Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/10474
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dc.contributor.authorSadiq, A. A.-
dc.contributor.authorNwohu, M. N.-
dc.contributor.authorAmbafi, J. G.-
dc.date.accessioned2021-07-18T18:12:23Z-
dc.date.available2021-07-18T18:12:23Z-
dc.date.issued2013-08-
dc.identifier.issn2306-6474-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/10474-
dc.descriptionA & TCen_US
dc.description.abstractAs the Nigerian electricity market tends towards deregulation thereby encouraging Independent Power Producers (IPP), one key issue is the optimal location of their generating units for a given network. In this paper, the application of Available Transfer Capability (ATC) expected values among selected candidate buses is used as criterion to siting of new generator. However, Genetic algorithm (GA) approach is employed to locate the optimal bus for siting a new generation resource and a comparison between the use of ATC level index and GA is made. The results shows that the use of genetic algorithm for real power loss minimization is a better technique for optimal generator siting when compared with ATC level index.en_US
dc.description.sponsorshipPrivateen_US
dc.language.isoenen_US
dc.publisherInternational Journal of Engineering Sciences (TI Journals)en_US
dc.relation.ispartofseries2;8-
dc.subjectGenerator Siting Genetic Algorithm (GA) Available Transfer Capability (ATC) Power Network Power lossen_US
dc.titleA Comparative Study on Implementation of Genetic Algorithm (GA) and ATC to Generator Siting in Nigerian 330KV Power Networken_US
dc.typeArticleen_US
Appears in Collections:Electrical/Electronic Engineering

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