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A Short Review on Data Mining Techniques for Electricity Customers Characterization

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dc.contributor.authorCembranel, Samuel S.
dc.contributor.authorLezama, Fernando
dc.contributor.authorSoares, João
dc.contributor.authorFilipe Ramos, Sérgio
dc.contributor.authorGomes, Antonio
dc.contributor.authorVale, Zita
dc.date.accessioned2019-11-22T15:10:43Z
dc.date.embargo2119
dc.date.issued2019
dc.description.abstractAn important tool to manage electrical systems is the knowledge of customers' consumption patterns. Data Mining (DM) emerges as an important tool for extracting information about energy consumption in databases and identifying consumption patterns. This paper presents a short review on DM, with a focus on the characterization of electricity customers supported on knowledge discovery in database (KDD) process. The study includes several steps: first, few concepts of the KDD process are presented; following, a short review of clustering algorithms is presented including partitional, hierarchical, fuzzy, evolutionary methods, and Self-Organizing Maps; finally, the main concepts and methods for load classification, based on load shape indices are presented. The main objective of this work is to present a short review of DM techniques applied to identify typical load profiles in electrical systems and new customers' classification.pt_PT
dc.description.sponsorshipThis work has received funding from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2019 and BENEFICE – PTDC/EEI-EEE/29070/2017pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/GTDAsia.2019.8715891pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/14935
dc.language.isoengpt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relationBENEFICE – PTDC/EEI-EEE/29070/2017pt_PT
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8715891pt_PT
dc.subjectClassificationpt_PT
dc.subjectClusteringpt_PT
dc.subjectData Miningpt_PT
dc.subjectKnowledge Discovery in Databasespt_PT
dc.subjectLoad Profilingpt_PT
dc.titleA Short Review on Data Mining Techniques for Electricity Customers Characterizationpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F00760%2F2019/PT
oaire.citation.conferencePlaceBangkok, Thailand,19-23 March 2019pt_PT
oaire.citation.endPage199pt_PT
oaire.citation.startPage194pt_PT
oaire.citation.title2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD Asia)pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameLezama
person.familyNameSoares
person.familyNameCarvalho Ramos
person.familyNameVale
person.givenNameFernando
person.givenNameJoão
person.givenNameSérgio Filipe
person.givenNameZita
person.identifier1043580
person.identifier632184
person.identifier.ciencia-idE31F-56D6-1E0F
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-id6D1F-C495-6660
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8638-8373
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-1120-5656
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-6945-2017
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id36810077500
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsembargoedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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