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Embedded flower pollination evolutionary programming based technique for voltage stability enhancement with distributed generation installation

This paper presents the embedded flower pollination evolutionary programming-based technique for voltage stability enhancement with distributed generation installation. In this study, a new technique is developed which combines the element of flower pollination into the general evolutionary programm...

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Main Authors: Mansor, N.N., Shaaya, S.A., Musirin, I., Hannoon, N.S., Mohamed, Z., Zamani, M.K.M.
Format: Article
Language:English
Published: 2020
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spelling my.uniten.dspace-132822020-07-03T07:52:29Z Embedded flower pollination evolutionary programming based technique for voltage stability enhancement with distributed generation installation Mansor, N.N. Shaaya, S.A. Musirin, I. Hannoon, N.S. Mohamed, Z. Zamani, M.K.M. This paper presents the embedded flower pollination evolutionary programming-based technique for voltage stability enhancement with distributed generation installation. In this study, a new technique is developed which combines the element of flower pollination into the general evolutionary programming algorithm. The aim is to enhance the voltage stability in power system with the presence of distributed generation. The proposed technique was validated using the IEEE 33-Bus Distribution System. Results obtained from the study revealed that the proposed technique is better than EP in terms of optimizing the sizing of DG and location. © 2019, World Academy of Research in Science and Engineering. All rights reserved. 2020-02-03T03:31:32Z 2020-02-03T03:31:32Z 2019 Article 10.30534/ijatcse/2019/6881.32019 en
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description This paper presents the embedded flower pollination evolutionary programming-based technique for voltage stability enhancement with distributed generation installation. In this study, a new technique is developed which combines the element of flower pollination into the general evolutionary programming algorithm. The aim is to enhance the voltage stability in power system with the presence of distributed generation. The proposed technique was validated using the IEEE 33-Bus Distribution System. Results obtained from the study revealed that the proposed technique is better than EP in terms of optimizing the sizing of DG and location. © 2019, World Academy of Research in Science and Engineering. All rights reserved.
format Article
author Mansor, N.N.
Shaaya, S.A.
Musirin, I.
Hannoon, N.S.
Mohamed, Z.
Zamani, M.K.M.
spellingShingle Mansor, N.N.
Shaaya, S.A.
Musirin, I.
Hannoon, N.S.
Mohamed, Z.
Zamani, M.K.M.
Embedded flower pollination evolutionary programming based technique for voltage stability enhancement with distributed generation installation
author_facet Mansor, N.N.
Shaaya, S.A.
Musirin, I.
Hannoon, N.S.
Mohamed, Z.
Zamani, M.K.M.
author_sort Mansor, N.N.
title Embedded flower pollination evolutionary programming based technique for voltage stability enhancement with distributed generation installation
title_short Embedded flower pollination evolutionary programming based technique for voltage stability enhancement with distributed generation installation
title_full Embedded flower pollination evolutionary programming based technique for voltage stability enhancement with distributed generation installation
title_fullStr Embedded flower pollination evolutionary programming based technique for voltage stability enhancement with distributed generation installation
title_full_unstemmed Embedded flower pollination evolutionary programming based technique for voltage stability enhancement with distributed generation installation
title_sort embedded flower pollination evolutionary programming based technique for voltage stability enhancement with distributed generation installation
publishDate 2020
_version_ 1672614220352454656
score 13.222552

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