<?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>0122-3461</journal-id>
<journal-title><![CDATA[Ingeniería y Desarrollo]]></journal-title>
<abbrev-journal-title><![CDATA[Ing. Desarro.]]></abbrev-journal-title>
<issn>0122-3461</issn>
<publisher>
<publisher-name><![CDATA[Fundación Universidad del Norte]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0122-34612020000100032</article-id>
<article-id pub-id-type="doi">10.14482/inde.38.1.519.5</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[A new statistical approach to customer classification and load profiling]]></article-title>
<article-title xml:lang="es"><![CDATA[Nueva aproximación estadística a la clasificación de consumidores y la construcción de curvas de carga]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[SIERRA GIL]]></surname>
<given-names><![CDATA[EDUARDO]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[BASULTO ESPINOSA]]></surname>
<given-names><![CDATA[ALFREDO]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[ESCALONA AGUILAR]]></surname>
<given-names><![CDATA[ARGELIS]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Camagüey  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Camagüey  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Cuba</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Empresa Inmobiliaria ALMEST  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Cuba</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2020</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2020</year>
</pub-date>
<volume>38</volume>
<numero>1</numero>
<fpage>32</fpage>
<lpage>43</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0122-34612020000100032&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0122-34612020000100032&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0122-34612020000100032&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract It is of utmost importance in an electrical distribution system to have a detailed knowledge of the characteristics of the loads it feeds and that they determine, in a final extent, the behavior of parameters in the different regimes of operation, there are various methods for the classification of consumers and the construction of the typical daily load curves, however these methods do not mainly consider that these curves are subjected to the behavior of each kind of consumers. This work proposes a new approximation to this problem based on a method sustained by two statistical tools, Kendall matching coefficient and the correlation coefficient for ranges stated by Spearman and its effectiveness is checked by means of its application in two distribution circuits, demonstrating that there is a coincidence between the load profiles obtained through the method proposed and the load profiles obtained through measurements accomplished at the substation.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen En un sistema eléctrico de distribución es de suma importancia tener un conocimiento detallado de las características de las cargas que este alimenta y que determinan en última instancia el comportamiento de los parámetros en los diferentes regímenes de operación. Existen métodos diversos para la clasificación de los consumidores y la construcción de las curvas de carga diaria típicas sin embargo, estos métodos en su mayoría no consideran que estas curvas están sujetas a la conducta de cada tipo de consumidor. Este trabajo propone una nueva aproximación al problema a partir de un método basado en dos herramientas estadísticas, el coeficiente de concordancia de Kendall y el coeficiente de correlación por rangos de Spearman, y se comprueba la efectividad del mismo mediante su aplicación en dos circuitos de distribución, demostrándose que existe coincidencia entre los perfiles de carga obtenidos mediante el método propuesto, y los que se obtuvieron mediante mediciones realizadas en la subestación.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Curvas de carga]]></kwd>
<kwd lng="es"><![CDATA[demanda eléctrica]]></kwd>
<kwd lng="es"><![CDATA[redes de distribución]]></kwd>
<kwd lng="es"><![CDATA[transformadores de distribución]]></kwd>
<kwd lng="en"><![CDATA[distribution network]]></kwd>
<kwd lng="en"><![CDATA[distribution transformers]]></kwd>
<kwd lng="en"><![CDATA[electrical demand]]></kwd>
<kwd lng="en"><![CDATA[Load profiles]]></kwd>
</kwd-group>
</article-meta>
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