<?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>S0122-34612025000100044</article-id>
<article-id pub-id-type="doi">10.14482/inde.43.01.489.326</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Evaluación de la calidad de la energía eléctrica suministrada por una planta solar fotovoltaica conectada a la red haciendo uso de algoritmos de aprendizaje automático y de minería de datos]]></article-title>
<article-title xml:lang="en"><![CDATA[Evaluation of the quality of the electrical energy supplied by a grid-connected solar photovoltaic plant using machine learning and data mining algorithms]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[YAJURE RAMÍREZ]]></surname>
<given-names><![CDATA[CÉSAR ARISTÓTELES]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Central de Venezuela Facultad de Ingeniería ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Venezuela</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2025</year>
</pub-date>
<volume>43</volume>
<numero>1</numero>
<fpage>44</fpage>
<lpage>63</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0122-34612025000100044&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0122-34612025000100044&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0122-34612025000100044&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La presencia de plantas solares fotovoltaicas para la producción de electricidad implica la disminución del uso de combustibles fósiles y la reducción de las emisiones contaminantes. La disponibilidad de la energía solar depende de las condiciones climáticas, por lo que los parámetros de la energía eléctrica a entregar podrían verse afectados. El objetivo de esta investigación es mostrar una metodología basada en la ciencia de datos para la evaluación de la calidad de la energía de plantas solares foto-voltaicas conectadas a la red, considerando los estándares vigentes. Se aplica a una planta de 260 kWp del Instituto Nacional de Estándares y Tecnología de los Estados Unidos. Los parámetros utilizados son la distorsión armónica total, fluctuaciones y desbalance de voltaje, frecuencia eléctrica, y factor de potencia. Casi el l00 % de los registros cumplen con los límites establecidos por los estándares para los parámetros, a excepción del factor de potencia, con un 63,56 %. Del modelo de clasificación del factor de potencia se obtuvo que las potencias aparente y activa y la frecuencia son las variables más importantes. Del algoritmo de descubrimiento de subgrupos se obtuvo que la irradiancia solar aparece en el 40 % de los subgrupos, y la frecuencia en el 50 %.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract The presence of photovoltaic solar plants to produce electricity implies the reduction of the use of fossil fuels, and of polluting emissions. The availability of solar energy depends on weather conditions, so the parameters of the electrical energy to be delivered could be affected. The objective of this research is to present a methodology based on data science for the evaluation of the energy quality of photovoltaic solar plants connected to the grid, considering current standards. It is applied to a 260 kWp plant of the National Institute of Standards and Technology of the United States. The parameters used are total harmonic distortion, voltage fluctuations and unbalance, electrical frequency, and power factor. Almost l00% of the records comply with the limits established by the standards for the parameters, except for power factor, with 63.56%. From the power factor classification model, the knowledge that apparent and active power, and frequency, are the most important variables was gathered. From the subgroup discovery algorithm, that solar irradiance appears in 40% of the subgroups, and frequency in 50%.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[distorsión armónica]]></kwd>
<kwd lng="es"><![CDATA[factor de potencia]]></kwd>
<kwd lng="es"><![CDATA[frecuencia eléctrica]]></kwd>
<kwd lng="es"><![CDATA[nivel de importancia]]></kwd>
<kwd lng="es"><![CDATA[subgrupos]]></kwd>
<kwd lng="en"><![CDATA[electrical frequency]]></kwd>
<kwd lng="en"><![CDATA[harmonic distortion]]></kwd>
<kwd lng="en"><![CDATA[importance level]]></kwd>
<kwd lng="en"><![CDATA[power factor]]></kwd>
<kwd lng="en"><![CDATA[subgrupos. subgroups]]></kwd>
</kwd-group>
</article-meta>
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<publisher-loc><![CDATA[Shelter Island, NY ]]></publisher-loc>
<publisher-name><![CDATA[Manning Publications Co.]]></publisher-name>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
