Please use this identifier to cite or link to this item: http://dspace2020.uniten.edu.my:8080/handle/123456789/20763
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dc.contributor.authorSahilahudin M.F.F.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorJelani S.en_US
dc.contributor.authorMansor M.H.en_US
dc.date.accessioned2021-08-01T13:28:02Z-
dc.date.available2021-08-01T13:28:02Z-
dc.date.issued2020-
dc.identifier.urihttp://dspace2020.uniten.edu.my:8080/handle/123456789/20763-
dc.description.abstractThe increasing electricity demand in transmission system has caused the power transmission system experiencing stress condition. This phenomenon has forced the system to need urgent additional supply to maintain system adequacy, in particular the de-regulated power system environment. Distributed generation (DG) has been identified as one of the possible solutions to address this issue. DG installation has the capability to reduce transmission loss and improve the voltage profile. This paper presents evolutionary programming (EP) technique for optimizing the sizing and locations in DG installation. In this study, several DGs have been installed to address the voltage profile improvement and loss minimization; implemented on the IEEE 30-Bus Reliability Test System (RTS). Results obtained from the study revealed that, installation of multi-DGs in a transmission system has significantly minimized the transmission loss along with voltage profile improvement. © 2020 The Authors, published by EDP Sciences.en_US
dc.language.isoenen_US
dc.titleComputational Intelligence Based Technique for Multi-DG Installation in Transmission Systemen_US
dc.typeconference paperen_US
item.cerifentitytypePublications-
item.languageiso639-1en-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.grantfulltextopen-
item.openairetypeconference paper-
Appears in Collections:UNITEN Ebook and Article
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