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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.
Other Authors: 57210749079
Format: Article
Published: Institute of Advanced Engineering and Science 2023
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spelling my.uniten.dspace-244842023-05-29T15:23:55Z 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. 57210749079 8620004100 57193388570 56372667100 57210749614 35944613200 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. Final 2023-05-29T07:23:55Z 2023-05-29T07:23:55Z 2019 Article 10.11591/eei.v8i3.1631 2-s2.0-85071394911 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071394911&doi=10.11591%2feei.v8i3.1631&partnerID=40&md5=a6376ad443583b89c0189ba58ce183d7 https://irepository.uniten.edu.my/handle/123456789/24484 8 3 978 984 All Open Access, Bronze, Green Institute of Advanced Engineering and Science Scopus
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/
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.
author2 57210749079
author_facet 57210749079
Abas N.A.S.
Musirin I.
Jelani S.
Mansor M.H.
Honnoon N.M.S.
Othman M.M.
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_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
publisher Institute of Advanced Engineering and Science
publishDate 2023
_version_ 1806424522942840832
score 13.214268

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