<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0121-1129</journal-id>
<journal-title><![CDATA[Revista Facultad de Ingeniería]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. Fac. ing.]]></abbrev-journal-title>
<issn>0121-1129</issn>
<publisher>
<publisher-name><![CDATA[Universidad Pedagógica y Tecnológica de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0121-11292019000100077</article-id>
<article-id pub-id-type="doi">10.19053/01211129.v28.n50.2019.8816</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Representation and estimation of the power coefficient in wind energy conversion systems]]></article-title>
<article-title xml:lang="es"><![CDATA[Representación y estimación del coeficiente de potencia en sistemas de conversión de energía eólica]]></article-title>
<article-title xml:lang="pt"><![CDATA[Representação e estimação do coeficiente de potência em sistemas de conversão de energia eólica]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[González-Hernández]]></surname>
<given-names><![CDATA[José Genaro]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Salas-Cabrera]]></surname>
<given-names><![CDATA[Rubén]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Instituto Tecnológico de Ciudad Madero  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Instituto Tecnológico de Ciudad Madero  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2019</year>
</pub-date>
<volume>28</volume>
<numero>50</numero>
<fpage>77</fpage>
<lpage>90</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0121-11292019000100077&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0121-11292019000100077&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0121-11292019000100077&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This paper aims at summarizing various methods used for representing and estimating the power coefficient in wind turbines, such as exponential, sinusoidal and polynomial models, as well as mathematical tools known as state observers. We present an exhaustive bibliographic review of the models used to calculate the power coefficient, given that this type of studies are scarce nowadays. In addition, we propose models that can be satisfactorily used for various analyzes of wind energy conversion systems, such as the representation by a polynomial function of fourth degree and the models based on the stochastic probability function. The relevance of this work is supported by the advantages and disadvantages of the various models and estimators of the power coefficient, which are presented at the end of the article in a comparative table with the purpose of offering to the reader a general summary. Ultimately, this review aims at helping researchers, students, university professors and those who wish to venture into this field, even though they do not have much experience, to establish a quick synthesized understanding of the different models and representations of the power coefficient.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen Este artículo presenta un resumen de diversos métodos utilizados para la representación y estimación del coeficiente de potencia en aerogeneradores, tales como modelos exponenciales, sinusoidales y polinomiales, así como también de herramientas matemáticas conocidas como observadores de estado. Dada la escasez de estudios que le presenten al lector un panorama general de los modelos utilizados para el cálculo del coeficiente de potencia, este resumen, producto de una revisión bibliográfica exhaustiva, constituye un aporte importante. Otra contribución que se logró fue presentar propuestas propias de modelos que pueden ser utilizados satisfactoriamente para diversos análisis de sistemas de conversión de energía eólica, tales como la representación por una función polinomial de cuarto grado y los modelos basados en la función de probabilidad estocástica. La relevancia de este trabajo se apoya en las ventajas y desventajas de los diversos modelos y estimadores del coeficiente de potencia, las cuales se presentan al final del artículo en una tabla comparativa, con el propósito de ofrecer al lector un resumen general que le permita una comprensión rápida y sintetizada de los diversos modelos y representaciones del coeficiente de potencia, lo que ayuda a investigadores, estudiantes, profesores universitarios y a quienes deseen incursionar en este campo, aunque no tengan mucha experiencia.]]></p></abstract>
<abstract abstract-type="short" xml:lang="pt"><p><![CDATA[Resumo Este artigo apresenta um resumo de diversos métodos utilizados para a representação e estimação do coeficiente de potência em aerogeradores, tais como modelos exponenciais, sinusoidais e polinomiais, assim como também de ferramentas matemáticas conhecidas como observadores de estado. Dada a escassez de estudos que apresentem ao leitor um panorama geral dos modelos utilizados para o cálculo do coeficiente de potência, este resumo, produto de uma revisão bibliográfica exaustiva, constitui um aporte importante. Outra contribuição que se logrou foi apresentar propostas próprias de modelos que possam ser utilizados satisfatoriamente para diversas análises de sistemas de conversão de energia eólica, tais como a representação por uma função polinomial de quarto grau e os modelos baseados na função de probabilidade estocástica. A relevância deste trabalho apoia-se nas vantagens e desvantagens dos diversos modelos e estimadores do coeficiente de potência, as quais se apresentam no final do artigo em uma tabela comparativa, com o propósito de oferecer ao leitor um resumo geral que lhe permita uma compreensão rápida e sintetizada dos diversos modelos e representações do coeficiente de potência, o que ajuda a pesquisadores, estudantes, professores universitários e aos que desejem incursionar neste campo, ainda que não tenham muita experiência.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[energy conversion]]></kwd>
<kwd lng="en"><![CDATA[energy efficiency]]></kwd>
<kwd lng="en"><![CDATA[power coefficient]]></kwd>
<kwd lng="en"><![CDATA[state estimation]]></kwd>
<kwd lng="en"><![CDATA[wind energy]]></kwd>
<kwd lng="es"><![CDATA[coeficiente de potencia]]></kwd>
<kwd lng="es"><![CDATA[conversión de energía]]></kwd>
<kwd lng="es"><![CDATA[eficiencia energética]]></kwd>
<kwd lng="es"><![CDATA[energía eólica]]></kwd>
<kwd lng="es"><![CDATA[estimación de estado]]></kwd>
<kwd lng="pt"><![CDATA[coeficiente de potência]]></kwd>
<kwd lng="pt"><![CDATA[conversão de energia]]></kwd>
<kwd lng="pt"><![CDATA[eficiência energética]]></kwd>
<kwd lng="pt"><![CDATA[energia eólica]]></kwd>
<kwd lng="pt"><![CDATA[estimação de estado]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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