<?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>1390-6542</journal-id>
<journal-title><![CDATA[Enfoque UTE]]></journal-title>
<abbrev-journal-title><![CDATA[Enfoque UTE]]></abbrev-journal-title>
<issn>1390-6542</issn>
<publisher>
<publisher-name><![CDATA[Universidad UTE]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1390-65422018000400120</article-id>
<article-id pub-id-type="doi">10.29019/enfoqueute.v9n4.407</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[The extended Kalman filter in the dynamic state estimation of electrical power systems]]></article-title>
<article-title xml:lang="es"><![CDATA[El filtro extendido de Kalman en la estimación del estado dinámico de sistemas eléctricos de potencia]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cevallos]]></surname>
<given-names><![CDATA[Holger]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Intriago]]></surname>
<given-names><![CDATA[Gabriel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Plaza]]></surname>
<given-names><![CDATA[Douglas]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Idrovo]]></surname>
<given-names><![CDATA[Roger]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Escuela Superior Politécnica del Litoral  ]]></institution>
<addr-line><![CDATA[Guayaquil ]]></addr-line>
<country>Ecuador</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2018</year>
</pub-date>
<volume>9</volume>
<numero>4</numero>
<fpage>120</fpage>
<lpage>130</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_arttext&amp;pid=S1390-65422018000400120&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_abstract&amp;pid=S1390-65422018000400120&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_pdf&amp;pid=S1390-65422018000400120&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: The state estimation and the analysis of load flow are very important subjects in the analysis and management of Electrical Power Systems (EPS). This article describes the state estimation in EPS using the Extended Kalman Filter (EKF) and the method of Holt to linearize the process model and then calculates a performance error index as indicators of its accuracy. Besides, this error index can be used as a reference for further comparison between methodologies for state estimation in EPS such as the Unscented Kalman Filter, the Ensemble Kalman Filter, Monte Carlo methods, and others. Results of error indices obtained in the simulation process agree with the order of magnitude expected and the behavior of the filter is appropriate due to follows adequately the true value of the state variables. The simulation was done using Matlab and the electrical system used corresponds to the IEEE 14 and 30 bus test case systems. State Variables to consider in this study are the voltage and angle magnitudes.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: La estimación de estado y el análisis de flujo de carga son tópicos muy importantes en el análisis y control de un Sistema Eléctrico de Potencia (SEP). Este artículo describe la estimación de estados usando el Filtro Extendido de Kalman (EKF) y el método de Holt para linealizar el modelo del proceso y entonces calcular el índice de error del rendimiento del filtro como un indicador de su exactitud. Además, este índice de error calculado puede ser usado como una referencia en posteriores estudios de comparación entre diferentes metodologías usadas en la estimación de estados en SEP tales como el Unscented Filtro de Kalman, el Ensemble Filtro de Kalman, métodos de Montecarlo, y otros. Los resultados del índice de error obtenidos en el proceso de simulación están de acuerdo al orden de magnitud esperado y el comportamiento del filtro es adecuado ya que sigue adecuadamente al valor verdadero de las variables de estado. La simulación fue realizada usando Matlab y el sistema eléctrico usado corresponde a los sistemas de prueba IEEE de 14 y 30 barras. Las variables de estado a considerar en este estudio son la magnitud del voltaje.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[state estimation]]></kwd>
<kwd lng="en"><![CDATA[electric power systems]]></kwd>
<kwd lng="en"><![CDATA[extended Kalman filter]]></kwd>
<kwd lng="en"><![CDATA[linear exponential smoothing of Holt]]></kwd>
<kwd lng="en"><![CDATA[performance indices]]></kwd>
<kwd lng="en"><![CDATA[IEEE 14 bus test case]]></kwd>
<kwd lng="en"><![CDATA[IEEE 30 bus test case.]]></kwd>
<kwd lng="es"><![CDATA[estimación de estados]]></kwd>
<kwd lng="es"><![CDATA[sistemas eléctricos de potencia]]></kwd>
<kwd lng="es"><![CDATA[filtro extendido de Kalman]]></kwd>
<kwd lng="es"><![CDATA[alisado exponencial lineal de Holt]]></kwd>
<kwd lng="es"><![CDATA[índices de performance]]></kwd>
<kwd lng="es"><![CDATA[caso de prueba IEEE de 14 barras]]></kwd>
<kwd lng="es"><![CDATA[caso de prueba IEEE de 30 barras.]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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