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Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system

This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simula...

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Main Authors: Abas, N.A.S., Musirin, I., Jelani, S., Mansor, M.H., Honnoon, N.M.S., Othman, M.M.
Format: Article
Language:English
Published: 2020
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spelling my.uniten.dspace-128722020-07-07T06:18:30Z Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system Abas, N.A.S. Musirin, I. Jelani, S. Mansor, M.H. Honnoon, N.M.S. Othman, M.M. This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system. © 2019 Institute of Advanced Engineering and Science. All rights reserved. 2020-02-03T03:27:28Z 2020-02-03T03:27:28Z 2019 Article 10.11591/eei.v8i3.1631 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 optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system. © 2019 Institute of Advanced Engineering and Science. All rights reserved.
format Article
author Abas, N.A.S.
Musirin, I.
Jelani, S.
Mansor, M.H.
Honnoon, N.M.S.
Othman, M.M.
spellingShingle Abas, N.A.S.
Musirin, I.
Jelani, S.
Mansor, M.H.
Honnoon, N.M.S.
Othman, M.M.
Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system
author_facet Abas, N.A.S.
Musirin, I.
Jelani, S.
Mansor, M.H.
Honnoon, N.M.S.
Othman, M.M.
author_sort Abas, N.A.S.
title Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system
title_short Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system
title_full Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system
title_fullStr Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system
title_full_unstemmed Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system
title_sort integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system
publishDate 2020
_version_ 1672614185387687936
score 13.214268

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