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A Data-mining-based Methodology to support MV Electricity Customers' Characterization

dc.contributor.authorRamos, Sérgio
dc.contributor.authorDuarte, João
dc.contributor.authorDuarte, F. Jorge
dc.contributor.authorVale, Zita
dc.date.accessioned2015-05-06T08:45:51Z
dc.date.available2015-05-06T08:45:51Z
dc.date.issued2015-03
dc.description.abstractThis paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.por
dc.identifier.doi10.1016/j.enbuild.2015.01.035
dc.identifier.urihttp://hdl.handle.net/10400.22/5936
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherElsevierpor
dc.relation.ispartofseriesEnergy and Buildings;Vol. 91
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S0378778815000420por
dc.subjectLoad profilingpor
dc.subjectData Miningpor
dc.subjectClusteringpor
dc.subjectClassificationpor
dc.subjectClustering Validitypor
dc.titleA Data-mining-based Methodology to support MV Electricity Customers' Characterizationpor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage25por
oaire.citation.startPage16por
oaire.citation.titleEnergy and Buildingspor
oaire.citation.volume91por
person.familyNameCarvalho Ramos
person.familyNameVale
person.givenNameSérgio Filipe
person.givenNameZita
person.identifier632184
person.identifier.ciencia-id6D1F-C495-6660
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-1120-5656
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id7004115775
rcaap.rightsopenAccesspor
rcaap.typearticlepor
relation.isAuthorOfPublicationf01a54a0-e6c0-4cf3-afd8-5a664bbac7b4
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication.latestForDiscoveryf01a54a0-e6c0-4cf3-afd8-5a664bbac7b4

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