage stability analysis using artificial neural network / Norol Janah Ahmad
author_facet Ahmad, Norol Janah
author_sort Ahmad, Norol Janah
title Voltage stability analysis using artificial neural network / Norol Janah Ahmad
title_short Voltage stability analysis using artificial neural network / Norol Janah Ahmad
title_full Voltage stability analysis using artificial neural network / Norol Janah Ahmad
title_fullStr Voltage stability analysis using artificial neural network / Norol Janah Ahmad
title_full_unstemmed Voltage stability analysis using artificial neural network / Norol Janah Ahmad
title_sort voltage stability analysis using artificial neural network / norol janah ahmad
publishDate 1999
url https://ir.uitm.edu.my/id/eprint/103545/1/103545.pdf
https://ir.uitm.edu.my/id/eprint/103545/
_version_ 1811598319154102272
score 13.211869

Similar Items