Overview of Big Data Analytics in Power Quality Analysis and Assessment

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorHub Tecnologia e Inovação-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorNEI Electric Power Engineering-
Autor(es): dc.contributorColorado School of Mines-
Autor(es): dc.creatorSiqueira-de-Carvalho, Ricardo-
Autor(es): dc.creatorMorales-Paredes, Helmo K.-
Autor(es): dc.creatorBates, Carson-
Autor(es): dc.creatorAusmus, Jason-
Autor(es): dc.creatorSimões, Marcelo G.-
Autor(es): dc.creatorSen, Pankaj K.-
Data de aceite: dc.date.accessioned2025-08-21T16:00:05Z-
Data de disponibilização: dc.date.available2025-08-21T16:00:05Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2023-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/978-3-031-66961-3_1-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/305922-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/305922-
Descrição: dc.descriptionThe legacy electric grid is changing at a fast pace and is expected to have high penetration levels of distributed energy resources (DER) and non-linear loads at the distribution level. This introduces several challenges to the monitoring and control of the distribution network. One challenge is to address the significant increase of higher-order harmonics (h) in voltage and current waveforms. At present, power quality (PQ) meters have sampling rate limitations and cannot detect higher-order harmonics. The amount of available data in the electric grid is also increasing at an exponential rate and has grown to big data size. Big Data Analytics (BDA) may provide several opportunities for the monitoring and control of voltage and current harmonics. The effects of increasing the sampling rate for monitoring higher-order harmonics are discussed, and this paper explores new ideas on BDA for modern distribution systems operation, specifically, for Power Quality (PQ) analysis and assessment.-
Descrição: dc.descriptionHub Tecnologia e Inovação, AM-
Descrição: dc.descriptionSão Paulo State University-UNESP, SP-
Descrição: dc.descriptionNEI Electric Power Engineering-
Descrição: dc.descriptionColorado School of Mines-
Descrição: dc.descriptionSão Paulo State University-UNESP, SP-
Formato: dc.format3-16-
Idioma: dc.languageen-
Relação: dc.relationSmart Innovation, Systems and Technologies-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectBig Data Analytics-
Palavras-chave: dc.subjectDistributed Energy Resources-
Palavras-chave: dc.subjectPower Distribution-
Palavras-chave: dc.subjectPower Quality-
Palavras-chave: dc.subjectRenewable Energy-
Palavras-chave: dc.subjectBig data analytic-
Palavras-chave: dc.subjectData analytics-
Palavras-chave: dc.subjectHigh order harmonics-
Palavras-chave: dc.subjectHigher order harmonics-
Palavras-chave: dc.subjectPower-
Palavras-chave: dc.subjectPower distributions-
Palavras-chave: dc.subjectPower quality assessment-
Palavras-chave: dc.subjectPower-quality analysis-
Palavras-chave: dc.subjectRenewable energies-
Título: dc.titleOverview of Big Data Analytics in Power Quality Analysis and Assessment-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.