Optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / Mohd Helmi Mansor

This project presents a methodology for solving Optimal Power Flow (OPF) problem by using Evolutionary Programming (EP) Optimization technique in order to improve the voltage stability, minimize the cost of generation and minimize the losses in the power system. This study has developed the Evolutio...

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Main Author: Mansor, Mohd Helmi
Format: Thesis
Language:English
Published: 2007
Online Access:https://ir.uitm.edu.my/id/eprint/84576/1/84576.pdf
https://ir.uitm.edu.my/id/eprint/84576/
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spelling my.uitm.ir.845762024-01-30T09:06:01Z https://ir.uitm.edu.my/id/eprint/84576/ Optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / Mohd Helmi Mansor Mansor, Mohd Helmi This project presents a methodology for solving Optimal Power Flow (OPF) problem by using Evolutionary Programming (EP) Optimization technique in order to improve the voltage stability, minimize the cost of generation and minimize the losses in the power system. This study has developed the Evolutionary Programming (EP) optimization technique using MATLAB software. The study tested three fitness functions namely total cost minimization, total loss minimization and the voltage stability improvement in power system. Comparison in the results obtained was made in order to determine the best fitness function to be used for solving OPF and hence the voltage stability is improved. The proposed technique was tested on the IEEE 26- - v./ bus reliability test system. 2007 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/84576/1/84576.pdf Optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / Mohd Helmi Mansor. (2007) 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
description This project presents a methodology for solving Optimal Power Flow (OPF) problem by using Evolutionary Programming (EP) Optimization technique in order to improve the voltage stability, minimize the cost of generation and minimize the losses in the power system. This study has developed the Evolutionary Programming (EP) optimization technique using MATLAB software. The study tested three fitness functions namely total cost minimization, total loss minimization and the voltage stability improvement in power system. Comparison in the results obtained was made in order to determine the best fitness function to be used for solving OPF and hence the voltage stability is improved. The proposed technique was tested on the IEEE 26- - v./ bus reliability test system.
format Thesis
author Mansor, Mohd Helmi
spellingShingle Mansor, Mohd Helmi
Optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / Mohd Helmi Mansor
author_facet Mansor, Mohd Helmi
author_sort Mansor, Mohd Helmi
title Optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / Mohd Helmi Mansor
title_short Optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / Mohd Helmi Mansor
title_full Optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / Mohd Helmi Mansor
title_fullStr Optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / Mohd Helmi Mansor
title_full_unstemmed Optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / Mohd Helmi Mansor
title_sort optimal power flow for voltage stability improvement by using evolutionary programming optimization technique / mohd helmi mansor
publishDate 2007
url https://ir.uitm.edu.my/id/eprint/84576/1/84576.pdf
https://ir.uitm.edu.my/id/eprint/84576/
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score 13.214268