Generic dynamic load modelling using cluster analysis

dc.contributor.authorCeylan, Oğuzhan
dc.contributor.authorCeylan, Oğuzhan
dc.contributor.authorPapadopoulos, Theofilos A.
dc.contributor.authorYetkin, E. Fatih
dc.date.accessioned2019-06-27T08:00:52Z
dc.date.available2019-06-27T08:00:52Z
dc.date.issued2018
dc.departmentFakülteler, İşletme Fakültesi, Yönetim Bilişim Sistemleri Bölümüen_US
dc.description.abstractIn this paper a new generic load modelling procedure is proposed based on the application of cluster analysis on load model parameters identified from measured dynamic responses. The performance of the proposed approach is assessed using measurements obtained from a low-voltage laboratory scale test configuration. In order to develop robust generalized load models applicable to a wide range of operating conditions different load compositions operating conditions and voltage disturbances are considered in the analysis. The findings of this paper verify the validity of the proposed generic modelling procedure and indicate robust results using the proposed methodology.en_US]
dc.identifier.citation4
dc.identifier.doi10.1109/UPEC.2018.8541940en_US
dc.identifier.isbn978-1-5386-2910-9
dc.identifier.scopus2-s2.0-85059947821en_US
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.12469/133
dc.identifier.urihttps://doi.org/10.1109/UPEC.2018.8541940
dc.identifier.wosWOS:000468972100088en_US
dc.identifier.wosqualityN/A
dc.institutionauthorCeylan, Oğuzhanen_US
dc.institutionauthorYetkin, E. Fatihen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.journal53rd International Universities Power Engineering Conference (UPEC)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClusteringen_US
dc.subjectFuzzy C-meansen_US
dc.subjectGeneric load modellingen_US
dc.subjectk-means plusen_US
dc.subjectk-medoidsen_US
dc.subjectMeta-heuristic algorithmsen_US
dc.titleGeneric dynamic load modelling using cluster analysisen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
relation.isAuthorOfPublicationb80c3194-906c-4e78-a54c-e3cd1effc970
relation.isAuthorOfPublication.latestForDiscoveryb80c3194-906c-4e78-a54c-e3cd1effc970

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