Application of the Least Squares Method to the adjusting the power curve of a small wind generator

Detalhes bibliográficos
Autor(a) principal: Gomes, Camila e Silva
Data de Publicação: 2020
Outros Autores: Krusche, Nisia, López, Javier Garcia
Tipo de documento: Artigo
Idioma: por
Título da fonte: Remat (Bento Gonçalves)
Texto Completo: https://periodicos.ifrs.edu.br/index.php/REMAT/article/view/3492
Resumo: With the development of the wind industry and the need of generating electricity, wind turbines are being installed in several locations. In each installation environment certain peculiarities are observed, which do necessary to model the relationship between the wind speed and the power generated by the wind turbine, in order to predict correctly the energy production in any environment. In this paper, a proposal was made, based on data collected by a wind generator in June 2017, to find a polynomial representation for the power curve of a specific wind turbine model, using a curve fitting method. The representation obtained was validated with the daily results collected and with the wind turbine power curve obtained which presented satisfactory results. In The 14929 data recorded per minute by the wind turbine during a month, the Least Squares Method was applied, using a grade 3 in these polynomial as base. The objective of this paper is to find a polynomial that adequately represents the power curve of a small wind turbine. Once this polynomial was found, the level of correlation and significance was evaluated to compare the polynomial found with experimental data collected over 30 days and the power curve of the polynomial. The results obtained are satisfactory for the cases in which the experiments allowed us to collect useful data for more than 2 consecutive hours.
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spelling Application of the Least Squares Method to the adjusting the power curve of a small wind generatorAplicação do Método dos Mínimos Quadrados para o ajuste da curva de potência de um aerogerador de pequeno porteMathematical ModelingWind EnergyCurve AdjustmentLeast Squares MethodsPower CurveModelagem MatemáticaEnergia EólicaAjuste de CurvasMétodo dos Mínimos QuadradosCurva de PotênciaWith the development of the wind industry and the need of generating electricity, wind turbines are being installed in several locations. In each installation environment certain peculiarities are observed, which do necessary to model the relationship between the wind speed and the power generated by the wind turbine, in order to predict correctly the energy production in any environment. In this paper, a proposal was made, based on data collected by a wind generator in June 2017, to find a polynomial representation for the power curve of a specific wind turbine model, using a curve fitting method. The representation obtained was validated with the daily results collected and with the wind turbine power curve obtained which presented satisfactory results. In The 14929 data recorded per minute by the wind turbine during a month, the Least Squares Method was applied, using a grade 3 in these polynomial as base. The objective of this paper is to find a polynomial that adequately represents the power curve of a small wind turbine. Once this polynomial was found, the level of correlation and significance was evaluated to compare the polynomial found with experimental data collected over 30 days and the power curve of the polynomial. The results obtained are satisfactory for the cases in which the experiments allowed us to collect useful data for more than 2 consecutive hours.Com o desenvolvimento da indústria eólica e a necessidade de gerar energia elétrica, os aerogeradores estão sendo instalados em diversas localidades. Em cada ambiente de instalação são observadas certas peculiaridades, o que torna necessária uma modelagem adequada da relação entre a velocidade do vento e a potência gerada pelo aerogerador, a fim de prever corretamente a produção de energia em qualquer ambiente. Neste trabalho, foi construída uma proposta, a partir dos dados coletados por um aerogerador em junho de 2017, para encontrar uma representação polinomial para a curva de potência de um modelo de aerogerador específico, usando um método de ajuste de curvas. A representação obtida foi validada com os resultados diários coletados e com obtenção da curva de potência do aerogerador. Nos 14.929 dados registrados por minuto pelo aerogerador no mês, foi aplicado o Método de Ajuste por Mínimos Quadrados, utilizando um polinômio de grau 3 como base. O objetivo deste trabalho é encontrar um polinômio que represente de modo adequado a curva de potência de um aerogerador de pequeno porte. Uma vez encontrado esse polinômio, para auferir a qualidade da representação, foi avaliado o nível de correlação e significância, comparando-se o polinômio encontrado com dados experimentais coletados ao longo de 30 dias e a sua curva de potência. Os resultados obtidos mostram-se satisfatórios para os casos nos quais os experimentos permitiram coletar dados úteis por mais de 2 horas consecutivas.Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul2020-01-19info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtigos; Avaliado pelos paresapplication/pdfhttps://periodicos.ifrs.edu.br/index.php/REMAT/article/view/349210.35819/remat2020v6i1id3492REMAT: Revista Eletrônica da Matemática; Vol. 6 No. 1 (2020); 1-16REMAT: Revista Eletrônica da Matemática; Vol. 6 Núm. 1 (2020); 1-16REMAT: Revista Eletrônica da Matemática; v. 6 n. 1 (2020); 1-162447-2689reponame:Remat (Bento Gonçalves)instname:Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS)instacron:IFRSporhttps://periodicos.ifrs.edu.br/index.php/REMAT/article/view/3492/2558Copyright (c) 2020 REMAT: Revista Eletrônica da Matemáticainfo:eu-repo/semantics/openAccessGomes, Camila e SilvaKrusche, NisiaLópez, Javier Garcia2022-12-28T16:04:13Zoai:ojs2.periodicos.ifrs.edu.br:article/3492Revistahttp://periodicos.ifrs.edu.br/index.php/REMATPUBhttps://periodicos.ifrs.edu.br/index.php/REMAT/oai||greice.andreis@caxias.ifrs.edu.br2447-26892447-2689opendoar:2022-12-28T16:04:13Remat (Bento Gonçalves) - Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS)false
dc.title.none.fl_str_mv Application of the Least Squares Method to the adjusting the power curve of a small wind generator
Aplicação do Método dos Mínimos Quadrados para o ajuste da curva de potência de um aerogerador de pequeno porte
title Application of the Least Squares Method to the adjusting the power curve of a small wind generator
spellingShingle Application of the Least Squares Method to the adjusting the power curve of a small wind generator
Gomes, Camila e Silva
Mathematical Modeling
Wind Energy
Curve Adjustment
Least Squares Methods
Power Curve
Modelagem Matemática
Energia Eólica
Ajuste de Curvas
Método dos Mínimos Quadrados
Curva de Potência
title_short Application of the Least Squares Method to the adjusting the power curve of a small wind generator
title_full Application of the Least Squares Method to the adjusting the power curve of a small wind generator
title_fullStr Application of the Least Squares Method to the adjusting the power curve of a small wind generator
title_full_unstemmed Application of the Least Squares Method to the adjusting the power curve of a small wind generator
title_sort Application of the Least Squares Method to the adjusting the power curve of a small wind generator
author Gomes, Camila e Silva
author_facet Gomes, Camila e Silva
Krusche, Nisia
López, Javier Garcia
author_role author
author2 Krusche, Nisia
López, Javier Garcia
author2_role author
author
dc.contributor.author.fl_str_mv Gomes, Camila e Silva
Krusche, Nisia
López, Javier Garcia
dc.subject.por.fl_str_mv Mathematical Modeling
Wind Energy
Curve Adjustment
Least Squares Methods
Power Curve
Modelagem Matemática
Energia Eólica
Ajuste de Curvas
Método dos Mínimos Quadrados
Curva de Potência
topic Mathematical Modeling
Wind Energy
Curve Adjustment
Least Squares Methods
Power Curve
Modelagem Matemática
Energia Eólica
Ajuste de Curvas
Método dos Mínimos Quadrados
Curva de Potência
description With the development of the wind industry and the need of generating electricity, wind turbines are being installed in several locations. In each installation environment certain peculiarities are observed, which do necessary to model the relationship between the wind speed and the power generated by the wind turbine, in order to predict correctly the energy production in any environment. In this paper, a proposal was made, based on data collected by a wind generator in June 2017, to find a polynomial representation for the power curve of a specific wind turbine model, using a curve fitting method. The representation obtained was validated with the daily results collected and with the wind turbine power curve obtained which presented satisfactory results. In The 14929 data recorded per minute by the wind turbine during a month, the Least Squares Method was applied, using a grade 3 in these polynomial as base. The objective of this paper is to find a polynomial that adequately represents the power curve of a small wind turbine. Once this polynomial was found, the level of correlation and significance was evaluated to compare the polynomial found with experimental data collected over 30 days and the power curve of the polynomial. The results obtained are satisfactory for the cases in which the experiments allowed us to collect useful data for more than 2 consecutive hours.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-19
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Artigos; Avaliado pelos pares
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ifrs.edu.br/index.php/REMAT/article/view/3492
10.35819/remat2020v6i1id3492
url https://periodicos.ifrs.edu.br/index.php/REMAT/article/view/3492
identifier_str_mv 10.35819/remat2020v6i1id3492
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://periodicos.ifrs.edu.br/index.php/REMAT/article/view/3492/2558
dc.rights.driver.fl_str_mv Copyright (c) 2020 REMAT: Revista Eletrônica da Matemática
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2020 REMAT: Revista Eletrônica da Matemática
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul
publisher.none.fl_str_mv Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul
dc.source.none.fl_str_mv REMAT: Revista Eletrônica da Matemática; Vol. 6 No. 1 (2020); 1-16
REMAT: Revista Eletrônica da Matemática; Vol. 6 Núm. 1 (2020); 1-16
REMAT: Revista Eletrônica da Matemática; v. 6 n. 1 (2020); 1-16
2447-2689
reponame:Remat (Bento Gonçalves)
instname:Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS)
instacron:IFRS
instname_str Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS)
instacron_str IFRS
institution IFRS
reponame_str Remat (Bento Gonçalves)
collection Remat (Bento Gonçalves)
repository.name.fl_str_mv Remat (Bento Gonçalves) - Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS)
repository.mail.fl_str_mv ||greice.andreis@caxias.ifrs.edu.br
_version_ 1798329705621880832

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