Application of the Least Squares Method to the adjusting the power curve of a small wind generator
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
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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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 |
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1798329705621880832 |