<?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>2602-8492</journal-id>
<journal-title><![CDATA[Revista Técnica energía]]></journal-title>
<abbrev-journal-title><![CDATA[Revista Técnica energía]]></abbrev-journal-title>
<issn>2602-8492</issn>
<publisher>
<publisher-name><![CDATA[Operador Nacional de Electricidad CENACE]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2602-84922019000200041</article-id>
<article-id pub-id-type="doi">10.37116/revistaenergia.v16.n1.2019.334</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Determinación del Modelo Estocástico del Estado de Carga de Baterías para el cómputo de Flujo de Potencia Probabilístico de Microrredes]]></article-title>
<article-title xml:lang="en"><![CDATA[Battery State of Charge Stochastic Model determination for Microgrids Probabilistic Power Flow computation]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cepeda]]></surname>
<given-names><![CDATA[Jaime]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Chamba]]></surname>
<given-names><![CDATA[Santiago]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Operador Nacional de Electricidad CENACE  ]]></institution>
<addr-line><![CDATA[Quito ]]></addr-line>
<country>Ecuador</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,CELEC EP Unidad de Negocio Coca Codo Sinclair  ]]></institution>
<addr-line><![CDATA[Quito ]]></addr-line>
<country>Ecuador</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>16</volume>
<numero>1</numero>
<fpage>41</fpage>
<lpage>50</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_arttext&amp;pid=S2602-84922019000200041&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_abstract&amp;pid=S2602-84922019000200041&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.senescyt.gob.ec/scielo.php?script=sci_pdf&amp;pid=S2602-84922019000200041&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: Este documento propone una novedosa metodología para la estimación probabilística del modelo estocástico del estado de carga (SOC por su nombre en inglés &#8220;State of Charge&#8221;) de los sistemas de almacenamiento de energía mediante baterías (BESS por su nombre en inglés &#8220;Battery Energy Storage Systems&#8221;). La estimación apropiada del SOC es uno de los parámetros más importantes en la planificación de la expansión y operación de las microrredes. Para ello, se estructura una herramienta computacional que enlaza los programas de DIgSILENT PowerFactory y Python. Este aplicativo permite, de forma probabilística, evaluar la operación de la microrred considerando la disponibilidad del recurso primario intermitente de las fuentes de energía renovables y la variabilidad de la demanda eléctrica. Como resultado se determinan los modelos estocásticos del SOC del BESS para cada período de tiempo. La metodología propuesta se aplica a una microrred de prueba que se conecta a la &#8220;Barra 6&#8221; del sistema de prueba WSCC de tres máquinas y nueve barras, obteniéndose resultados prometedores.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: This document proposes a novel methodology for probabilistic estimation of the State of Charge (SOC) stochastic model of Battery Energy Storage Systems (BESS). Proper estimation of SOC is one of the most important parameters for microgrids expansion planning and operation analysis. For this aim, a script that links DIgSILENT PowerFactory and Python is structured. This computational tool allows a probabilistic assessment of the microgrid operation, considering the intermittent availability of the renewable energy primary resource and the electric demand variability. As a result, the stochastic models of SOC of BESS are determined for each period of time. This methodological proposal is applied to a microgrid test system connected to the &#8220;Bus 6&#8221; of the three machine - nine bus WSCC test power system, obtaining promising results.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Flujos de Potencia Probabilísticos]]></kwd>
<kwd lng="es"><![CDATA[incertidumbre]]></kwd>
<kwd lng="es"><![CDATA[Montecarlo]]></kwd>
<kwd lng="es"><![CDATA[microrred]]></kwd>
<kwd lng="es"><![CDATA[BESS]]></kwd>
<kwd lng="es"><![CDATA[SOC]]></kwd>
<kwd lng="en"><![CDATA[Probabilistic Power Flow]]></kwd>
<kwd lng="en"><![CDATA[uncertainty]]></kwd>
<kwd lng="en"><![CDATA[Monte Carlo]]></kwd>
<kwd lng="en"><![CDATA[microgrid]]></kwd>
<kwd lng="en"><![CDATA[BESS]]></kwd>
<kwd lng="en"><![CDATA[SOC.]]></kwd>
</kwd-group>
</article-meta>
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