<?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>1815-5901</journal-id>
<journal-title><![CDATA[Ingeniería Energética]]></journal-title>
<abbrev-journal-title><![CDATA[Energética]]></abbrev-journal-title>
<issn>1815-5901</issn>
<publisher>
<publisher-name><![CDATA[Universidad Tecnológica de La Habana José Antonio Echeverría, Cujae]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1815-59012019000300181</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Predicción del consumo de energía eléctrica residencial de la Región Cajamarca mediante modelos Holt -Winters]]></article-title>
<article-title xml:lang="en"><![CDATA[Prediction of residential electric power consumption in the Cajamarca Region through Holt -Winters models]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mejía Vásquez]]></surname>
<given-names><![CDATA[Eduar Jamis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Gonzales Chávez]]></surname>
<given-names><![CDATA[Salome]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional de Jaén Escuela Profesional de Ingeniería Mecánica y Eléctrica ]]></institution>
<addr-line><![CDATA[Jaén Cajamarca]]></addr-line>
<country>Peru</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional de Ingeniería Facultad de Ingeniería Mecánica ]]></institution>
<addr-line><![CDATA[ Lima]]></addr-line>
<country>Peru</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2019</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2019</year>
</pub-date>
<volume>40</volume>
<numero>3</numero>
<fpage>181</fpage>
<lpage>191</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S1815-59012019000300181&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S1815-59012019000300181&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S1815-59012019000300181&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN El objetivo de este trabajo es predecir el consumo de energía eléctrica residencial de la Región Cajamarca mediante modelos Holt-Winters. Este procedimiento de modelización predictiva es útil para la predicción a corto y mediano plazo de ventas de energía eléctrica. La previsión del consumo de energía eléctrica tiene importancia en la planificación energética regional y nacional; a partir de sus resultados los agentes del mercado de energía eléctrica toman decisiones más adecuadas para su labor. El método Holt-Winters se estimó para diferentes constantes de suavización, que incluye métodos para patrones estacionales aditivos y multiplicativos. El valor de las pruebas estadísticas del error porcentual absoluto medio (MAPE) fue considerado como el principal estimador de la capacidad del modelo. El modelo Holt-Winters aditivo fue seleccionado como el mejor modelo de predicción, con un error porcentual absoluto medio de 1,70 y con constantes de suavización estimadas de 0,4.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT The objective of this work is to predict the consumption of residential electrical energy in the Cajamarca Region through Holt-Winters models. This predictive modeling procedure is useful for the short and medium term prediction of electricity sales. The forecast of electricity consumption is important in regional and national energy planning; from their results, the agents of the electric power market make more adequate decisions for their work. The Holt-Winters method was estimated for different smoothing constants, which includes methods for seasonal additive and multiplicative patterns. The value of the statistical tests of the mean absolute percentage error (MAPE) was considered as the main estimator of the capacity of the model. The additive Holt-Winters model was selected as the best prediction model, with an average absolute percentage error of 1,70 and with estimated smoothing constants of 0,4.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Consumo de energía electrica]]></kwd>
<kwd lng="es"><![CDATA[modelo Holt-Winters]]></kwd>
<kwd lng="es"><![CDATA[predicción]]></kwd>
<kwd lng="es"><![CDATA[residencial]]></kwd>
<kwd lng="es"><![CDATA[suavización exponencial]]></kwd>
<kwd lng="en"><![CDATA[Electric power consumption]]></kwd>
<kwd lng="en"><![CDATA[Holt-Winters model]]></kwd>
<kwd lng="en"><![CDATA[prediction]]></kwd>
<kwd lng="en"><![CDATA[residential]]></kwd>
<kwd lng="en"><![CDATA[exponential smoothing]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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