Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/57411
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dc.contributor.authorUžupytė, Rūta-
dc.contributor.authorKrilavičius, Tomas-
dc.contributor.authorBabarskis, Tomas-
dc.coverage.spatialTW-
dc.date.accessioned2018-10-07T01:21:15Z-
dc.date.available2018-10-07T01:21:15Z-
dc.date.issued2017-
dc.identifier.issn2223523X-
dc.identifier.otherVDU02-000022097-
dc.identifier.urihttp://ijdatics.datics.net/current_issues/IJDATICS_06_01/IJDATICS_06_01_11.pdf-
dc.descriptioneISSN 2071-2987-
dc.description.abstractThe changes and evolution of the electricity distribution has provided new possibilities to the electricity providers for developing a better marketing and trading strategies. A key aspect for designing specific tariff structures is the identification of customers groups exhibiting similar consumption patterns. This paper presents a new methodology for the classification of electricity customers on the basis of their electrical behaviour. Approach is based on the periodicity analysis and well known clustering technique – k–means. The paper presents the classification results obtained on a set of 3753 industrial users, whose consumption has been monitored for 3 yearsen
dc.description.sponsorshipBaltijos pažangių technologijų institutas, Vilnius-
dc.description.sponsorshipInformatikos fakultetas-
dc.description.sponsorshipTaikomosios informatikos katedra-
dc.description.sponsorshipVytauto Didžiojo universitetas-
dc.format.extentp. 44-47-
dc.language.isoen-
dc.relation.ispartofInternational journal of design, analysis and tools for integrated circuits and systems (IJDATICS). Hong Kong : Solari Co, 2017, vol. 6, no. 1-
dc.relation.isreferencedbyApplied Science & Technology Source (EBSCO)-
dc.relation.isreferencedbyAcademic Search R&D (EBSCO)-
dc.subjectElectricity patternsen
dc.subjectLoad profilingen
dc.subjectTime–series clusteringen
dc.subjectClustering techniqueen
dc.subject.classificationStraipsnis kitose duomenų bazėse / Article in other databases (S4)-
dc.subject.otherInformatika / Informatics (N009)-
dc.titleIdentification of electricity consumption profiles based on smart meters dataen
dc.typeresearch article-
dcterms.bibliographicCitation8-
dc.date.updated2018-01-15T13:03Z-
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local.typeS-
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptInformatikos fakultetas-
crisitem.author.deptTaikomosios informatikos katedra-
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications
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