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	<front>
		<journal-meta>
			<journal-id journal-id-type="publisher-id">rte</journal-id>
			<journal-title-group>
				<journal-title>Revista Técnica energía</journal-title>
				<abbrev-journal-title abbrev-type="publisher">Revista Técnica energía</abbrev-journal-title>
			</journal-title-group>
			<issn pub-type="ppub">1390-5074</issn>
			<issn pub-type="epub">2602-8492</issn>
			<publisher>
				<publisher-name>Operador Nacional de Electricidad CENACE</publisher-name>
			</publisher>
		</journal-meta>
		<article-meta>
			<article-id pub-id-type="doi">10.37116/revistaenergia.v22.n2.2025.730</article-id>
			<article-categories>
				<subj-group subj-group-type="heading">
					<subject>Aplicación Práctica</subject>
				</subj-group>
			</article-categories>
			<title-group>
				<article-title>Modelo de Unidad de Medición Fasorial PMU Implementado en el Software de Simulación en Tiempo Real de Transitorios Electromagnéticos HYPERSIM</article-title>
				<trans-title-group xml:lang="en">
					<trans-title>Implementation of a Phasor Measurement Unit PMU Model in the Real Time Simulation Software for Electromagnetic Transients HYPERSIM</trans-title>
				</trans-title-group>
			</title-group>
			<contrib-group>
				<contrib contrib-type="author">
					<name>
						<surname>Paguay</surname>
						<given-names>D.S.</given-names>
					</name>
					<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<name>
						<surname>Lozada</surname>
						<given-names>R.F.</given-names>
					</name>
					<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<name>
						<surname>Almeida</surname>
						<given-names>W.A.</given-names>
					</name>
					<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
				</contrib>
				<contrib contrib-type="author">
					<name>
						<surname>Lozada</surname>
						<given-names>C.X.</given-names>
					</name>
					<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
				</contrib>
			</contrib-group>
			<aff id="aff1">
				<label>1</label>
				<institution content-type="original">Escuela Politécnica Nacional, Quito, Ecuador E-mail: diego.paguay@epn.edu.ec </institution>
				<institution content-type="normalized">Escuela Politécnica Nacional</institution>
				<institution content-type="orgname">Escuela Politécnica Nacional</institution>
				<addr-line>
					<named-content content-type="city">Quito</named-content>
				</addr-line>
				<country country="EC">Ecuador</country>
				<email>diego.paguay@epn.edu.ec</email>
			</aff>
			<aff id="aff2">
				<label>2</label>
				<institution content-type="original">Operador Nacional de Electricidad - CENACE, Subgerencia Nacional de Investigación y Desarrollo, Quito, Ecuador E-mail: rlozada@cenace.gob.ec </institution>
				<institution content-type="orgname">Operador Nacional de Electricidad - CENACE</institution>
				<institution content-type="orgdiv1">Subgerencia Nacional de Investigación y Desarrollo</institution>
				<addr-line>
					<named-content content-type="city">Quito</named-content>
				</addr-line>
				<country country="EC">Ecuador</country>
				<email>rlozada@cenace.gob.ec</email>
			</aff>
			<aff id="aff3">
				<label>3</label>
				<institution content-type="original">Operador Nacional de Electricidad - CENACE, Subgerencia Nacional de Investigación y Desarrollo, Quito, Ecuador E-mail: aalmeida@cenace.gob.ec, </institution>
				<institution content-type="orgname">Operador Nacional de Electricidad - CENACE</institution>
				<institution content-type="orgdiv1">Subgerencia Nacional de Investigación y Desarrollo</institution>
				<addr-line>
					<named-content content-type="city">Quito</named-content>
				</addr-line>
				<country country="EC">Ecuador</country>
				<email>aalmeida@cenace.gob.ec</email>
			</aff>
			<aff id="aff4">
				<label>4</label>
				<institution content-type="original">Operador Nacional de Electricidad - CENACE, Subgerencia Nacional de Investigación y Desarrollo, Quito, Ecuador E-mail: clozada@cenace.gob.ec </institution>
				<institution content-type="orgname">Operador Nacional de Electricidad - CENACE</institution>
				<institution content-type="orgdiv1">Subgerencia Nacional de Investigación y Desarrollo</institution>
				<addr-line>
					<named-content content-type="city">Quito</named-content>
				</addr-line>
				<country country="EC">Ecuador</country>
				<email>clozada@cenace.gob.ec</email>
			</aff>
			<author-notes>
				<fn fn-type="current-aff" id="fn1">
					<p><bold>Diego Paguay Garcés. -</bold> Nació en Riobamba el 10 de agosto de 1997. Graduado en Ingeniería Eléctrica en 2023 de la Escuela Politécnica Nacional, actualmente cursa la Maestría en Electricidad mención en Redes Eléctricas Inteligentes en la Escuela Politécnica Nacional. De 2021 a 2024 desempeñó el cargo de Analista de Estudios Técnicos del Departamento de Planificación de la Empresa Eléctrica Riobamba S.A. Actualmente se encuentra en el cargo de Analista de Investigación y Desarrollo de la Gerencia de Desarrollo Técnico del Operador Nacional de Electricidad - CENACE. Sus áreas de interés son: modelación de sistemas dinámicos, simulación digital en tiempo real, estabilidad de sistemas de potencia, y calidad de energía.</p>
				</fn>
				<fn fn-type="current-aff" id="fn2">
					<p><bold>Ricardo Lozada Orquera.-</bold> Nació en Quito, Ecuador, el 5 de septiembre de 1998. Es ingeniero eléctrico, graduado de la Escuela Politécnica Nacional, y actualmente cursa un MBA en EIDHI International University. En la actualidad se desempeña como Analista Nacional de Investigación y Desarrollo en el Operador Nacional de Electricidad (CENACE), donde participa en proyectos de investigación aplicada e innovación tecnológica orientados a mejorar la seguridad, la calidad y la eficiencia del sistema de potencia ecuatoriano. Sus áreas de interés incluyen las energías renovables no convencionales, los mercados energéticos y la simulación en tiempo real.</p>
				</fn>
				<fn fn-type="current-aff" id="fn3">
					<p><bold>Ariel Almeida Carrera. -</bold> Nació en Quito, Ecuador el 2 de septiembre de 1992. Es Ingeniero Eléctrico graduado de la Escuela Politécnica Nacional (EPN). En la actualidad, se desempeña como Analista Nacional de Investigación y Desarrollo en el Operador Nacional de Electricidad - CENACE, donde lidera y participa en proyectos de investigación aplicada e innovación tecnológica orientados a la mejora de la seguridad, calidad y eficiencia del sistema de potencia ecuatoriano. Sus áreas de expertise incluyen el análisis de flujos de potencia y la integración de energías renovables no convencionales.</p>
				</fn>
				<fn fn-type="current-aff" id="fn4">
					<p><bold>Carlos Lozada Caguano. -</bold> Nació en Quito en 1995, Recibió su título de Ingeniero Eléctrico de la Escuela Politécnica Nacional en el 2020; graduado de la Maestría en Electricidad Mención Redes Eléctricas Inteligentes en la Escuela Politécnica Nacional en el año 2022, se encuentra cursando sus estudios de Doctorado en la Escuela Superior Politécnica del Litoral en Electricidad mención - Sistemas de Potencia. Actualmente se desempeña como Especialista Nacional de Investigación y Desarrollo en la Subgerencia Nacional de Investigación y Desarrollo de CENACE. Sus áreas de interés son: Sistemas Eléctricos de Potencia, Optimización Aplicada y Aplicaciones de Machine Learning en Sistemas de Potencia.</p>
				</fn>
			</author-notes>
			<pub-date pub-type="epub-ppub">
				<season>Jan-Jun</season>
				<year>2026</year>
			</pub-date>
			<volume>22</volume>
			<issue>2</issue>
			<fpage>0032</fpage>
			<lpage>0043</lpage>
			<history>
				<date date-type="received">
					<day>09</day>
					<month>11</month>
					<year>2025</year>
				</date>
				<date date-type="accepted">
					<day>15</day>
					<month>01</month>
					<year>2026</year>
				</date>
			</history>
			<permissions>
				<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc/4.0/" xml:lang="es">
					<license-p>Este es un artículo publicado en acceso abierto bajo una licencia Creative Commons</license-p>
				</license>
			</permissions>
			<abstract>
				<title>Resumen: </title>
				<p>El objetivo de este trabajo es desarrollar un modelo de unidad de medición fasorial (PMU) en el entorno de simulación digital en tiempo real del software de simulación de transitorios electromagnéticos HYPERSIM de OPAL-RT. La metodología propuesta para la modelación está basada en los lineamientos de los estándares IEEE C37.118.1-2011 y C37.118.2-2011 para la estimación de los sincrofasores de voltaje y corriente, la frecuencia y el ROCOF. En el modelo implementado la estimación sincrofasorial se lleva a cabo con el cálculo del valor eficaz (RMS) para una ventana móvil variable, el uso de controles PLL (Phase-Locked Loop), y las interfaces de sincronización GPS y del estándar C37.118.2 del simulador en tiempo real. Se ha considerado que el modelo sea eficiente en cuanto a recursos computacionales. Finalmente, se realiza la comparación de los datos sincrofasoriales del modelo de PMU con los datos de una PMU comercial en un sistema WAMS, en un entorno de simulación en tiempo real.</p>
			</abstract>
			<abstract>
				<title>Abstract: </title>
				<p>The purpose of this work is to develop a model for a phasor measurement unit (PMU) in OPAL-RT’s real time digital simulation environment of the electromagnetic transient simulation software HYPERSIM. The proposed methodology is based on the IEEE standards C37.118.1-2011 and C37.118.2-2011. For synchrophasor estimation the RMS value calculation over a rolling window and a PLL-based (Phase-Locked Loop) scheme is used, as well as the interfaces for GPS synchronization and C37.118.2 communications that the real time simulator has available. The model was designed considering efficiency in computational resources. Finally, the implemented PMU model is compared to a commercial PMU on a WAMS using a real time simulation environment.</p>
			</abstract>
			<kwd-group xml:lang="es">
				<title>Palabras Clave:</title>
				<kwd>PMU</kwd>
				<kwd>simulación en tiempo real</kwd>
				<kwd>sincrofasores</kwd>
				<kwd>PLL</kwd>
				<kwd>WAMS</kwd>
			</kwd-group>
			<kwd-group xml:lang="es">
				<title>Keywords:</title>
				<kwd>PMU</kwd>
				<kwd>real-time simulation</kwd>
				<kwd>synchrophasors</kwd>
				<kwd>PLL</kwd>
				<kwd>WAMS</kwd>
			</kwd-group>
			<counts>
				<fig-count count="12"/>
				<table-count count="5"/>
				<equation-count count="19"/>
				<ref-count count="24"/>
				<page-count count="012"/>
			</counts>
		</article-meta>
	</front>
	<body>
		<sec sec-type="intro">
			<title>INTRODUCCIÓN</title>
			<p>La evolución de los sistemas eléctricos de potencia ha dado lugar a la integración de sistemas de generación basados en recursos energéticos renovables, la digitalización, y la transición hacia redes inteligentes, lo cual ha creado nuevas oportunidades de investigación, desarrollo e innovación al considerar los nuevos retos introducidos por estas tecnologías. [1]</p>
			<p>En la transformación hacia redes inteligentes, la integración de sistemas de monitoreo, control y operación en tiempo real de los sistemas eléctricos facilita su análisis, caracterización y evaluación. Los sistemas de monitoreo de área extendida (WAMS - Wide Area Monitoring System) han probado ser una valiosa herramienta para el monitoreo y operación de los sistemas eléctricos en el mundo. [2] [3]</p>
			<p>En Ecuador, desde el 2010 un sistema de monitoreo de área extendido (WAMS) fue implementado en respuesta a los riesgos y vulnerabilidades que existían en su sistema eléctrico debido a fenómenos dinámicos. Esta implementación comprende la instalación de unidades de medición fasorial (PMU - Phasor Measurement Unit) en puntos estratégicos, y la aplicación de estudios especializados para mejorar la estabilidad del sistema. [4] </p>
			<p>Las PMU son equipos que realizan la estimación de los fasores de las magnitudes eléctricas, el cálculo de la frecuencia y la razón de cambio de la frecuencia (ROCOF); y asocian los datos fasoriales estimados a una señal de tiempo de alta precisión, como puede ser una señal GPS. La tasa de datos manejada por una PMU comúnmente es de 60 o 50 datos por segundo, dependiendo de la frecuencia nominal del sistema. [5]</p>
			<p>El estándar IEEE C37.118.1-2011 define los conceptos básicos relacionados a los datos sincrofasoriales, junto con los requerimientos mínimos en cuanto a la validación de la estimación fasorial [6], y este tiene una enmienda que revisa los requerimientos de desempeño de una PMU en el estándar IEEE C37.118.1a-2014. [7] El estándar IEEE C37.118.2-2011 define los lineamientos para la transmisión de datos sincrofasoriales a través de una red de comunicaciones. [8] </p>
			<p>La información de una PMU resulta versátil para realizar estudios especializados como el modelado y validación de componentes de un sistema eléctrico, o la identificación paramétrica y sintonización de sistemas de control; [4] y para aplicaciones de control y protección como la integración de datos sincrofasoriales en esquemas de protección y la implementación de esquemas de acción remedial. [9] [10]</p>
			<p>El software de simulación hace posible realizar estudios especializados de un sistema eléctrico. Para ello se modela el sistema de interés, y se simula su comportamiento dinámico bajo las condiciones operativas o de prueba que se hayan definido para el estudio. [11] La simulación puede ser de tipo EMT (Electromagnetic Transient), en donde se obtiene las formas de onda de las magnitudes eléctricas, con pasos de tiempo en el orden de microsegundos, o de tipo RMS, en donde los resultados son la representación fasorial de las magnitudes eléctricas, con pasos de tiempo en el orden de milisegundos. [12]</p>
			<p> La simulación de sistemas eléctricos se puede realizar con soluciones tradicionales, o fuera de línea, como son los softwares DIgSILENT PowerFactory, EMTP-RV o PSCAD, o con soluciones de simulación digital en tiempo real, como es el caso del software RSCAD de RTDS Technologies, o los softwares RT-LAB y HYPERSIM de OPAL-RT. </p>
			<p>En simulación EMT, para contrastar los resultados instantáneos de la simulación con los datos de una PMU, es necesario convertir a su representación fasorial. Esto se logra en el entorno de simulación al modelar el funcionamiento de una PMU. [12]</p>
			<p>En [5] y [13] se detalla la fundamentación teórica sobre la estimación fasorial, y en [14] se presenta una revisión de las técnicas utilizadas para la estimación fasorial y modelado de PMUs.</p>
			<p>En [12] y [15] se describe metodologías basadas en aplicaciones de la Transformada Discreta de Fourier (DFT) para la modelación de PMUs, junto con el proceso de validación utilizado para determinar el cumplimiento de los lineamientos del estándar C37.118.1. Estos modelos fueron implementados para software de simulación fuera de línea. En [16] se describe un modelo de PMU basado en un control PLL (Phase-Locked Loop) con la finalidad de crear un prototipo de PMU de nivel comercial. Este modelo no esta diseñado para ser usado en entornos de simulación de sistemas eléctricos.</p>
			<p>En [17] se detalla una metodología para la evaluación del desempeño dinámico de una PMU, con el uso de un conjunto de pruebas para determinar el cumplimiento de los requerimientos propuestos en el estándar C37.118.1.</p>
			<p>Modelos de PMU implementados en un entorno de simulación en tiempo real se presentan en [18] y [19]. Estos modelos implementan algoritmos eficientes computacionalmente para la estimación fasorial, y el despliegue de comunicaciones a través del estándar IEEE C37.118.2 para el intercambio de datos sincrofasoriales con PDCs, diseñados para el software RT-LAB.</p>
			<p>El software de simulación EMT en tiempo real de OPAL-RT, HYPERSIM, está integrado a los estándares IEEE C37.118.1-2011 y IEEE C37.118.2-2011 para envío y recepción de datos sincrofasoriales [20], mas no dispone de una herramienta o bloque específico para la estimación fasorial en su librería nativa. </p>
			<p>De esta forma, es posible desarrollar un modelo en el entorno de HYPERSIM con los elementos disponibles en su librería nativa, considerando eficiencia computacional, que permita realizar la estimación fasorial de los valores instantáneos de las magnitudes eléctricas en base a los lineamientos del estándar IEEE para sincrofasores, hacer uso de la sincronización por GPS del simulador en tiempo real, y usar la implementación del estándar IEEE C37.118.2 en este entorno para el envío de datos sincrofasoriales a un PDC, y su monitoreo en tiempo real en WAMS. Adicionalmente, se realiza una comparativa bajo condiciones dinámicas con un IED comercial configurado como PMU.</p>
			<p>En este artículo se plantea el diseño e implementación de un modelo de PMU, de clase P del estándar IEEE C37.118.1, en el software HYPERSIM para simulación digital en tiempo real. En la segunda sección se revisa la teoría asociada a la estimación fasorial, los sincrofasores, y las unidades de medición fasorial. La tercera sección comprende la metodología utilizada para la construcción del modelo de PMU en HYPERSIM. En la cuarta sección se analizan los resultados del modelo de PMU obtenidos de la simulación digital en tiempo real, los índices de desempeño del modelo, y la comparativa con una PMU comercial para distintos eventos.</p>
		</sec>
		<sec>
			<title>ESTIMACIÓN FASORIAL</title>
			<p>En esta sección se revisa el fundamento teórico asociado a los conceptos y definiciones necesarias para aplicar los lineamientos del estándar IEEE C37.118.1 en cuanto a los requerimientos de la estimación fasorial, y de los datos entregados por una PMU. </p>
			<sec>
				<title>Definición de Fasor</title>
				<p>Los sistemas de potencia están basados en corriente alterna (AC) en una configuración trifásica, de esta manera las magnitudes eléctricas correspondientes a voltajes y corrientes pueden ser representadas como formas de onda sinusoidales, en función del tiempo caracterizadas por una amplitud, velocidad angular y ángulo de desfase, como se muestra en (1). [21]</p>
				<p>
					<disp-formula id="e1">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>A partir de (1) es posible utilizar la identidad de Euler (2) para expresar una forma de onda sinusoidal como un fasor, la cual se presenta en (3). [22] </p>
				<p>
					<disp-formula id="e2">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>
					<disp-formula id="e3">
						<graphic xlink:href="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAjcAAABvCAYAAAAQauEdAAAAAXNSR0ICQMB9xQAAAAlwSFlzAAAOxAAADsQBlSsOGwAAABl0RVh0U29mdHdhcmUATWljcm9zb2Z0IE9mZmljZX/tNXEAABSASURBVHja7d0LmFVlvcfxGQZmgBkuw/2OgIAMIMT9KiB2BBGRo6JWaEloSiLWyUJEMG+ICKRiIij6aKkoXhE9oqZiZkJaIgqGppWV4dFDZdZJnf7/nt+y91lnrT17RvbMMHzneT4P7HXZe621N7y//X/fd03eRRddlAcAAFBXcBEAAADhBkAd+k8gL6+TWWQuMPNMz1p6nIWmXmxZD9Ohml57nBlp6pvOpiRhmxPMeeYy80WTz2cMINwAqP7QMNGUm2+aUaZNLTzGgeYXZkyw7GTzX6a0ks/VzbSMLcv3ZaYoYftG5mZzqQLgZnOiQsyhwXYeevqbseZV81NTwGcMINwAta1R7Wo6Zljf2JT5t/b9+BzHmz1maC09vgKvJilYdNWyI81y0zRh+/wMz3WQecOc7mEkWF5k/C9lCfu0Mr80F+vxWap2eZBZkxQG7ec+8yPCDUC4AWpTg+pdDOeaG8Nv5wnbeaP4DXOb6VuNx9dUXTKdFcB66XGjKoabd81hCcHNqxxd9BpdtLyNQoK/XqdqONd+5nZ19RSqQuKVlPGx7XqrW604OE4PMc31uJ3ez4/NA2ZCsK8/51J/jpRjWKrq1gmx5YvNmQnbbzRPEG4Awg1QW4JNPXOdWZ/yrbxYoaIoWHaKeda7T6rpGP31H1NF4VU11tvN02ZWZcZ6ZAg3peYeVTp2m9la7t1Yb5pdZko1nGuJjuFpdR91V9hpE2zjVZSfq6riAai93iff56ogEG4xO80A00TP3dy0NlebEaaZti3Qft82DyoY+XUaHbzuTLM2fr0JNwDhBqht4eYk87oHiJTg85D5tVcuEr7FPxB2d+T4ODeqmrBejbl31fxVy47+rOFG676k5yuP1tvPVD2eUx2Ntyo3e8139fgIc1dUpVKY8ffkeT2+0vxMIeUO85rGzXiY+Y25KXjuc8y1Cjbbtf0KVYm8O2q6+cRM1pgcv75Lgv0n6vo3JtwAhBugpoJLkb61HxQsa6Zv/kWqDDwcja+I7dtEjZ037L81R0VjQLS+iyopR1fDeTTXgFU/llOC5U9o2ddi2+er68ob6T7hrKMKwk2xKiLl6uLxc9zhXXFZHGN97Z+f5Tm1U1gYEXUtaflx5iMzQ48nqaIUhZuh6mo6W4/9PXhIf9+sgcgF2u7P5svBc7fQ63q32zV+DUxbqa9xMy9qWw+QH3gXVbD/BHN3wswpwg1AuAGqJdi0V3fGXg2g9Wm9Hc3L5k8aQ9Jd3S0TE8LBdK0rVzfJ/fHxFlq2OsMxNNJg1I4ZdKpo7IzC2F41+mOD8/ujju/wYNs+CgM/8WMzb3n1ImqQM4UbrV+o53zRbPMqR5bXe6CqIPUq2M67gJao6+t685xXYaLxL/Zzhc61hx6P0Pk00eMhqq54d9wgHetyBbE9QbfUnGjcjKZ1t4i9v/46vWJVuie9CqTHXtF7LzZWZ5KuZRHhBiDcADURbkZrjMSVauR8rMQP1BDOUWM2w/wqfq+XYKrwT7TvPAWVBrHtVqpaUC/DMTxq/jsDrxyNqOBcvqDjeF0DaTtoTIgvWxY1thr4u1uNchQWnlMo6qnH4yoIN/78v9Nzb0yaLh3bfqimSXtoulDVjfkpM5vqKRx8Wm2yn2/p8VeCoPBK1PWj7iKvlgzR4wYKYI8qvM3Xn/d6sAlC0GBVu3y72eHx2E9DhZuy2PGN1Pt5g45jRmy9v9b8hPMi3ACEG6Bawk2+/hxm/qYGdFFsm7mqzrRP2L+tBtL+wwxPeQ1vTF8Iu1Vi6xuqCyQTHyzcsIJzuVjH75WJH5t3VJGJz+ZZpe0u0WPv4vk/80xUucgi3JQqIJWHXTIZjs27eb6j8SuPqBozM+UeMtP0vFvVDdRT198raX3VrfVevFpkP2dEFZlgWYsosOg6t0x4vcKwYhMsr6/uymYJ6wpUBYqPq+ms0NObcAMQboCaDjntFAbejYcYVQ12pcySOlJjO15Naji1zTJ135Tk8PgLVX0oV6Xo86qs7AlDlyocr2i7DRr46lWbW32Kd7BdpjE3DbT9m+r68T/bVnB8HjKOVdfSO5omPzihypUfhC/fdp0CwTMaG+TT0C/R9ewd29erZgs0DqhVDXyGeqladGTKesINQLgBqrVh8tvif2j+4t/WY+tO03iabgn7LVBDfEuG575OXVcNUtYPV9C4K8XdCiFDMrxGe4UMP5bjtOx6PV4dbDdY5/mWzvmwqIsm9nyZws21GnfyOXWBlYcDclOOb4q6/Kao22amKhwtEkLa03rOBQqP4QDtw3UPoS4ZXssHIB9cA5+hsUk3/CPcAIQboDobo4b6tj9V41qimUbT1ci2DRp6r4KMS3iO9drnvODbe3GsEuEB5eYMx9FGjX4mXrVoneE5JmjMzJ6oYbefr+vYtgU3sRugLrRXYvsfGwsRafe5WayZUdFA3uV6jfsruNYN9GcfVZYKJD+hKvSUnnNELDiM2s8/b4QbgHAD5Lyxma4pwTs1qPcMNaovqNoS3cOlRAHh3ITnWK19ntW04TXhGA11A71kTszheTQOBuC+HwwSnhrcj2aSBuoWB91Xt6iKslnjYLqnhRvtN1/7LdaygmDWlDsxi1lQDSvqMgoGD2/T39fpfZpKuAFAuAEqDjfeBTJNj9vpFv6PqSsqvO/LQnXFxH8D9WB1G23W7fg7xNafropQ6xyex0BVkKIxNKdoeWuFrXt1A7pomnc3dQk9qVCzMN41FYSbaEr5MD3/fX53Xi0r1Tlv0HT3JXlV+FUPSVUeBanHdF3XZuruIdwAINwAVWuYvHqzyVxaiX3KVH2Yth+eb8b73IBwAxBugLrROPnU3zvN5fF73sS2K9JN4fzXLszaT8+VcEO4AQg3wAHSQPmYkeP9rrcZtmmq8Sd99uPzjMLNGN73fXZNHyTcAIQbADXXEPt06r9rIHJDGuTPdC0LdQ2f1C0BuJYA4QZADTTIAzXY+nYNSh7EdanSdSzSjC+/ho9rGnw9rg1AuAFQc41zgSoPNMhVv4Y++6uQawEQbgAAAAg3AAAAhBsAAEC4AQAAINwAAAAQbgAAAAg3AAAAhBsAAEC4AQAAINwAAAAQbgAAAAg3AAAAhBsAAEC4AQAAINwAAAAQbgAAAAg3AACAcMNFAPCv/wzy8g41t5qrzHzTI2GbzmaRb5vD42hg2vufwbJW5gRzrGmhZaeYr+yD1yuNnrOK+w81F5qV5mbTi88TQLgBUDvCzfHmEzPddDfFsfUjzdPmLNM8h8cx1bxlyvS4xDysADHHvGD6KYzda641hZ/h9R4x36/kPn3NIP29ma7XXFNujuDzBBBugNre6OerYe+SYZvm5rBcNvrVcJ7TzDumT8I6r6T81MzK8TEUmyFekTFNgmv7M3ONHh9lOgXB4nGzuAqvVc+0NCebMbF19X29/l4Q+yyU6FrcH1Z8dFx/NuNzfI0aZLFNoR8r/35BuAGQ1Ei0M98zK0zXDNs1NvPMBjO8mo9vpALBCDPOG2rTuorh5o9mQMI6vwabkhpM++kWHIP/2cEDgVc2/FqYsd6tlOUxjDbPmqVRuNDyK1QVOSdhH3/N16JKTyXOt5FZYp4Lw439TDYLgnDj57fQg4wC0Xwdix/nadE10fXLSbhRoPLXusAMC5YPU3edV9vaBMt7mfP8emV77QHCDXBgBBuvGDyqhjWpUe+uxqVxsMwbma3VFXB8XIz5hXnPvGHuMrvk25XprkkLN/bT0bxuvpyy33jzO/O++bGHAS33MSh/1ziellkeQyfzJ7M2qpqYVep+8rE+H3iFJLZPgbqtVlXh+l2ooDJQj6fqOk7ysODXQp+Dn5tl2uYyHYefd8PY9dvn4cZ+inQN71L4a6bg+ISuzUxzj3k5em1Vbnws0Bp1Jbbn3zQINwDy9C15a9iABeu8gfml+U38m7EazAc/yziQShyjd59sUQN9uRq1UeYvWvb5fRBuZqnB75iyn1czbtLrPaVl+QocXt1oW4lj8K6dj3ywsB6fqXFAIxUyPohCRsJ79VplBgbrGP19ekmDmJsrINyp9d7ttE1VucfVFeVB426zI/65yGG4Ocm86RWxYNkXzPNRhU5VqJd1zQsSPqcL+TcNwg1Q94NLJ31LHxp0P/TRN/ZGatC88ZidsG9HVUW8Md+pb859g/UHq9IxuRrO4yDzKx3LUVrWWINufdlxCfv0NCdqtlG/LMLNDV4lqOA4jtDr/Y+6RBYpGLRP2LZAAcxD0zGx7hS/rn/1Li499i6j54P3zNddmvCc/l7+Ialiphle0/R6Q6PGX+NtvOG/IwhW5ZqRVaxq2HVa97KCUGv9fU1KOMxFuFkbv/4KYm1iyx5WlaZBbPmN5pmwmw8g3AB1L9j4TJfH1GXyocaKDFfDvEfTjkerEjAgoUrhA1DfVkPoA11v8ZlGsYqAd2ctr+A4Dla31uAU3hAfkmlgqP0crkrHXtNbyz5n/qFlZcG2XtVZrADjXUY/VIUnqpIcEw83qmhsiQJAhuMoUZdUuYLV9qTp4jqfh9RttlhVk1c8pGn9PQocxXr8oNaXajbSr6NZSgnvqXeNfSm2/Gvmt2adBxVdqwu1zt/3j83ZejxG630w83E6l8W6xnsVYnvr2q5SoOqXy3CjSpEHkx9WsN1YBeqTEtYtUAhvwb9/EG6AuhtuvCGYoLET3oDdbh4wZ5ijtc1cNaptY/vmayzGjrTKiLbzwHNfWjDR81ygacibUjysAa+FGc7lGzoOHxPSX4HoKVUdZoWvr4b6X91Xejxcj2/KEG6aKqiszOK6nqHnc1MT1rdSGCwPplGviqZPq4vNqyKbgn08TNym6sMP/L3LUInzELMgWHaqnnu9HrdWF9cWPZ6px/8RVJTmalD4MnX9LNdYl9napqHuA7RR175VjsNNscLiioR1HlYnKrT5uR+b8hznqvu0K//+QbgB6n7ImaDG7+P4N177udi86I17wn59NOj1f736kvLc6xQyCjK8fn01lkUpfF39Cs5hjc7hLQWHjxUQBsW2668unfd1/L00HsYrFTOCxjkebtqq22tpFtfzTB2LN/ATEtZ/KwobarSPUeVoux731frTE/ZtVMFrlyqMLgyC1BvRuCPNKluvx/O0jYfa3dkOds7i/HMRbnyG1qs+qD1hnX8+vmjOV3eUV8QOSdjuq5riX8a/exBugLofbnpogKp3g5TE1l2ib8xNEvaLKgI/ShpsXIlw01hjJ5qmaBY/roQG/aWowdZN7d5W99qolODxhrqjHlFlaVqscY6HmxbqQlqaRcO+PahorU6oMmwKrtu9qkx9X7PORum47ky65lm8l211blG4maSqzPt6zqhCdpoqOGdqPM9J+/DzlItw0y6bcKnxQ7vUhdgktu5kVXYINyDcAAdAuFmsysW78Vvmq8thV8qA2KgrZUmG516vb9L5KevzNatqsxreJD5u58q0bilVOvbqHA7Tslt0bCti235Py72bZWDSvU9Swk0jDQxenuFch6hy5Pdb+U+FirejKeFBJWW3KjUzVD0KZ/WM0+sXVvG97KbXnKvHZ+t879S06XCmUXN1OZXt489TLsJNG123bCpnizRm7KDYcu9++3046B0g3AB1K9B4taO9wss9+qb7iWbK+LfkLtruSDWWQ2P7F2gwcrnK/fU0hie8100DTR2+rIJj6aqgcWiKAWq00wLSyToOD2GlWna+lm2J3QTvUi0/P1h2uAbP1s8QbvJVZbkj5Rh6arDqwiA47Ix3L6kS5VWdv+X9+9cq+HPPzovdHbiK7+shqk7M1OPTdAzrgm38Ws+pqIurloWbEnWPLo0t97FVExNC99a8//9rM85RuOnB/wEg3AB1M9ycrW6brZoiHH3D3617tfTXdt4l5DfHOyuh4hJVR15Sw+83+SsKtumtwDEmh+fRJri/zae/MkFVkU8H9QbTnkdokPFHGqezQWNzvhpskzYVfJnCWkFs+Wjdf6U8qgpoYO9rwTigvsF1W6DlOzQIdotuRDdgH1yPyZotNTKo5OzS692mLi9/3YVhEN0Pwk1jVc5uTAgsH6oqM1BdpbtSZkt9U5/vdvwfAMINUDfDzTFq3PsFIcFnTa2OunaCbRdofEj8viH91L1zg2YkFcXWX6EbwDXK4XkMUehYIpO1vLW6u5aqSlEY7DPeXKNwdmU4jbmCcHOqgkrnWMg7VVPK/eaBI7R8uK7nEs0qmhjs4wOoT9f1X6sGusk+uh7f0QDpsILWX9fIz/fqXIbNHIabqHK2Mba8gz6fK/VeXxWv5ATbrtBg8yL+DwDhBiAINVbX1YpKhqdt+6IaUQPnm+nXL+yM30OmFh13gULo5bXg+uXiJn7zNFi6VRX394HtV/NvGoQbAFHD0EYVmpXRTfJStmum8v+GtHux7K/hRusuUmWk1n3712DkHTU9YDaH4aaFuvBWasxY/SwDn49z+rqC0X4XtgHCDZDbRqueGtDuGbYp1Q3Vmu/H5xmFm7KEdS01dfqCWnbMLRS6FtSCY5mSl7vfCt5dXXnr4oPcU7YvU3eUjyMbxr9jEG4AHKgh7njdBPBozeSK/2LIXhoAPN8rVbXgeEdouv3l8XFR1XwcTXS9zorutpzD1yrJZiyXulRL+FyDcAPgQA83gzSr6HoNwO2VsE0rzTDrXwuO12eGTakFx+G/k+paDZS+NZq5BoBwAwAAQLgBAAAg3AAAAMINAAAA4QYAAIBwAwAAQLgBAAAg3AAAAMINAAAA4QYAAIBwAwAAQLgBAAAg3AAAAMINAAAA4QYAAIBwAwAAQLgBAACEGwAAAMINAAAA4QYAAIBwAwAAQLgBAACEGwAAAMINAAAA4QYAAIBwAwAAQLgBAACEGwAAAMINAAAA4QYAAIBwAwAAQLgBAACEGwAAAMINAAAA4QYAAIBwAwAAQLgBAACEGwAAAMINAAAA4QYAAIBwAwAAQLgBAACEGwAAAMINAAAA4QYAAIBwAwAAQLgBAACEGwAAAMINAAAA4QYAAIBwAwAADnj/BFi5A7XjqRpdAAAAAElFTkSuQmCC"/>
					</disp-formula>
				</p>
				<p>Si se considera la frecuencia como constante, y, por lo tanto, la velocidad angular constante, se puede despreciar el termino e jωt . De la misma forma, se puede considerar el fasor solamente en función del valor eficaz o valor RMS de la onda sinusoidal. En (4) se presenta la representación fasorial de la sinusoidal en su forma exponencial, polar y rectangular. [22]</p>
				<p>
					<disp-formula id="e4">
						<graphic 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					</disp-formula>
				</p>
				<p>Esta definición de fasor es la que se utiliza en el estándar IEEE C37.118.1 [6], y en este se aclara que, para poder realizar comparaciones, todos los fasores deben estar referidos a la misma velocidad angular.</p>
				<p>En la <xref ref-type="fig" rid="f1">Fig. 1</xref> se presenta una comparación grafica entre la forma de onda instantánea de una sinusoidal (1), y la representación fasorial de la misma (4).</p>
				<p>
					<fig id="f1">
						<label>Figura 1:</label>
						<caption>
							<title>Onda Sinusoidal y su Representación Fasorial. [9]</title>
						</caption>
						<graphic xlink:href="data:image/jpg;base64,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"/>
					</fig>
				</p>
				<p>El valor eficaz de una onda sinusoidal pura se puede obtener al dividir la amplitud de la sinusoidal para 2 . Sin embargo, las formas de onda asociadas a voltajes y corrientes de un sistema eléctrico no son puramente sinusoidales, es decir, presentan alguna distorsión. De modo que se pueda obtener el valor eficaz de una onda sinusoidal distorsionada se puede utilizar la definición de valor eficaz, que se presenta en (5). [13]</p>
				<p>
					<disp-formula id="e5">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Cabe destacar, que para el cálculo del valor RMS de una señal periódica cualquiera, se debe integrar sobre cada periodo o ciclo de la señal de forma individual. [13] De esta forma, cada ciclo de una señal periódica tendrá asociado un valor RMS. </p>
			</sec>
			<sec>
				<title>Definición de Sincrofasor</title>
				<p>Un sincrofasor es una representación de una forma de onda instantánea similar a un fasor, como en (1), con la consideración de que el ángulo de desfase 𝛿 está referenciado a una onda sinusoidal a frecuencia fundamental cuyo parámetro de tiempo este sincronizado con el tiempo UTC (Coordinated Universal Time). Este valor de tiempo debe provenir de una fuente de sincronismo de alta precisión, de modo que se asegure una precisión en tiempo de 1 microsegundo. [6] </p>
				<p>El ángulo de desfase total corresponde al desplazamiento en tiempo entre la onda sinusoidal de referencia, y la forma de onda instantánea. [14] A partir de (1) se puede establecer el valor de la amplitud en función del tiempo y el valor de la velocidad angular en términos de una frecuencia en función del tiempo, como se muestra en (6). </p>
				<p>
					<disp-formula id="e6">
						<graphic xlink:href="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAjcAAABGCAYAAAAwybXjAAAAAXNSR0ICQMB9xQAAAAlwSFlzAAAOxAAADsQBlSsOGwAAABl0RVh0U29mdHdhcmUATWljcm9zb2Z0IE9mZmljZX/tNXEAAA6mSURBVHja7Z0HlBXVGcff7rJIBwHBhRUMEgmgIAgoCKKASJFNaGIDRRAsFBGwgQYU0ETQWEgsidhjV4IFcqyxJZZoYostEcWuiYkmRoxu7nf4T7zOuTPvLb597JLfnvM7e97MvTN37szc+5//9817mcWLF2cAAAAAthboBAAAAEDcAAAAACBu4P/3IstkGjlGO76bUmZbx1jHTrXgeFo7xjm2TylT7hjv2G4rO5fdHAc4tqkl7W3mqBdYXtcxyo4npW5Dx/cdu2xF58/6o773eS/HfgXab3GWMnWsHGMmIG6gNgymXRzXOBY5ylLK2WQzyXGHTSgFaluxY6BE1Q8cIx2NHc01qY3TsgZenQGOmx2zrGzKtps65jlW2wSylZzLKTr2Ud6yDlp+vONYR48a0tYDHVc6nnTc5mjlrdvBcaljubU/y/VhovxXjsm1/NyVOZY4fq1r8hzHno6ejlWO8+yarYb9HqR+nmr3eGC9XT/THX1MhDoOcay0eoyfgLiBmjqgtnE8bpN8wvo9JSqaxJ4kn3LsX4D2FTlmODY6/uO4WCKrgdrwueNoR6nK7+540TEmsK0SxxDHsKi8lo9XH9Tqp3/3N83xTOSs6Xgvd2zQZLTM8anjI8fJ9hS+Bdtq57RS7ZvsuMXRQusaa4JfkVC3u8Ruy5hA/63jsGpoawcJqPY5li+1a6mqDof7O9fxld1Xjr0d7zs+NtGna/4KCb6SPB7bUY7fmzPk96fW1XecoXNxXiSK5fBY+ReSxg0AxA1s6QnRng7vDdnRFq5xfOh4Jz5Qu7/ZjvstLFCANjbSxGWT4VneBPeW4ySvXB1NkpcnbKeHtvFoYN0Fjqtr8Xksl6ib6C2zkM3Ljt9E59f6T33wXpojUs1ttUnzJccXIUHp/k7QhNsoQTg8L1HbMbbOROoT+Q4zur816rNBOZa3++aBqoaS3N8vtJ/R+txf56uJPluo9WnflfuWx2Vh5j85jks4RzfpfmqXUP9Ex6vmsjGWAuIGCjmJmJ09U0+dkbMxRE5HE2GD5cGBul30JGmD7SsmIhz9YpOpLR9foGOZr7Y8oqdic1qWBdpsk+YeAcfG+uJ6bcOE0hxH15gb9RdHryztqKeclgY5tLmuXKKFmgjG+ROFOSyOIx2L9QTdNcv2BmjiX6YwUw9v3VT1SYOY2Ovn51G5v8PVB2/4ToTtW+Jgiq6PY9Qm//OuKW1rqW0UZTmGMh3Dl45/6th7xfrsgZAjoP5aqPab4D7dFxASwXY9z87h3HQ2sZClTBv1678c/3b8SI5RtryUlnI7BlXxGv+eY73jXUffhDIrFYKrk4d7apBEbv/AugW6l1qm1O+jh5/hjLeAuIFCCZvejvscn2kyMJt7uOMfmhiaS+iYQOkcq1usQfwd1TWHZoVjRKzcnY6LUtrQXiGtihRGReGILMezs+NtTTJvKFejNOAmWaiqeUCQHKdJyo7ndh1PH69MU02Ms1KESl2FCK7T03ndpElG5VYrrHCi3DHb9/Fav68msieVz/CMJppDAtsq0RP85woPWN7MX00EeGVutLyMHPrxUrXjIoX8SnSu12t5xJexzxYuOTL0hO8dz8+8p/6iFPfsfm3zOTlmg2MTprkBA2P1inS9vqS6j+scHhRwP25O2HdxJP4kEoZou9ukPBw8pP3Zfn+ivs8mblo41lmfVPGenSCnrVL/dwqUGa+2tM3DGHGshNQuAQH6iu4Zc3c6htwwE+q6F6cx5gLiBgrp2nTVxFqpJ8k1Sr7trTJzZPFvlzBARxPJ8IR9rFJycdJEto+s7RtTuCourlKO6TK151kbdAPrL3HcExIccnU+lbjrkjDxPWgTWMK+O6qtBylfZZJyIL6TUP5stfV8fd5VomqAHLNoEuun9SP12UJt5QHH4u8SN7tq2YhIiNnkLFG3KAfB+5kEVbmWNVYy6RjHhdrHSAnTR5TnVKHPoTeahum8TFBy9myJgHo5CKxlgXUHy0HrlCAwH1TdyQnbXipnLtRW66fzle9jydUT1ZZhKW1dpf0tqcK9Z+HAu3JNUpf4vlD7mevlI10Tz6/R9bPBF+bfYoyYJxHTLrY8egg6W6LarvPXHGfGctVMBL1pYwxjLiBuoNAiZ4Ceui2/YWhs3TLlNjQO1NtNTscHKTH3VZpsSgpwHKVe7kMwzi8hdXtC/QrVfcp/zTYmbh5KytfxxMFqPa3eqOTlkJBqov1UJoT8DtC6d6PQkEJdf9Py/QIu0AveE/1k3z1QGMSWz0lpe5m28XTK+bzb8WeJCCv/ieqkvXG2jfr2CU265ygBN0nwNvDckHGB9cfp/JYnOAVvSYD1TBE3zyUl87q/HeX4mAv4mN64a5jS1kf9PJiEcp2Um2JuzVo5ph/JXVqr5euS3jBUCMj2cZsnpD+RwIi7Kv11Tw7Owz11RuheUgjyKwmt5lo2Xa7pUK9cM+XsLGWsBcQNFFrcdNLT+svxSUpPYk8liJtpGnDvjod/vDJXpIkbTfId5TykUT+H4/i542FNvtau6YEy16eIm8hJWZmwPlXc6NVkc2xuUE7ILXLFWiVMwq9rfwcG1h+qdW96DsqOXmjosECdfSUgojDRE5HjpRCjTTInJLS9vpy7Z1OETSuJk/v0+UDt59Ys52V39e0d6perlddTN6H8Lpq4jd0C64+Wm1CeIlCfThEvieJG/XCE3tB6QMLDxFi3hG11V17Qe5n0739qrdypY3XfzNP5OFefj9G6boG67dXvG6MwloWcvOtnWIK4GZSHseHHcmR2CDg6H/vLdS+/GjmRWtZI4dQljLWAuIFCCpsi5TRslCsQz62ZrYmkbaBu9ObGGSnbv1lORtJT+v6aVNelsDotUVXb+aEmrO0zm74HpFJPx/Vi5VZKAMWX1/NyXialCAAL1yxPEYmnKNS3VLkh80NiQcnWr6eIsNFeUqwvbjZo+YgUsThNk0wUtiiSq2Vi55yEehZ2+l3mm6/z9/dDal6blnp1KpMEU+wcT9f2TlcC85yUPJYKL6k79DbUePVD98C66NxfltKe8+XIlCY4MacoZHuiQnuWMLx3wraO0P7urUoCr9wsy0fbM4ey+2ofGyIxISH9rpySHrHyw7SuRx7GhyUJzs0MiZuOMSFj9+CV3rKmcvZwbgBxAwURNW2U47FcoaO1kYugNzI6qdxADap9Ay7GfaozTYPYWH8ykmCwV4wXprSjngRJGq2SnCFPgL0RPeUrNLRRblSfWNnJoZCGwjav6XgGa/Ko8B0nLXs2k+WLyZRgeUo8aTkwud2k/d0Q7UfhqA465re1fh+t66dQwPq42FQS7mnediao7j2RsNR5vjPQlmEK46yW+FiqnJgNviugfKX/OU1yYiolAHbOlvQtl+P4HK7NyEG7NmF9V/XB6MC6a1V3ka4tyxNqGbtub01y5wITeO8sZRbFROSopByrwPW2Lhd3JbPpra3IHYq+52dKFKaKO2BygB4P5ZxtxjgxT45uXNz0VFhtrLcsCpv6XzUQ5dyczLgLiBsohLiZm/n6Laem3mD5gcIGkbhpKLdibmAbF6vOej25LvQHWuXkmJDoVU3HYE/ZJ6kNz3tvuYz1QjMP+cnQcj+sTRUBkbVOdV6QKJjqO05yLuzJtCwHN6woh/b39JKGX1X47+HM11+ENllPx39QkvKjeiIPhbHGaDu/VI6InQ97W2q8V2aCEsDbeMtaeG0I0V/lhuqzJQ/vrGVRftMzEj7l2folhz6p64nmBQllinWuVgTWna6676sPlme++TMFFs6x7/oZmYurmUOZg7W/z3QvmYBsnaO4sfJDcihboty3LxQiO0rXwdpM4EsD5ZZekKd7bKbcwy6Bc3Cm3LUJEuV3KTRcGnMobXw4mnEXEDdQCHEzUO5CW31uorj/qZnYd6kogfOxQD5OO71RsiD0NokmvKvTXJdveQxRCGaGhEhrLR+uYzlGrk67mPBYESVmBhyBueqDfgHBcldaCG4zj8HyiWbJLZnpCw+t7yMBd7ZCXJ0TtmOvnR+mnJ+zVKd3rEwz5ZHMj4mbqV5/+Uzx+nQP9fOEKJwk52+++rhNnvqjzAvXDU4pN06iL+5gtVLbF0jwxd8kWqzz2CiPAnuirplJuW5X/W5CaK8q7GuUwq8m4A7JhH8Goa/cxV55Oj5z9T7MJH+nzki16VQJveLY+t3lOI1g3AXEDdQ0IVRHCZZXZXL8tmFNmA/nYtFvgeNpoQluaY7lSzQprvFzUmrpuewrh2hMDW1f9Lr7i5ks3yKc2fSFeWsyKV8iFys/WuGaHjXgOIuVo1Kax212kFs1I4/bbKlzcdJm1p+l+mWMpYC4gZo46TSUNX5JJv0XmLfVk+WVmcB3xdSg47Fcnp/K5m+bUq693mhZmcnDl6LVkGPvp9yUmdXlqm1mu8q80OChOYrOk7M5IEoEN4fxuiQHYis4pxV6E3BaNWz7cIV9D8hFpMjl3F65a3/0nUIAxA3U1EG0c1puhUJF3TNb8AcXq3g83dISYRXuqdU/lpkiVndLeh17C7XpNCUpT6xivZ3SHEKJm+6ZHH4Oo5aeyyK9BNC2GvcxTjl2h2ay/3xGqV5MWJkp0E+vAOIGAKCmTtKN6AcAQNwAAAAA4gYAAAAAcQMAAACAuAEAAABA3AAAAAAgbgAAAABxAwAAAIC4AQAAAEDcAAAAACBuAAAAAHFDJwAAAADiBgAAAABxAwAAAIC4AQAAAEDcAAAAAOIGAAAAAHEDAAAAgLgBAAAAQNwAAAAAIG4AAAAAcQMAAACAuAEAAABA3AAAAAAgbgAAAAAQNwAAAIC4AQAAAEDcAAAAACBuAAAAABA3AAAAAIgbAAAAQNwAAAAAIG4AAAAAEDcAAAAAiBsAAAAAxA0AAAAgbgAAAAAQNwAAAACIGwAAAADEDQAAAADiBgAAABA3AAAAAIgbAAAAAMQNAAAAAOIGAAAAAHEDAAAAiBsAAAAAxA0AAAAA4gYAAAAAcQMAAACIGwAAAICthf8Cs3WzyxnUH14AAAAASUVORK5CYII="/>
					</disp-formula>
				</p>
				<p>Si se considera la frecuencia nominal del sistema como 𝑓 0 , entonces se puede definir el termino 𝑔 𝑡 = 𝑓 𝑡 − 𝑓 0 , el cual representa la variación de frecuencia en el tiempo. De (6) el termino 𝑓 𝑡 ∗𝑡 puede ser reemplazado por la integral de la frecuencia en el tiempo. [6] En (7) se presenta la aplicación de estas consideraciones. </p>
				<p>
					<disp-formula id="e7">
						<graphic 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"/>
					</disp-formula>
				</p>
				<p>Al aplicar la identidad de Euler a (7), se obtiene la representación fasorial de un sincrofasor, como se muestra en (8).</p>
				<p>
					<disp-formula id="e8">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>De forma similar a un fasor, para la representación fasorial de la forma de onda sinusoidal se utiliza su valor eficaz y se considera el valor de 𝑒 𝑗 𝜔 0 𝑡 como constante. [6] El sincrofasor asociado a la forma de onda original se muestra en (9).</p>
				<p>
					<disp-formula id="e9">
						<graphic 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"/>
					</disp-formula>
				</p>
				<p>Al comparar la ecuación de un fasor (4) con la ecuación de un sincrofasor (9), se observa que el resultado de referenciar la forma de onda 𝑥(𝑡) a una onda sinusoidal pura a la frecuencia nominal 𝑓 0 , resulta en la introducción de una componente de desfase angular adicional al desfase angular original 𝛿, la cual es resultado directo de la variación de la frecuencia de la forma de onda 𝑥 ?? en el tiempo.</p>
				<p>En la <xref ref-type="fig" rid="f2">Fig. 2</xref> se muestra el efecto sobre el ángulo del sincrofasor resultado de la referenciación de la forma de onda a una sinusoidal pura a frecuencia fundamental. En este caso se ha considerado que la forma de onda tenga un desfase angular 𝛿 igual a cero. </p>
				<p>
					<fig id="f2">
						<label>Figura 2:</label>
						<caption>
							<title>Desfase en Tiempo entre una Forma de Onda a f<sub>1</sub> con δ=0 y la Onda Sinuoidal Pura a f<sub>nom</sub> de Referencia</title>
						</caption>
						<graphic 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aff/wCp7KPfX7v+CaUnVP96snUo2FhdeWMyWkguoh9DuI/H5h+Najh8r84+96VBMrJeRNuGJVMRyPxH9fzqW+VqXYpLmi49w0qVZ9OjljfejlmVt27ILHHNSP/AMhCH/rm/wDNaxfBqXMWiva3F0JntbiSEHZjCg/KPpjH5+1bLBhqEOTn92/b3Wtq0eWpJLuZxd0mNMiDVSpYZEIyM/7VJqMq/wBnXGHGfLPQkfy5/Kn/APMTP/XH+tJqX/INuMZ/1Z6Z9Pbn8qmHxIplfSpFhFzaFgPIlO3n+BvmX+ZH4Vf8xP76/nVG6P2PVre56Rzj7PJ7Hqh/PI/4EKs312ljZS3D8iNc47k9h+J4rNOy9Cnq/Uo2jrc69eXJYbLdVto+e/3n/mo/CtPzE/vr+dVdJtGs9Ojjl5mbMkp9XY5b9TV2mlZEvVjPMT++v51g+JYjcwHyW/fRBposE/eTYR7fn+FdDVKQZ1OIEZG2TPBx0X8Pz/Crj5ef5B6klnexXlnDcRsNsqBxz6ikvr2O0sZpy4xGhbrWd4fb7FNeaQ55tnMkOe8THI/I5H5UmvH7dc2mkpz57+ZNjtGvX8+n41D126/1+AJ21fT+vxJvD0QttGh8wgSzZmk57tz+gwPwrT8xP76/nTulLVMSVkM8xP76/nXLpb22leKpL2BVQXU/lzMCTncqnv8A7WOnHzGurrF1Oz+12d+ASrLLuVsHj5F559OvHHHrmhWXvPp/T/Aq7acV1/4dfiascibT8w6nv71keIJRcLDZI/M7CM47BuCf++A9X9KvBe6bHOwCuciRc/dYHDD881QsP+Jjrk131itwVT/fYD+S4/77NK3vJPpr93/BsTe8brrp9/8AwLmyHjVQFZQBwADR5if31/On0UDKepDz9MuoopUSR4mVWbkAkdcDmsjwrNJBC1tdzLJK8aXG8Dbkn5WGD6MvP+9W/P8A8e8n+6fX09qwZidPksr3okagydR+7YBX688EI3PvVL89P8v8vmOT9y3bX9H/AJ/I3zImPvr+dYlo4u9ZiZjhYIzOef4n+VB+CKf++q09RmWO0YM4TeCCx/hXGWP4DJqvoMTfYWupE2SXbebtP8K4ARfwUD8c1Md2+35v/gfmKWyXf8l/wfyNDzE/vr+dHmJ/fX86fRQBz/ieZR9hTyJZ0uJvs8nlfwq6kZP0ODzx+laGj3n2jS4WmcecgMcvP8ana36inapF58cEeSN0wwRng4ODx7+vFVNOm8jVZYmG1LxfOQeki4WRf0B/OqXb5/5/oObVou22j/T9S9eyK8SwhhmVgh57dT+gNUtKdJobu+LLm6mJT/cX5V/QZ/Gk1e4ch0gP75/9FgPo7/eb/gKjP4GtJIEtbJIIhiOJVRR6AcCphs5d9Pkv+CKW6j21+b/4BJ5if31/OjzE/vr+dPooA5e9uYbbU5HEyeZYvHNsDc+U5YPx04D5/AZ7V0vmp/fX86ybmxtjrc07wJie3W3mfackMWA56dgPxGe1S6XdmPS3juWJnsiYZfVivQ/8CGD+NO9o2fT8hyS5049fz6jNTvfJhvJ4mBkRBBDz1kbp+pX8qvWcUVlZQ20bjbEgQc9cDFZwjNxqdratgi2/0q49PMbIQfqx/wCAitqlFWgr7vUTd5trZaETyJlPmH3vWorxla2Yoyl0Idee4Oank6p/vU48ilJXTQ4uzuYOlzpDqgYOPKvomdSSeXRiO/PKsP8AvmtZmVtQh2kH92/T6rXPWdlLY6Gdk09zcWNy1whkJ3MmSCoz6ruGPXpxit5biKe+tjE4YPA8ikd1JTBq5y5vefoJxUZuKd1uKd/9qnBXHkjHHP3qTURIdNuB8pzGeNpP6A5qSW0WWcSmSVWC7fkbAxnNMl06OeJopZJ2Rxhh5p5FEXZpgSXNsLu3eCYK0bjBHP8AnNUxptxJJD9suxPHAdyL5e3cw6M3PJH4c81b+xj/AJ7T/wDfw0fYx/z2n/7+Gosr3Hd2sS/vPVfyo/eeq/lUX2Mf89p/+/ho+xj/AJ7T/wDfw0xEv7z1X8qqOH/tOE/Lwr87T6L3zj86m+xj/ntP/wB/DUf9mRmYSma4LjO0mU/KDjI/QVUXZgRX2ltdXUF3DMILqDIVwuQynqrDPIpNP0t7S4nup5hPdzn5pCuAqjoqjPA/nVr7GP8AntP/AN/DR9jH/Paf/v4alKwPUl/eeq/lR+89V/KovsY/57T/APfw0fYx/wA9p/8Av4aAJf3nqv5VXtlfzrv7vMv90jPyL6nn8Kf9jH/Paf8A7+GmJp8cbOyyzgu25j5p5OAP5AU07JgZx0O4Q3H2G9FvFcN88Zi3AY4yORzjA/CtKysxYWqwQkbVySzclieSSfUnmhbEKMefcHknmQ077GP+e0//AH8NJaKwPV3Jf3nqv5UfvPVfyqB7UIjN5ty2BnAkOTWWNSjWIPJHf8gY8tiwJP8AD2OR34oA2Jw5t5OV+6ex9KrLafatMgjfaP3a4yh4+XBBBPTGQQaz5NStxBI0keobRIsON33ywz8vPI/yKWG7j+xloIb5I4isY8xyoAPHXk4Hc03ZxswTs7jl0CdlSC4vfOtEAURmP5mUHIQtn7vTPc4AJrXj3+WvK9B2rGXU42OPI1MDfs3E98kevtWnHZr5Sfv7g8DkyHNIVix+89V/Kj956r+VRfYx/wA9p/8Av4aPsY/57T/9/DQMjvA5e1+6cTD+EnHB9Dx+NQ32lNdndHOIXDiRWVclXHG4c+nBHQip5NOjlKF5JyUbcv708H/Jp/2Mf89p/wDv4acrNLyBOxTstKlguFuLmdJ5UUpGAhVUB+8cZOWPc1fl3+WeV/KmfYx/z2n/AO/hpr2IZSPtFwue4kOaVxJE/wC89V/Kj956r+VRfYx/z2n/AO/ho+xj/ntP/wB/DQMiMRlvrhHClWhQH5Tzy/fOP6/pVWbSLlrpbmG7jWUAK2+IlZAM7SwDDJGeDVwafGJWkEs+9lCk+aeQM4/maf8AYx/z2n/7+GiVm7ju7WI7GxaxiceZ5ssjb5ZWHLt6+w6ADsBVn956r+VRfYx/z2n/AO/ho+xj/ntP/wB/DTbvqyUrKyHvvyvK/e9Kd+89V/KoGsQ2P39wMHPEh5p32Mf89p/+/hpDKtnbyNbxyIyxyKzjJQ8gseCCc1Fp+mtpupBRMrwvG5VNmPLOV4Bz93ngdquRadHDHsjknVck4809zk/qakjtUjlEm+RmAKje5OAcf4CiVnJyXUd3awstykUgjIdmI3YVC3H4VFNqUNvC0syzJGgyzGJuB+VV7y6ks9R80xK0AhHmMG+ZBu64xyB3qTVnf+yLhhtA2ZBDsP1Az+VCethxjdrzJ/ti/wDPKf8A79N/hR9sX/nlP/36b/Cpcv6L+dGX9F/Ogki+2L/zyn/79N/hR9sX/nlP/wB+m/wqXL+i/nVXUNQNhEhMfmyyuI4olbl2Pb+pPYUN2Al+2L/zyn/79N/hUR1S3FytuRMJmUuE8lskDGT09xUUOpTrqC2V7AkUsil4WVyyyY6jOOo/lTXZ/wDhIoRxzA5xvbHVe2MfnzTjqNLcufbF/wCeU/8A36b/AAo+2L/zyn/79N/hUuX9F/OjL+i/nSERfbF/55T/APfpv8KPti/88p/+/Tf4VLl/RfzrMn1a4a/eysLZJ5Y03SM0m1E9BnHU/wCNJsC99sX/AJ5T/wDfpv8ACsaFrmeSWS21Gfyw7YH2dmIzggHI7Z7e1aOmamdSgY+V5U0bbJYmblD+XI96bpDOYJujfvO7sf4V9RVJDWsb/wBdSkU1Nzk37gE8hbVuPYcUttDfx3CvPfTSRAlin2dsk89/TnpWzGX2nhep7+9Oy/ov50hGHHBfxRiNNQuWUKfme3ZmLY7nHTPNPlXUWWPyryRXCKJC1s2HIUg4HbJOa15ZTDGzuF2j0JzWP/bt46faItPV7UOV3CX5nx12jHPcD1xx1GS+tg6XBWuYLiKW6u5mjVsAeQwJ4JOcDBP4U6Y3NywuLW8uI96IB/o7FccknHqcj8sVbubgXFpBNCyNHIdysrsMgqT2FT2Zc2UBwp/drzuJ7e4zTtoxvZMyni1EKfK1GcE4x5lqTjn2FSKL3+0jcfbJzbls+T9nP3cHAzjjr+Na5L46L+dNjL+WvC9B3pCMMW2oLGyrqNyCRjBgY9uTk8gnrxwOcVKkd8IAkl5OXEhIdbdhhMYx7nr19faruoal9giZmQMVXcQCfXAHTkk8Ad6rw6vcrcpFfWiQCVtilZd2xjyFbjv2IyM8ULV2QPTcoh74SskuoSY3iMYt2yWIz6fjW79sX/nlP/36b/CqkrP9pHT/AI+lH32/55/T9On41oZf0X86dtExtWZF9sX/AJ5T/wDfpv8ACkN6gHMU/wD36b/Cpsv6L+dNl3+WeF/OkIZ9sX/nlP8A9+m/wpr38ccbO6ThVGSfKbgflVO61mWJkS3t1leQMyDeR8o6ueOF/U54oGoyXFvdwTxpDcxRFiFkJV1IOHUgZx17ZBpJ3V0O3vKLLg1CIytGEn3qAxHlNwDnHb2P5U77Yv8Azyn/AO/Tf4UxC/8AaUwwv+qTjcfV+2MVYy/ov51UlYRF9sX/AJ5T/wDfpv8ACj7Yv/PKf/v03+FS5f0X86jnneFAdgZmO1VB5Y1LaSuxpNuyE+2p/wA8p/8Av03+FN+3xCQR7J95BYDym6D8PcVntqlzc3jW0EEJET7XkMhwSOqr8vJGec8friZbG+YqRqsmMd4I/wDCqSutyW7O1rlmPUYpk3xpMy5Iz5Tdjg9qljukklEYWRWIJAZCMgY9fqKqOl0bqT7Ncw52rmKQE7OTzgEdefy9qmUOL6EPt3eU+SvAJ+Sh7jFKhtSZWAIMGCD35rOdjFot9ZsSWtQUU5bJQ8r93npxx6VoeWh1UkqpJhGTj/arN12NYHaQKNtxC0JwpPzD5l+7z03dKh6NM0p/FY3aKb5af3F/Kjy0/uL+VUZjqyLYfb/ENxctzFZD7PF6byAXP5bR+dX7uWKzs5riRV2xIXPHoM1V0Oz+zaRAJlHnSAyy5H8THcf54/Cl1DoN8Q2rz6YZrcf6TasJ4T/tLzj8RkfjUdvcpeavZXMRJjmtGdeW6Ep6fL+fPp3rV8tD/Av5Vy+hRi31+XT2XP2QShcq33GZWXn7vqOeeOKqO/8AXYpHV0U3y0/uL+VHlp/cX8qRJDfXK2dlLOxAEak81S8PWrQaYs0o/f3R86Qnrz0H4DH61B4hRbhrPTkUZupQHx12Dlv0BrZ8tP7i/lQur/r+v8gfRf1/X+ZjXI/s3xHBcLxFd/uZPr/Cfz4/4GauaPnyJs5/1vfd/dX+9Ueu2QudMcIArp8ykDoex/A4P4VH4ddbnTPOaNQZCGIweDsXI598jinHZrt/mv8AgldPW36/8A1Y/un6n+dPqKONNv3V6nt70/y0/uL+VIkydelkcRWkDFZJmCKR2LZGfwUO3/ARWj9kiWyFrGuyNUCIB/Djpj6Vk2iLe+IJJdqlLdCRx/E/A/8AHVz/AMDrb8tP7i/lSSvHXrr/AJfgF/euumn+f4nPWkjQvLZMNoEnnxqM8BgwdRjsHDfgw9q3LP8A48YP+ua+vp78/nWHrMKWupW1wQAolw2AfuyKV7f7QQ/jW3Zxr9igygz5a9j6e/P51Sd4Xf8AVv6uNq2n9f10Jz0psZxEpP8AdFBjTH3F/Kq1yq/YlRVAaXEYOPXr+mamTsrhFXdjPiH9oazHuGY4R9pcf7RysQ/ABm+pFW9Ws1uotrEqso8pmHVc8q31DYx9aj0KJJbWW8KD/S5WkXjog+VP/HQD+NX7i2Sa3kjCqCy4Bx0PY0Ti4pJbr8/+HFBqTbez/L/hjJsLt723hllGJhdBJVG7h1TDDj3B9vxrcrmbNx/bMsRjASaaO5QbW6lNrj8CB7c+tdJ5af3F/KtJWaTXUHdOz3Q6qt+S0AhX70zBPoO5/LNWPLT+4v5Vj60+yC5MQAkCLbxcf8tJCAPyyDWUlzWj30Ki+W8u2pLoyi4e51DAxO3lw+0SZC4+p3N+Iqlq6NaW7XEY+azJU9RmCTgjjng8/wDAK27e0htraKCNBsjQIvHYDFU9Wt42hcMg2TQvC3GeoJHTnsfzp1JWlzL0+WwUo3XK/X57lpP+QlN/1yT19X/D+vr2qzWNoTGZCJlBlhiWCQ4PLIzqT6c4B/H6Vr+Wn9xfyrSorSsRF3Vx1Zeo3bW8dzdIu54VEUK/3pGwB+pUfnV+QRxRM7Ku1QSePSsloRNqGnWrKMoGvJhjv0Uf99MT/wABrNLmmk9lqU3ywbW70LIsPsWkwQxEtJBh93d25LH/AIFz+dRD7MuqQwfZ49lzC0sb56kEZGPoQfzrSeNMp8q/e9KwdSjW3Mcyp82nuZOAf9Xlcj0+4x/Kk4qVT3lv+ZUW4wdun5GvaIkrfalQLI2UJ55AbHf6U9gRqEWccxv/ADWmadGn2NflH33/AIT/AHj6809lVdQhwAP3b9B7rWk1aTSIGlm/tUgJkeSMHP8AtVS8TRtNoFyxjyYgJQBz9056D2BFX/8AmJn/AK4/1qPWEEmkXKlN4KEFdu7P4ZGahq+hdN2mmWUlMiK6KCrDIOeopdz/ANz9ap6QxW1e3YndbSNFz6Dlf/HSKv0J3VyWrOxka6WuIrax2/8AH3MqsM/wL8zfoMfjWpuf+5+tZqf6X4lkfqllCEH++/J/IAfnWrQu4MZuf+5+tc7cH7J4+tJSnF3ayQ57Blww56dM10tct4picXsN5EmZLJDcKdmfusmRnPGRnjFVG103/WjGr2djptz/ANz9aNz/ANz9aIpFmiSSM5R1DKfUGknlWCCSVuiKWNJ6bkrXYxrcte+KbibblLOIRLz0Zuv6D9a2tz/3P1rL8MxMNK+0yZ8y7kac59D939AK16LWVn/Xf8RJ31/ry/AicNIjIycMMHmuf8Hu0MN9aFSXiuC5yCOGAPf3DD8K6WuW00fYPEAbZsS6Jjb5duW2hlPU9ww/GnHd+a/yf+Zb+D5r9UdJGz7T8nc9/eo7qaSO2dlXDEbV57ngfqamj+6fqf51leIpnFosERxLKdq/7zHaPyLZ/wCA1Mk2rLqJO2r6C+H1P2BrgJ/x8yGRcn+D7qf+OqK1Nz/3P1pIYUt4I4YxhI1CqPQAYFSVTab0JirLUw/E1mb6wSMrgsxQHrglTtPHo22ruj3Ru9Gs50QAPCpxnGDjkfgaNYh+0WYjAyS3B25wdpwfzqn4ZkCW8tqBtVNs0a4xhJBnGPZt4/CiPwyXz/R/oXPaL+X6r9TYLPj7n61jazPKLTy4hiQxiOP5v45DsU/hljW2elYaYvdYtVHKJuuW+gHlx/rvP4VK1kl8/u/4NiXpFv5ff/wLmvBH9nt44Y48JGoRRnsBgU/c/wDc/Wn0UwOXvVFtq0E5QjydQAbrjbKgH/oePbiul3P/AHP1rC1qx+1yNGFA8+by923owjyjdexHX9K1tNu/t2m29zjDSICw9G7j8DkU1/DS7XX6oqp8fqk/wsyfcw6oPzrDctdahZxleAXvXGf+Ax/z/wDHa175j9mKKcNKRGPx4/lk1Q05RNPf3YHytIIIv9yPjj/gRelH4m+y/MmXwpd3+Rqbn/ufrVPVkeXSrkeXkhCwxycjnp+FX6gvRmxnGM5jbjGc8enepkrxaLpu00/MytPYQ+JL5UX5buCK5T8Mq3/sp/Gtnc/9z9a56YfZNXhucY+yulu5x/yzkLAc+gJT8q6StZPmSl5IztyycSpeFnRIdn+tcKfm7Dk/oP1qrpjNcX9/ebchpBAnP8MfB/8AHi1SX92LX7TdEZFrCSB6ueg/QfnU2l2hsdMt7djl0Qbz6seWP5k1ENpS76fd/wAEc94x7a/f/wAAmdnyvyfxetUbiMPqyrJHlLi2eNh2OCO/0J/KtCTqn+9VO/BW5imA5iQvnHbK55+maipor9jSlrK3dMq+GXddChhYAyW7PA/OPmViP1xn8a0GLHUIcrj92/f3WszRf9F1G5t8bUuQblBtwNwYq/H/AHwfxrUf/kIQ/wDXN/5rW9b42zCG1hhjU6qSRyYR3/2qj1eJTpNyNu7KHggNn8CcVJuI1UjYxHkjnjn5qj1hs6TcgocbD12n/wBCOPzrM1h8SI2RbXXFJGI7xNvX/lovT81z/wB81dmMVvA80p2pGpZjnoBUV/bG9tjGAySKQ8bjHyMOQetU5or7Ulit7u2EMAIacq4bzcfwr7E9c9uKjVaINHqSaJbFdP8APmUia6czuCem7oPwGB+FaHlL6frRuP8Acb9P8aXcf7jfp/jV7aEieUvp+tZc9tHLr8avHlWtpFJ2g8ErxnOfwxitXcf7jfp/jWZIf+KkgOw5+zydkz1T33flx601q/v/ACKjoQ+Gzts5dPmyZrGQwnJ6p1Q/lx+FHiM77aHT4SRNeyCPg9F6sfwFSXlncxatHqVhGGdl8q4iZgvmL2IP94UljZ3UuqSalqEWyTb5dvCGDeUnck/3j7dKnff+v+HJtZaf1/wxpx28cUaxouFUBVAPQCneUvp+tLuP9xv0/wAaNx/uN+n+NMBPLX0/WubuLIvpUssCBZoZw6fKF5AUjofUD8M10u4/3G/T/Gs3SlD2twjRkq0mCPkGflX+6aNdbf1qi1blaf8AWjLVjLDeWUVxFnZKN456Z7VmIi6h4iGBmK1G88/xHKr/AOzn8qjhh1XTo7mC0txcQyOWiYyhTGSfm69u/wBSetaOlWR0+1KuC80jb5XGMFumBz0AAA9hQrN8y/r/AIb/AIYzd7cr/r/h/wDhy75S+n60eUvp+tLuP9xv0/xo3H+436f40DKmoRKY4/lz8/oD/CfU1kxIthfWMu3bGyLA/bCvyh444cEf8DrW1BiYo8ofv99v90+pqvNZC+0iGPyznyQuMqMggcZHAPAII6ECmtFfz/AqSvFL+ty5d4jt22D943ypz/EeBVDQYElimvQDtnYLFz/yyQbV/M7m/wCBVXkg1i9jjtbmIRgLse5V15HQsF7MRx6DJOTxW1bgRW8cccRVEQKqjGAAOBSWl33/AC/4P6EN3su35/8AA/Uf5S+n60eUvp+tLuP9xv0/xo3H+436f40DMm+tvMYiNPnF2rKcDqEBHf2xnrSaSY47y6tRnY5F1Bz/AAv94fg2f++hU0x/0kfIf+Pteyf88/r/APX/AAqK+srpZ457GMGWJy8YZgBhvvof9k9fYgU72tfZ/wCehU1fbdW/LUdqtwLdZJI13PCmI1z96V/lQfr+tWbWwSx0yG2HPloFLZ+8e5/E5NUrW0u7m7jnvoDFHCxkWPerF5SMbjg4AA4A/GtWVj5Z+Rv0pJWjZ7vUhvmldbLQd5S+n61BexKbGcbc/u2469vQ8VY3H+436f41BesTYz5Rv9W39309zj86T2Lh8SM69so7jULmBxtjurZYi2OjAuVOc59fyq1plyt1piTTjbKgKzDP3XXhv1BpZI/PvZ12sreVGQw25BDOQeufz4/WqEttfxXUskVoXguCGuIVkUZccblyehAAIPp9aqTavH0t9wrJ2l94s0f2q4s7Qg5mkN3OM9EUjaD+Owfga2vLX0/WqOnW00TzXV4ubq4I3BSCI1H3UB74yee5Jq/uP9xv0/xosopRXQlNybk+ox41yvH8XrULwo18gK5BicH8179amdjlPkb73tUTMf7QjOw/6pv7vqvvmpZcNzDVFtdMtbsKQdPuHSXjH7osQx49irfhW6VVdQh29437+61StoWNruSHzEk3pLGdoDLub0OM8n659ah0q3urXUI4rpGKRwMkMhcE7MrhSP7w7nvgVUm7uL3Tf3Eta83R/mackMxuxLE8ajZtIZSe+fUVHd2t1d2kkBnhTeuN3k5x+BOKKKQ07O6Jdt1/z1g/79n/AOKo23X/AD1g/wC/Z/8AiqKKBBtuv+esH/fs/wDxVG26/wCesH/fs/8AxVFFABtuv+esH/fs/wDxVVjY3bakt2biAbEZAghznODnOcjp0HFFFAXLO26/56wf9+z/APFUbbr/AJ6wf9+z/wDFUUUAG26/56wf9+z/APFUbbr/AJ6wf9+z/wDFUUUAG26/56wf9+z/APFVBaWV1aI6i4hfc27PkbccAdj7UUUBfSxMiXgXDSwZyekZ9f8Aepdt1/z1g/79n/4qiigA23X/AD1g/wC/Z/8AiqNt1/z1g/79n/4qiigCK4trqdVBnhXac/6knsR3b3p0MN1DBHH50J2KFz5RGcD/AHqKKAuPK3eP9bB/37P/AMVSIl4I1DSwZAGcRn/4qiigBdt1/wA9YP8Av2f/AIqjbdf89YP+/Z/+KoooAgeyunkD/aIR+9EuPI9F246/r1qfbdf89YP+/Z/+Kooov0Bu4bbr/nrB/wB+z/8AFU2SO8aMhZbfPvG3/wAVRRQA7bdf89YP+/Z/+Kpk0F1NA8fnQrvUrnyicZ/4FRRQNOzuILe6Fy83nw/MirjyTxgk9d3v+lSbbr/nrB/37P8A8VRRTbuINt1/z1g/79n/AOKo23X/AD1g/wC/Z/8AiqKKQDXjvCVxLb8Nk5jbp/31SGC6M6y+dD8qlceUe5Hfd7UUUDTsJb211bwiMTwtgk58kjqSeze9SJDKbhZZZEO1SoCoR1I9z6UUU27u7Ef/2Q=="/>
					</fig>
				</p>
				<p>El ángulo debido a la diferencia de frecuencia crece con el tiempo, y considerando la naturaleza periódica de ambas formas de onda, esto conlleva a que el ángulo se incremente hasta un valor máximo de 180°, y seguido a ello empiece a crecer desde un ángulo de -180°.</p>
				<p>De la Fig.2 se puede verificar que, en una forma de onda a frecuencia distinta a la fundamental, no existe coincidencia entre el cruce por cero de la referencia y el cruce por cero de la forma de onda.</p>
				<p>En la Fig.3 se muestra el efecto sobre el ángulo del sincrofasor resultado de la referenciación de la forma de onda a una sinusoidal pura a frecuencia fundamental, considerando un ángulo de desfase 𝛿 en la forma de onda.</p>
				<p>
					<fig id="f3">
						<label>Figura 3:</label>
						<caption>
							<title>Desfase en Tiempo entre una Forma de Onda a f<sub>1</sub> con δ&gt;0 y la Onda Sinusoidal Pura a f<sub>nom</sub> de Referencia</title>
						</caption>
						<graphic 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"/>
					</fig>
				</p>
				<p>Al no considerar un desfase 𝛿, ver <xref ref-type="fig" rid="f2">Fig. 2</xref>, se puede observar que el desfase en tiempo respecto a la señal de referencia va incrementando con el tiempo. Cuando el desfase 𝛿 se considera, ver <xref ref-type="fig" rid="f3">Fig. 3</xref>, se observa las dos componentes del ángulo de un sincrofasor, el ángulo de desfase 𝛿 es el comprendido entre las líneas cortadas roja y verde, y el ángulo resultante de la diferencia de frecuencias es el comprendido entre las líneas cortadas verde y azul. De este modo, el ángulo del sincrofasor está comprendido entre las líneas cortadas roja y azul.</p>
			</sec>
			<sec>
				<title>Unidad de Medición Fasorial - PMU</title>
				<p>Originalmente, una PMU era un equipo especifico capaz de realizar la estimación de los sincrofasores, haciendo uso de una fuente de sincronismo en tiempo de alta precisión, a partir de señales correspondientes a las mediciones de magnitudes eléctricas. Luego asocia dicha información a una estampa de tiempo, y es capaz de transmitir los datos sincrofasoriales a un PDC, basándose en los lineamientos de los estándares IEEE C37.118.1 y IEEE C37.118.2. [5] [9] Actualmente, los IEDs comerciales de diversas marcas han sido integrados con ambos estándares, de modo que adicional a las funciones de control y protección que estos dispongan, también pueden operar como PMUs. [10]</p>
				<p>Una PMU realiza el proceso de estimación fasorial con el cual obtiene los datos sincrofasoriales de voltajes y corrientes. Adicionalmente, la PMU realiza el cálculo de la frecuencia de la señal de voltaje y de la razón del cambio de dicha frecuencia (ROCOF). El ROCOF corresponde a la derivada en el tiempo de la frecuencia de la forma de onda, como se muestra en (10). [6]En la <xref ref-type="fig" rid="f4">Fig. 4</xref> se presenta un diagrama de bloques en donde se muestra un modelo simplificado de una PMU.</p>
				<p>
					<fig id="f4">
						<label>Figura 4:</label>
						<caption>
							<title>Diagrama de Bloques de una PMU </title>
						</caption>
						<graphic 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"/>
					</fig>
				</p>
				<p>
					<disp-formula id="e10">
						<graphic xlink:href="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAjcAAABYCAYAAAAJFdYIAAAAAXNSR0ICQMB9xQAAAAlwSFlzAAAOxAAADsQBlSsOGwAAABl0RVh0U29mdHdhcmUATWljcm9zb2Z0IE9mZmljZX/tNXEAAAzTSURBVHja7d0LlFVVHcfxmYFheD+EmISQhxDII5LnUCIkISAgDwF5KEiUPSDAgCBFjbRECCEQBbQiKqnMtER8kai1TA0rQAGzjKREJXpYUkpy2//l7+Rus8+daRjgjvOdtT4LZ599zz1z7x3Pb/b5733yFi1alAcAAPBOwYsAoHL8zyovLz/LtiKnMMv2bNvys20HQLgBgIoKM62d5c6tzlVOzUifM50lzgPOFvs+2N7AmetckBaO3Fc1Z6wz3zmF1x4g3ADA8Qo39ZwfORnnLqcg2H6W8ydnhzPB2er09ra31eMWOM2DxxY7gyxA6fvmClA/dN7L6w8QbgDgeAWc7yrczI1sW69tH9X31bxtdZ2HbOQnZb/r9NgxQfvVzianDq8/QLgBgIoIMw2dkc4c52POs85h5xyvj43oDHZeUEBZ5W9Xn4s0otM0aG/ijHYOOEecL+v7Qm/fTzmTeT8Awg0AHGuwsfqZXzr7FW62KLxYiGnj9Wvh3KJtdlnqq84lwb42Oqsjz9HJuVeP3Wd9nHlODa+P1fk8SJExQLgBgGMJNu92dip09FfbR/S9hZHqQf9Lte3HkX01c3bbyE/Kcy3TY9ekbLf6nT12TLw3AOEGAMobbmYocGz02q5Q2/JI/+Xadn1kWyeNyoyIbLOZUffosdNSjmWo85LTlfcGINwAQHmCja0z8x0Fjo97bXeqbULQv7bzhLZNjuyvxHnZGRjZ1kbb/uF0TzmeYarJ6cn7AxBuAKA84cZmNm1TWBmstvbOnxUy2gT9T1f7q06XyP66aORmaGTbKD3PL9JmRKmg+UC4Zg4Awg0AlDXc1HeeUej4kFPLG8nZqQLiPknRrxbcs227nEaR/Vn/3zozI9tmeXU8hboE1SHoM9X5jdXu8P4AhBsAKE+4KfBqaH6tFYkthPxebbY43+xkHRutSGztd/hr2wT7s8X7bolsG6LH2jTwR53bnJZBn5XO98JFAyvg56yhwun8CthXTQqeAcINgLdPjGeEoxXBdrtPU68TefK0ERjnE5qW3V1t/RRyhnn98hVcLKDMy7I/m0213W6/EAkYo3VLhim2rk7kOOyS1ZQK/Nmq6+e60ZkUhhvN7hqZ5TJZf62ybMfcXm11bPFC5xusyQMQboDSTkSn2cnVZsro3z76t1Ypj3u/M1yLyxWX0tcuw3xY/c9xWsX+mtdJ0W4xcH5yuSbSp6nTQ8fbTcW0JTpmCzFFQWiZq5V9e5UyknKRCnrPz7H3p6Vz0Hk9W8Gv6nhsVtQ1/+f+bYXiu+3xFXS8FsYWOw87Hf33UKMvFlB+5zwZBjH1se336f2fqb4DvYDTV5fgZvD7CxBugLSTkZ0s9qqgdKdO8Ht18pkYub9RL51E9+o+SNtUCzIhZf+XaUTB+v1Ai9DZvt8V9LtQ7bvU7znn8fCE7r7aaeG7AzrJ2eWUzZoRZJdz6nt9V2nUo1HkuJpoEb1GXltvPeeYHHlv7BhvSJsCHunfRgsBzi1D4CzWwoEPVOS9pXQMfwxDokLptc5n9T496b9X3oiOfVYmem1b9DnzbzXxJX1WG/M7DBBugLSTXLKs/yc17XiSvv+bfzlHf03v17bRGmmxNVb+qdDSNhg1WZUsPKeiV1tz5WYtGFfH6/tp9duvmT/Wb7z32FrB6M5PtG2pinHrKBBtSkaENPpjf/W3S/m5LcQdioSncbHwdZLem/G6seUsf0XhMryfC20F4yx3BS/QJSq7ceapFXzME/Q+nhG010wKljWy8/NIuLlYs778z9FC7a+F13aewm0PfocBwg0QOxmVaA0UO9F3VlsrhZUjXj1IU927yELFVd7ja2sk5X/WYFE9SUZFsqd57S396cwaLXlNzzXEa3+f8y8dW9fg8c9r30O99lZJfYa+txGdVSmjIWOcNzS1enpwZ+2aOvHOyYH3pqi8Rb6aGZUt3BQep2P+vEb1WmTpszxl5OZ6jfoUe202evh3P4TqkqiN1A3ndxgg3ACxE02y5P+e5GSjYs9k6nETtc1Wm518WnmPP8V5WtvmRwLP4lJOwN9SvweDSw+9VWfyptXreO1Ws/NvndyKFQAuDkZ3Wmmq9bjIc/ZTAW1GIcmef1bQZ6WmTudnOfbmqv3plqK7AlpRFfs82ajMr+xzUY5ws1ZhuLHXNlafA/8z0FlrAlFYDBBugOiJZrVO9JtVzzJAd6a2S1XneSMID6vfbcHjrWj0L9o2UW0DdEJ6PblvUspz2/O9osdeFmy7UO0Hg5Gez6h9r+6ivcZ5LKi1seLlP/gjMt626t5KwFemHNcc1X7Uz3LskxWA7sni66XVvrwDP08367UrT7hZGQk34zSq2M9ra6mQTVExQLgBjjrJ1PDuRP2st7Dc1uCu1O/x1mCZHQkhb+oSUg+1LfD22TTL8w9Uvzf8k5e2LfEWtWvotd+q9oec63TZanXw2LEKNx0jz1lPIwv/XR040me2wlOzLMdeoEtYRVkUpjx2oS6b5aI1xzLapPdnRznDzTKNyDULPl8Hg0uTzVVP9Sl+jwHCDRCeZNqrMDOjS1HnarTFFpZr7fU7U3UxmXCJf61lktG9j+oGbZuzFcKqqDWjUSL/+axI+GfattZrb+TV/UzzglR4TONUmNoh8pwl+hn3+bVA5Qg3tXQ8DVI01L8Fkccu1UhYLrrdQtsxfKZuLMPIzTJ9XuoF7XYz0b8GI3Vzw5WZNSPLbvQ5nd9jgHADhCeZwQoKLyer1rqvR9Q2w+vXTTOijvjrxejywAvhZSX3dZPavhkZNanrfT9V/Z4JTl5DVVdz2Dnba++kGVyHkxqMlBV7bUToRecDkW3T9Zx3Zym4tZGV3bF1WIJgdr8CXMy9WnCuSq2qq9G0Hdmmabuvr6juqXpK2F7otVkt1oqgXxeN5kzi9xgg3ADhSeZKnejv89qSyz4bvLZiXQaw9r6Rvj/1p07nvX0/o7u8tiaawj3Saztb/fYlJ0MFoKTgd7U/8uFNUd8TrrQb/Fynq1j4ksi2ldrHSn3fN7x0psLWO0opKG6iwtaOKSyItT1es5Jy+DN1hQLvaZFtIzTS9mLyHtgInD+Co0X8dmo9HBvh+X64LxVrv5LUhAEg3AD+KMhenWS2J+udePUy9pdxidf/Uk3JfURTqb+tOptNeUffxdrC0KPazwJN592uy0EdvX41FGCs5mad1kh5XAWkNvpT2+t7qgqHM/rrvnOWny25ZcHayLY52sdLWhvna0EBq830eiq57FWJ3s/8HDmOEVpGoGtkm10SHKWC8/5ai+jcvGAl6ry3Vp+eqrWU6kX2M0oBqRO/ywDhBvBPEAO1YqytS7IoudxktS95by3Jf004lVqjHEtVV3GDPwoT2X9TBZub1N8ed0F4GUmFuRaWVqjfEj9Uef3s0tgXveMdVIaT7NN5R98k0o7rcxo1mJkXrF6sqfFPVIZZTro0ZlPZN1pgyJFjaqzX/fLj+BzrdUmwBr/LAOEGqGoBbrFGlhqVsX8PzeIZWokCakYGBIHRVpMecjLW2VFx+nYVCHeuoH3amkg9bS0lXbbMiTAHEG4AnOiTbDUVB68vZb2d6roMYjOFRlein6+niryf92+joJofm56/7SQeW4lG2caWd5XlYH8NVI8zP+2WGgDhBkBVCjmdstVnaE2akmxr8uTQz1KiqepzvQUY71SdUYGm7W9Q+zb163qSjzk/F/YBEG4AILdCTb6mWR9SEfQ8/beFmGvVp1CjG68ms9V0v6Y+vIYA4QYAci3czFRgud1rS+7fNcxra6v7Lh062SM2AAg3AJAWbGwl5OdUX/NBtTXTejKvBdPrB6vfjtg0agCEGwDIhXBzlgLL7mTml3d39MeCO6J/QaM563jtAMINAORquJkSWUl6hdqu89qKtP5LprItQgiAcAOgaoWbaQos92t6+yDdYDKjWhy7DUQ7ra68S+3DdYPJcVXtFhAA4QYAcj/cdHD2K7TYbS0u1yyo5DYSG5LF8rRWT0a31tiq9XsKeB0Bwg0A5FrA6aE7mo/X6I2N0kzWPb+ae/1a6xYS1rcbrx1AuAEAACDcAAAAEG4AAAAINwAAAIQbAABAuAEAACDcAAAAEG4AAAAINwAAAIQbAABAuAEAACDcAAAAEG4AAAAINwAAAIQbAABAuAEAACDcAAAAEG4AAAAINwAAgHDDiwAAAAg3AAAAhBsAAADCDQAAAOEGAAAQbgAAAAg3AAAAhBsAAADCDQAAAOEGAAAQbgAAAAg3AAAAhBsAAADCDQAAAOEGAAAQbgAAAAg3AAAAhBsAAADCDQAAAOEGAAAQbgAAAAg3AAAAhBsAAADCDQAAAOEGAAAQbgAAAAg3AAAAhBsAAADCDQAAAOEGAAAQbgAAAAg3AAAAJ9B/AHLKGRty70xAAAAAAElFTkSuQmCC"/>
					</disp-formula>
				</p>
				<p>El estándar C37.118.2 establece que el paquete de datos generado por una PMU puede incluir señales analógicas y digitales, las cuales serán complementarias a los datos sincrofasoriales. [7] </p>
				<p>Cada paquete de datos de generado es asociado a una estampa de tiempo de alta precisión, la cual se obtiene de la misma fuente de sincronismo que es utilizada para el cálculo de los sincrofasores. [6] La ventaja de tener cada paquete de datos referenciado en tiempo es que hace posible alinear los datos provenientes de PMUs instaladas en diferentes estaciones de medición. [5]</p>
				<p>La fuente de sincronismo en tiempo de alta precisión utilizada en una PMU puede provenir de un reloj GPS, el cual obtiene la señal de sincronismo en tiempo de los satélites que componen el sistema de posicionamiento global (GPS), o pueden integrar el estándar PTP (Precision Time Protocol), el cual maneja sincronismo en tiempo en una infraestructura de red, considerando mantener la precisión del tiempo en todos sus puntos. [9]</p>
				<p>El estándar C37.118.1 define los índices TVE (Total Vector Error), FE (Frequency measurement error), y RFE (ROCOF measurement error) para evaluar la estimación fasorial de una PMU. [6] Estos índices se calculan con las ecuaciones (11), (12) y (13), respectivamente</p>
				<p>
					<disp-formula id="e11">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>El índice TVE se calcula a partir de la parte real e imaginaria del fasor estimado, 𝑋 𝑟 y 𝑋 𝑖 , y de la parte real e imaginaria del fasor real de referencia, 𝑋 𝑟 y 𝑋 𝑖 .</p>
				<p>
					<disp-formula id="e12">
						<graphic xlink:href="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAjcAAABGCAYAAAAwybXjAAAAAXNSR0ICQMB9xQAAAAlwSFlzAAAOxAAADsQBlSsOGwAAABl0RVh0U29mdHdhcmUATWljcm9zb2Z0IE9mZmljZX/tNXEAAAqmSURBVHja7d0JcFXVHcfxkECAxAgpCEKaGBQXcGEZVBjFWFxQNEC1tOBeW5WgskkFlBGhWAZFRRS0FkasFguOre2ArbQuo6JVWy3WWvd9o3VpLdZd/P/1d2eOt/e+QHgXX+I3M58h95777vYu7/zeOefeFM2aNasIAACgpeAkAAAAwg0AAADhBsAX/+mKivY2AzdhuXJTYVq1oGOvNG1a8Hvb1gw1O2S0/o75uB7sp9R04P8jCDdA86hcepvvmOFmlBljjtG8/UyJlutuvq3ljgqW+56p9/IM9/GnZlmO8j3N5eYP5iFzWDN/T4rNWLPC/NVc6SGghV5/ncxf/DrK83pPMheb4/x8xsr2NbUprxtoTjOT/DqKgpFC8ylmkRnGZwcIN0BhVy7+Qf9P85H5myrSX5kPzMrgw72z+ZOWe9UsMdeYZ827HoQy3MfFZmlK2V7mFTnS/Lo5Vz4KNl4pbzTnmyk6161b6PX3DXO/+W4e13m21jnYW76C+buZa81b5tDYazqYW8ydCvZ+3l8wVwcBfzsF+2c8NPH5AcINULiVy/b6EN8Yfnu2n1VmdmzZm7Xc/GDeaPOg6ZbhPvq35SUpZT/RPp3XQt6PWrPBvPZ16AZRuPHQPCpP6/umrufRsfne0jhf4eY9c1CsvNqsMYOCeTPMx/4FILbsQvNnuqlAuAEKt3KpUyuNV6i9YqGnMjb9j4QQVJplsEkLN/ZTZg40j2qffqlv1SXN+L3oYS7S8bxkfmR2Idxs1vqONq+b3YN5rfzaVtdSfwXHobHXlfiYrdi8sfq/MTg237tm/2X68hkCwg1QmJXLWFWmazXtTfeTE5bz7qv31aTfU4N3p3roybFuDz4HmZGqEJJ4Wb8mhBvvJpurffdusWXmzObcfWM/Q4Kwdq+5xPQh3GzW+mao5aYmR5j/v3CTsqyPeXrYtI/N94C03hzBZwgIN0BhVi4/U2X6iJlu7jPL43eY2M+pWu4/GuDrTfhPeMjIse4KVdA3avxOEi87ZXPDjeb7QOZPFQjKMz5P3nK1j9kpw22UalC0n+cfZLidVvFBtnlefw+dq65fQbiZq2u585aEGw8u5kVzSEKZD2B/0xzLZwgIN0DhBRvv2rlblakPnDxHzfANCcsu0HKrdFfVanPDVtrPtHBztvbpuq2wD0NVoc1IKfdgeKv5fQovu9TPeY5tVKtC9RayffKwz61NVXinlVrm7vJgmOG58u60d7yb8CsIN36trPP1NjXcaJD6o2mDhhXefFD96XyOgHADFF642V0tMd76sb/mTQ7H3mhee1VAG6MuK722TyPr93EMNerG2inFzo19w88RbqIBztPzfF6KE+aN1LZGpLSEHOKVnbr5kpyuW+nb5tju4drGU5vS6tHYfmufn4zeT+3nbhrX02tLWn4aaRWaZv7nIWETzmu+w80Stdw0Kdzoer3dTMixjSrdJTiOzxEQboDCCzf1qkxf9gCSY7kdNcbgE/Ot2DfYurQuDvvZVt1ea9RykcTLxm9uuFGl+Hftf/zOl210O+8yHeMQtTgdF4Qub336sVqkDtZ8f2DeuboD6zy/WywamGo/M81/PYxl+H5MCAZHF6cEh+HarwW69d3nDdA+z9WdPDUKMWs1HmmhnlNUo3M5U91s0TnyUHWwuiMbNKbE37d5/h4G2++vYDRH6zgr6g5Ua4cv7xOP6dk17VTWS2XR66ZF4SODcLO4kZabAxRuDk0oK9W5nxM75+1iy9Xq/wwtNyDcAAUYbuZEXU2NLDciCEGdNa9Ct4Bf3Mi3eB/4202VaZqKJoSb/c2H5g0PX7Gy7nrA4CN6/s14hZujVX6ZBopWaczPPQo2t6m7rZu6knzwdJVe81vzgFeAGb4fK3WeZ6eUe6h5XKFysbpOKvXvVfr9Uh1XNC7kRoWLUg0Cf1zH0VO3Rz+hrjD//Sbd+uwB50LtS522PUihYKKC0wYt7+9xP10b07Vv/tyka/Q6f0jk89r3at3JdEc08DujMTf+4MNOKeX76jjqEsrO1TOeSqOWJl079bHl9tC1cTyfIyDcAIUVbAboQ36jvmn3SFmuezAuZ0PQqvFwWjdNBvuaFG4mBHcVVSS8pkwtO79RBVwStHJ4N9wv9BRbP45x6jL6JKjM/WFuv9NrKnWulmR4jF3M0zqmMQnlUaBYpSDyoO4Maqtw5kFmWPSnGtRC4cdzQrCOagWPCzXdQQ+ku17TN+lOI++GPENdS31Udp15ThV+rcbUNKjsaoVI35euCpxnqmyBtlmhP4WwPnwmUQbhZqbCVHVCa4s/KuB6neMbNF0TtC69p3C3XsfwppYdHltXXx1TPZ8lINwAhRVu9tOt0w2qyPqmLLezgkSDQsBkdUf4v99Pa/7fCuFmkSqehTnCmw/MPTU2/0Q9ZXm2xsLsqvlXqfIuUwXtlfU0ldUpKByf4TH20/6+k/RsG3VHfahuoXHheBaNXbpDrx+qed7i8G8PRcFyh2vAeL2mB2t6lFp2PNgsU5nftfWAfi9V8Fqq6WPN294qo2kPx8v1+0htd4Cm/c9h3KzfD9MYr7oMw80YBY/4uLE9dd1O0vmbqOnoGHpqXNR4PZ14isob4s9xUoj0ANSfzxIQbgA0tcL60t+WUivAY0nfqoNlJqo8/gC20zR/L00fqZaZ5eqy6ahxI5/fju1BQ0HuXY3f6ZnRMY7XNlcnDTrWw+m8/MAgqNQqTGyv8U0+JugCla/UoNc9gqAxOwo3Gn8zVa1YvdVd4+s/Wevyloufq8VoBwWGS9TltVZBaG+1ePgDB69Ud94f1co1SMHYQ9G12sfVWu+Q6JZ6hZu8/W0pHZfv2w8zvB7nqcVwG/5/gnADoKmVyUVRC40GC0ddUiuKUv5itsakeKvBdrH5Vapkb1flPVXh5gR1ZyxUy8Q6dWn1VZfVKwoMA/N8bN7Ns6vGvniAOiBluU7a/t3qIjpH3UzeTXWLxhGtCVoixqolakUUABVcXlbY6K3QeJ+67EYrlHiLXhut6yEFPN/20qIv/uTAJJ0zDy0XKPxdoXEuUxQEn9F75mXzdS6nK8A9q3O8i/apowLRyDwHxXUaJN01T+ss0bUzQnegMd4GhBsAW1SxVEYDRP0uF91lNS9Xl5gGz5anlLVWV058XEbnqDLUNrsEZV3C6TweW7mCmAepYZsQhPzOtdpYK1atwkr8rp7PB2zHXt8lOJflwd1O7bSuYk231fkoCSr3blFrhdYd/d5GFX9FUFYRbNOnOwRl4R1YrTSvLM/n9USd16PytL4yhcNFSXdaAYQbAFtSyXgl3L4FHU9xY3eLAQDhBgAAgHADAAAINwAAAIQbAAAAwg0AAADhBgAAgHADAAAINwAAAIQbAAAAwg0AAADhBgAAgHADAAAINwAAAIQbAAAAwg0AAADhBgAAgHADAAAINwAAAIQbAAAAwg0AAADhBgAAgHADAAAINwAAAIQbAAAAwg0AAADhBgAAgHADAAAINwAAAIQbAAAAwg0AAADhBgAAgHADAAAINwAAAIQbAAAAwg0AAADhBgAAEG4AAAAINwAAAIQbAAAAwg0AAADhBgAAEG4AAAAINwAAAIQbAAAAwg0AAADhBgAAEG4AAAAINwAAAIQbAAAAwg0AAEC6zwDwqZVFFYn4jwAAAABJRU5ErkJggg=="/>
					</disp-formula>
				</p>
				<p>
					<disp-formula id="e13">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>Los índices de FE y RFE se calculan con los valores real y estimado de la frecuencia y el ROCOF.</p>
			</sec>
		</sec>
		<sec>
			<title>MODELO DE PMU IMPLEMENTADO EN HYPERSIM</title>
			<p>HYPERSIM es un software de simulación especializado en sistemas de potencia, específico para simulación de transitorios electromagnéticos (EMT), implementado en un entorno de simulación en tiempo real y distribuido por OPAL-RT. [20]</p>
			<p>Este software tiene disponible en su librería nativa un conjunto de modelos de elementos de sistemas de potencia, elementos de control y protección de sistemas de potencia, y elementos para modelado de sistemas de control, en donde se incluyen funciones de transferencia continuas y discretas. Sin embargo, no existe un elemento que tenga funciones de PMU, o en su defecto que pueda realizar estimación fasorial.</p>
			<p>El entorno de simulación en tiempo real de OPAL-RT tiene integrado el estándar C37.118.2, para intercambio de datos con PDCs y PMUs, e integra sincronización en tiempo de alta precisión por GPS.</p>
			<p>A continuación, se describe las etapas que se han implementado en HYPERSIM con elementos de su librería nativa para obtener el paquete de datos resultante de una PMU, considerando la estimación fasorial, el cálculo de la frecuencia y ROCOF, el proceso de sincronización en tiempo, y la construcción del paquete de datos conforme al estándar C37.118.2.</p>
			<sec>
				<title>Magnitud del Fasor</title>
				<p>El cálculo de la magnitud de los fasores ha considerado la ecuación (5), en su representación discreta, como se muestra en (14). En HYPERSIM se tiene disponible el bloque de valor medio de frecuencia variable, este dispone de dos entradas: la señal de entrada, y la señal de frecuencia; y tiene como salida la señal del valor medio para una ventana móvil en función de la frecuencia.</p>
				<p>
					<disp-formula id="e14">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
				<p>La señal de entrada se obtiene elevando al cuadrado las mediciones de cada fase. La obtención de la señal de frecuencia se explica en la siguiente sección. De la salida del bloque de valor medio de frecuencia variable se calcula la raíz cuadrada. En la <xref ref-type="fig" rid="f5">Fig. 5</xref> se muestra la implementación en HYPERSIM, se debe considerar que este modelo realiza el cálculo de la magnitud de una fase.</p>
				<p>
					<fig id="f5">
						<label>Figura 5:</label>
						<caption>
							<title>Modelo para Cálculo de Magnitud de un Fasor.</title>
						</caption>
						<graphic 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"/>
					</fig>
				</p>
			</sec>
			<sec>
				<title>Frecuencia y ROCOF </title>
				<p>Para el cálculo de la frecuencia de se ha considerado el uso del bloque PLL (Phase-Locked Loop) disponible en HYPERSIM. En [13] y [18] se describe a detalle la estructura interna del esquema de control PLL utilizado para la estimación de la frecuencia de una señal sinusoidal. En la <xref ref-type="fig" rid="f6">Fig. 6</xref> se muestra la estructura interna del PLL disponible en HYPERSIM.</p>
				<p>
					<fig id="f6">
						<label>Figura 6:</label>
						<caption>
							<title>Modelo HYPERSIM de un Control PLL.</title>
						</caption>
						<graphic xlink:href="data:image/jpg;base64,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"/>
					</fig>
				</p>
				<p>El control PLL toma como entrada una señal sinusoidal, y tiene como salidas la frecuencia de la señal de entrada, y la velocidad angular en fase a la señal de entrada. De forma similar a la media, el bloque PLL calcula sus salidas en una ventana móvil. El bloque PLL de HYPERSIM requiere que la señal de entrada tenga un valor pico menor a 1, por lo cual, se ha incluido una etapa de normalización aplicada a las señales de medición. </p>
				<p>La normalización se logra con el uso de Comparadores y Selectores de HYPERSIM. En un selector de dos entradas se conecta la primera entrada a la señal original, y la segunda aplica una ganancia de 0.5 a la señal original; la señal de control del selector viene de un comparador, que detecta si el valor instantáneo de la señal original supera el límite de 1, y entonces cambia la señal del selector a la señal escalada. Este proceso iterativo se aplica en 10 pasos, y este continuamente escala la señal de entrada.</p>
				<p>El PLL se utiliza exclusivamente para el cálculo de frecuencia y ángulo de desfase del sincrofasor, por lo cual la normalización se aplica directamente a la entrada del PLL, y es independiente de la estimación de magnitud.</p>
				<p>La señal de la frecuencia se obtiene del uso de un bloque PLL trifásico de HYPERSIM, el cual toma como entrada las señales normalizadas de voltaje o corriente de cada fase. Esta señal de frecuencia es la que se utiliza para la entrada de frecuencia del bloque de valor medio de frecuencia variable, <xref ref-type="fig" rid="f5">Fig. 5</xref>, de la sección anterior.</p>
				<p>A partir de la salida de frecuencia del PLL trifásico, se calcula el ROCOF haciendo uso de la derivada en tiempo discreto (15), la cual se ha implementado con el bloque de función de transferencia en tiempo discreto de HYPERSIM, en donde se considera la constante Ts correspondiente al paso de integración de la simulación.</p>
				<p>
					<disp-formula id="e15">
						<graphic xlink:href="data:image/png;base64,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"/>
					</disp-formula>
				</p>
			</sec>
			<sec>
				<title>Ángulo de Desfase</title>
				<p>Para el cálculo del ángulo de desfase se utiliza el bloque PLL monofásico de HYPERSIM, el cual toma una señal normalizada para calcular la velocidad angular de cada fase de forma independiente. La salida de velocidad angular del PLL monofásico es una señal diente de sierra, la cual tiene un rango de 0 a 2𝜋, y esta sincronizada a los cruces por cero crecientes de la componente fundamental de la señal de entrada. </p>
				<p>En la <xref ref-type="fig" rid="f7">Fig. 7</xref> se muestra la salida de velocidad angular de un PLL para una entrada de 3 señales sinusoidales.</p>
				<p>
					<fig id="f7">
						<label>Figura 7:</label>
						<caption>
							<title>Señal de Salida de Velocidad Angular de un PLL.</title>
						</caption>
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"/>
					</fig>
				</p>
				<p>La señal de velocidad angular de los PLL de cada fase no es el ángulo de desfase del sincrofasor, ya que solo considera el desfase propio de cada sinusoidal.</p>
				<p>Para obtener el ángulo de desfase de los sincrofasores, se parte de una señal de tiempo UTC, obtenida de la interfaz de sincronización de alta precisión, y se le aplica la función Modulo de HYPERSIM, limitando el rango del tiempo de 0 a 60 segundos, esta se multiplica por un valor de 2𝜋∗ 𝑓 𝑛𝑜𝑚 ∗180/𝜋, se ingresa el resultado a la función Coseno de HYPERSIM, y finalmente se obtiene la velocidad angular de esta sinusoidal con un PLL monofásico. Esta velocidad angular esta en fase a la sinusoidal de referencia a frecuencia fundamental sincronizada en tiempo. En la <xref ref-type="fig" rid="f8">Fig. 8</xref> se presenta el diagrama del modelo implementado en HYPERSIM.</p>
				<p>
					<fig id="f8">
						<label>Figura 8:</label>
						<caption>
							<title>Modelo para Obtención de Referencia Angular UTC.</title>
						</caption>
						<graphic 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"/>
					</fig>
				</p>
				<p> La señal de velocidad angular de referencia debe ser restada de las señales de velocidad angular de cada fase del voltaje y corriente. A esta señal resultante se le aplican las ecuaciones (16), (17), (18) y (19) de modo que su valor esté entre −𝜋 y 𝜋. </p>
				<p>
					<disp-formula id="e16">
						<graphic 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QNAAAAIG4AAAAAEDcAAAAAiBsAAAAAxA0AAAAA4gYAAAAQNwAAAACIGwAAAADEDQAAAADiBgAAAABxAwAAAOsp/wNf0x5cRjQ9aQAAAABJRU5ErkJggg=="/>
					</disp-formula>
				</p>
				<p>
					<disp-formula id="e17">
						<graphic 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					</disp-formula>
				</p>
				<p>
					<disp-formula id="e18">
						<graphic 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"/>
					</disp-formula>
				</p>
				<p>
					<disp-formula id="e19">
						<graphic 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					</disp-formula>
				</p>
				<p>La señal de velocidad angular de referenciada al tiempo UTC, solamente se puede obtener al momento de simular el sistema en tiempo real, debido a que la sincronización en tiempo por GPS solo se activa en este tipo de simulación. </p>
				<p>En caso de que se desee usar el modelo de PMU en simulación fuera de línea, la señal Angle_REF puede ser obtenida de la velocidad angular de la fase A del voltaje de la barra de referencia (Barra del Generador SLACK), y en base a esta señal se calculan los ángulos del resto de PMUs presentes en el modelo de simulación. En este caso se obtienen son los fasores del sistema simulado.</p>
			</sec>
			<sec>
				<title>Modelo de PMU</title>
				<p>En la <xref ref-type="fig" rid="f9">Fig. 9</xref> se muestra el modelo de PMU implementado en HYPERSIM, con todas las consideraciones revisadas en secciones anteriores. </p>
				<p>
					<fig id="f9">
						<label>Figura 9:</label>
						<caption>
							<title>Modelo de PMU Implementado en HYPERSIM.</title>
						</caption>
						<graphic 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"/>
					</fig>
				</p>
				<p>El modelo presentado puede tener como entrada la medición trifásica de voltaje o de corriente, y calculará el paquete de datos sincrofasoriales completo (magnitudes, ángulos, frecuencia y ROCOF) para la magnitud que tenga como entrada.</p>
				<p>De modo que se mejore la eficiencia computacional del modelo de PMU, considerando que en un entorno de simulación en tiempo real los recursos computacionales son clave para asegurar el correcto desempeño de la simulación, el modelo de la <xref ref-type="fig" rid="f8">Fig. 8</xref> es independiente al modelo de la <xref ref-type="fig" rid="f9">Fig. 9</xref>. Con esto se consigue que la señal de referencia angular se calcule una sola vez, y dicha señal sea utilizada por todas las PMUs que se instalen en un mismo sistema a simular.</p>
				<p>Asimismo, otra optimización tiene lugar al considerar que para obtener los sincrofasores de voltaje y corriente, se necesitan 2 subsistemas de la <xref ref-type="fig" rid="f10">Fig. 10</xref>, uno para cada magnitud, respectivamente. Sin embargo, el estándar C37.118.1 define que el valor de la frecuencia y el ROCOF se obtienen de las mediciones de voltaje, por lo cual, en el subsistema que calcule los sincrofasores de corriente se podría eliminar el PLL trifásico y el derivador, ya que dichas señales no serían utilizadas.</p>
				<p>Cada paquete de datos es calculado para todos los pasos de integración que se lleven a cabo, y el modelo de PMU funciona bajo una ventana móvil que avanza Ts en cada paso de integración. </p>
			</sec>
			<sec>
				<title>Interfaz de Entradas y Salidas</title>
				<p>La plataforma de simulación digital en tiempo de OPAL-RT real integrada en el software HYPERSIM hace posible integrar tanto la sincronización con una fuente de tiempo de alta precisión, así como poder realizar el intercambio de datos sincrofasoriales a través del estándar IEEE C37.118.2.</p>
				<sec>
					<title>Sincronización GPS</title>
					<p>En cuanto a sincronización con una fuente de tiempo de alta precisión, el simulador OP5033XG está equipado con una tarjeta Oregano syn1588, la cual permite la sincronización en tiempo a través de una señal IRIG-B obtenida de un reloj GPS, o a través de PTP. [20] En este caso la sincronización se realiza con el uso de una señal IRIG-B obtenida de un reloj GPS SEL-2488.</p>
					<p>HYPERSIM gestiona el proceso de sincronización, y entrega al entorno de simulación 7 señales de la fuente de sincronismo de alta precisión, ver <xref ref-type="table" rid="t1">Tabla 1</xref>.</p>
					<p>
						<table-wrap id="t1">
							<label>Tabla 1:</label>
							<caption>
								<title>Señales Sincronización en Tiempo [20]</title>
							</caption>
							<graphic 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"/>
						</table-wrap>
					</p>
					<p>Las señales utilizadas para generar la señal de tiempo de la sinusoidal de referencia son el tiempo en segundos y nanosegundos. El tiempo en nanosegundos debe ser escalado correctamente, considerando que es entregado a la simulación en un rango de 0 a 10<sup>9</sup>.</p>
				</sec>
				<sec>
					<title>Estándar IEEE C37.118.2</title>
					<p>La implementación del estándar IEEE C37.118.2 en la plataforma de OPAL-RT integrada en el software HYPERSIM permite el intercambio de datos entre PMUs y PDCs, ya que dispone de interfaces de maestro o servidor, y de esclavo o cliente. [20]</p>
					<p>De modo que el modelo de PMU envíe los datos estimados a un PDC, se requiere utilizar la interfaz de esclavo o cliente. Las configuraciones de red necesarias para esta interfaz son la ID de la PMU, el puerto TCP, y la dirección IP. El paquete de datos de la interfaz de cliente IEEE C37.118.2 está compuesto por las señales mostradas en la <xref ref-type="table" rid="t2">Tabla 2</xref>. </p>
					<p>Las señales de la estampa de tiempo y la calidad de tiempo son gestionadas por HYPERSIM al momento de incluir las señales de sincronización en la simulación. </p>
					<p>
						<table-wrap id="t2">
							<label>Tabla 2:</label>
							<caption>
								<title>Paquete de Datos Interfaz Esclavo IEEE C37.118.2 [20]</title>
							</caption>
							<graphic 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d3Ax7rRd57FOTfI6TzizQmptNl9V3veguzruBGcCO4uXZw05lCcDKFX2vv9xReuqn0VVsF1cVreU0OKiJaerMoELO8F3YWBWmdKHnxLgU3CbQsp1NYBi3rFqRzd9K1C9+boVFx56c6V8HGbsCz0ZPfW4TuZWNgZhNOBY7VoWIZRCXfj/xryrGO5OX0YGyBF14FQMDsoBXHmnDvvnHebBcqjGm47xtzrCv5bc/eLJ+06cw9W+FpGEKlUBpYmxvY1wXS1tKuQehYbZ7X4liPY5mkyRjyK4kKdhLfu3oVUF/SNx3PzWHP9odTeVoaxl8B3FQjfnNInywPzkaRFg153oFUrIG37Tqv63EunrdEz37aXyL/EonjKO5Xj/fW4tyGdKkLGMzEm+fPNOrIcw8HSEpxjYUXnpXVh2ccEXd+E8egXBkWF5othZ1PwuvSBLttwG9tsO0pcReYaRl3bgzMfNK0s2evs0nvql76j+W5Mj0vTTj92gXvqAfU0wkvx/PCjcSGc0mHXh70W3z65HN9o0uUK4IbwY3gRiq+cCOV2HwdSKt7ZCGu1QrFUiTsT3AjuBHcSIIbKaL5OigYnCu4kQQ3ghvBjSS4kWLdJgQ3kuBGcCO4kQQ3kuBGkgQ3ghvBjSS4kQQ3kuBGcCO4EdxIghtJcCNFE9wwI7PUFdpre2Z++fvUJTFjLecS19dgdmziVUoLwY3gRhLcSIIbKcbg5jYWWMwq5L1SWVPrX73FJeOp15651LIdrGX1XNxV2l1ecCO4kQQ3kuBGiiG4YX2pL1g8cJp33N/qpEJ4XSYWX0wP1WG2kry/U/z08EKreHOyAKJEIKgZnp+EULlYLnRt1WDBTe9YadZxKiW4EdxIghtJcCMJboJtI9awevJpYCOZ1eGf5rdXWd25AguK3s8qyWfjzu9tNwXPTbu48zug72Bl9Z3AzCC2xVjNCta2wnRrVn9+lFXNM1nVeh/njGH7ioOE+a63UvZswt9EWNcJbgQ3kuBGEtxIMQw3bBFyN6uNP8D2GdUAnK14c/qxMvrfAJvOrDxtHpO3bLsNwrKVrH+PF2YGXpwWrIT9V7ZVeRdgMvu2HeOfZeVuA55/jzu3UfIRtryoTr3Ym1WuBwA+v2J7imAftdc5PugiK08LbgQ3kuBGEtxIMQI37fHWdMPL8t9x53eFX8vea1mE9W/eNhId2MrFdnn/2IOb37GNxA68OBnAku3DdSju3Aam7+PdMU/R3Vx7kH3t6gI9Z0LPmcqWH7Yn2T/hpUkEmP43+211vEg8BTeCG0lwIwlupBiBm0Vs9lobD4uBwm5+C8ChJl6T3+O1WccYnXpsfPoJ548Fbhqx0egf2F+tCp9vY+8429x0MXt4lebaA2yoWgtg+tB7xsp4e571Ntg97v3elk197d61BDeCG0lwIwlupBiFGzYE/Ylt5Mp3m4r9R3Y6r8e4mm/YUDXYuXwhY2P+hSnenwBAFtY9nDMMj9BPAaHbAJKWjNt5GaCaRReWAdAbeI2acQ/bvX4X543Ey/MB9/w93p3uAM8g3pVPNeZGcCMJbiTBjRTbcNOUsTTd+F6PAbo3ABmj+NyEneNn0x2VbXUVg3y7ML6mJbvOzw5mSzFQ+GaDJ3aot26kU07fYYDyTxg/046d3v2d0ocCNmO4rhWANZDuqansoD4dL9CcC3ltBDeCG0lwIwlupBiBmyJ4npYMFB7FbCwbP/Mzg6prcG/BjeBGEtxIghtJcBPx5ynDOBubtr3caYV5hK7RvQU3ghtJcCMJbiTBzVV7rlQGCSdcw3sKbgQ3kuBGEtxIgpuoSgvBjeBGEtxIghtJcCO4EdwIbiTBjSS4kQQ3ghvBjeBGEtxIghtJcCO4EdxIghtJcCNJghvBjeBGEtxIghtJcCO4EdwIbiTBjSS4kQQ3ghvBjeBGEtxIghtJcCO4EdwIbvTiCW4kwY0kuBHcCG4kwY0kuJEkwY3gRnAjCW4kwY0kuBHcCG4EN5LgRhLcSIIbwY3gprCJP81pugwxJl8820hul9JCCtnFXqWDdAX208VpqdIiLy0qlfQytiQn/jinx5zmSTGnFU5nlQ6Sp4VO7/BX6SEVRnudnlE65GmN02HBTdHAzXinh51mSDGnJU5vKB0kT7Od3uKv0kMqjHY6nVI65MkakPcJboquW2qGXIjqlpIkdUtJEbCfrnHqlgrSIsNpt+CmaBI/YgOK3b9Ep2RUzimtBMQ/Je7coK+KBQACU5JT6RL+4hXJgGJL84v8ZraTWMTpYnac7VQ5H1ux39Kc0s0GorAwLlYDii9hK5Yf8cWk/KiQz/EEKyOwlcRos5WLpEmhBhS7f+UtzfI5XqEYvRv1L7eu4BoNKI4SuLHMXxB3rp+xj9N88wyY0Rbj+Jd1OmDPfInz4nEx3uo0x2md0w1O91gl6DTUqYfg5rLu28jpmNMY75gBw91OKy9WoRXwPv2dhhSywtoY9mq5f1lOW8h3K8Dvsr9XoaW3w6mZ4Cbvedo5PeTU0ztm79sh3sPECN1njFO3Qlxn4HJvuDLHxrc7TXIaRp52iHDa1KX8qVmS4QaoyaEuauNUjeMtnGYR3i1ODQrxLDl0DyVFIF7WYD/itFpwE2NwQ3ibnPZRWdWmkqiWz3lJ/Fa7GKTBTU7bLsNjs9upLV15TzrVMsPlBWpYmJcvRuGmotOHjO2owLHOTj9zuj2C97E8aUzhudlAtgDX2kD7I6FjZtMvO42lRW4V4ogIp81Ip187LRTc5D1PHacfOj0eVFCk0T8b3ETwPs3x1lmZtamA19rYta2hYzWw7640oKY79Ypw2tiA1X9xGlXC4cYAcWncuYHs95APVcnz3rx3Nzs9V1AvDiDcMT+PUCHjZmPRNgpuYhNurOW9ISBd77gVGhPjzs3CmEVr5udOj9ISTqdCMSNfSwWYa5UdBr6RlloOFdVCwm2Dp2gwA9kW42XJAELseZaFu5ConK7nnFctTK9Qup4Cq0sIxq7js1Vu9/O5glM9p1VO7b0Kwiq+G/mbQOthrtNwvFkGSUPizs0saMl1CygEZwKInb3WvB1b5DQhUq74IoSbcuTni059vULj6cAWKdyC/FsKXMZjIzPJ69vIi9XYyFZLY88jdzMexKlOv3Q67DSaPFnCeQPwyCUT/gTuawMij+bj0bECt1NgQ/zNxqbXYqMWTiWe1b4vpzurCrZlNtr9AmAxH1s6XBTdXsUQbrLwepwBVBN5n62iG+cBUDj9rUKcwvG92NBk8ro3legErs/keEfy6mdcMzAYGMp5E7xyJ428tPf1dac7Q89t9nvani1oHPG3CbZ+R/AuE8cJlBcLvDjNoBxqlU+6VKAstfdoewmHm1q8q/dT3ncijR4KQcq3DBCdBpEuo2lwjvPK6HGUo1sJ186Zxe/VqGusMTucY63xwvfhmjkcr+KVP0uCIRbY0+0FiJvgJorgxrptDpob2ekJp+ocP4Zh1KVCak6hMJFjrTlel4plGpXgZxhXB6dPeV4z/ncBG6v4v6BSaMtxKyi68JKZe/gVp34hUNlCQZaNi3sjgLXfIIXrnw2ePxRHe+YHAsigYjRPzjK+r6ECtkLrpLm7KQS/QwG9CaBqTCH3ENfdzAvcmDi/wgu6m+sbOD0fqQHgRQg3GVRQluYbKHQW4cZfzjm9yb9c0qEjBdUx0uQY3YnZpOtc8szyvxV5bIB4p8Gj05uATFCRvObd5228OzeTN9lclx/cnORZ53mAZKDenWd8nX55q2jXU8lNprK6h2dsR+VcKxR+KyqsKrwDTQQ3eQ2HpTQI5uONW8A7O9VL/66UC69zzUK6OWvzzqzBDr7P+dbIOIstleL9tXD78W525v0wOz3BfaxMeoHzN/Fc2XRVbA49dxXgfRLgdL3nEWxNw+YlK18AqbmENR6b30c5YN3dJ/IZ09MXeLPy8qn8vOMlCG5K06gcRZwr03jZETrnbd5de8++Jg3sXh+Rt3OAo/qkeX3Of5a8PMQ9gjphEPf6LjDVDe9RMz4PAEZfCbxught5bnbjYbECJYPjBhIfWEHvuSJP+wU4re06GHZA208GfdUUIsHnR4LxFHxuxGerUA57rZscKsKh3n2q4zJuwfdlVEYGNV/xYqwCNNpfCm44toPC1yrA94GkRbyQMyk0A2+Pgd8hPluhfIrP5lHY6aXPy4RxxoPEjXERWjehCOGmMnbSgdbaagoTs5eV3nkVvfzrTkF1BE/YOvI6gcK/OdfYmk2DPFu8jfw2WKjipf8TfG6GjWVTCQ7g+NQgj0JwcwoImhZ4ibw4GZwcp4AeAYwv8jyMX2NXt2JbXUPhL+O3hhTIc4ogb4ob3NQH9K1lfZQ8bR0Afwgm/PRfSgMmkXdxNlB9GuC0eD7jeU3vwVPSHO9cMscnBd2TjOF6kGd6zSs/bsnHc1MFeLkeaJoQ8up0o9yqRrnxkQdAwyiHFgP/Vp7khMLfRJzMfm05h2ElFW58gPE+7/LfPxq6Z4FCg9eHAhuNO7eUyWr+9s8HAo/yTAab6RzfT1kagG1TjlveD/TKn1zKn4GCG8GNgcE673tTz6A60PLdystv3RC5/NYLY2sGfU/j+BNeN8BOD24eprBJosCp7XmOttAvfyuUvieotLxK/T1rAXjXrKa19gKVYcW4C8yIwcMUHo+xg5ZDMC6jN3BVnhdolAc3nTyIsYr2MT6PD/pz3b8ytMhmUnjV9Z71UAmHm0pU8knAygd0O633vF8TiGsO+deDymkPLS5z4dckvU96ldQjXlfXSlSLiqyyV0mF4SaLvB/J8RnhtMFD96hnjwlUnnN5nhzAIHiWHOJ3H4Xr83gSKlJYJ3lhp+K5asW7YaCzqwjypjiOuVlK2r8AnCRQOQUNpSD9G/HsuaT9blrfC3gXs7i+Gul/yqvUdlIWtgWWkzw7uI/PA2jU1KaiDbqhzZY35AM3p7xuqWCW3XLAuSWVbha/t6Ni3Urj6UnsPSiHEr2wM/FK1Scu1k2/pqTDTSgM87yd9L5n432t5+Vz4Dk/BAA/5Xvo+a0fXbx9adAGZcA2wDGVOqa5V690p3Fyi1d/9PW8d2sFNzEGN7zAe3lJG9PaOkVBM5cW6QSouyJGtYgXdCetpzpcs4aX2gaeDqZgeIFWTWlaM1Pos34W4GhAgTYK2r6Zgs6Meqb3nAkUUnt4piO8AJUo/GZQ6VklWCkUxwReCoOjcl68rUC8w2sF3k1F1Z9CdQ6tvRSe9XniNJE4BuN0ThKPQXS7VKOgW8Kz7vO9UCUUbuqR/hU9j0wiBcsuznmUOAf5N4603IyrviUFk8XhEyCxDC3gSYSxj0qwPLYzhYqhOef1Iq+/JJ3v5BkaU8mcCbUmM7hulncsnRbhBCrG96kEp+AJ7Bp0MWHvc7l/f6+gTcA+LJ+DsRnWQv1RUPnGMNy053lS6UoayOeXqHwSeZcmcO4HeEUm4o0dTNonke6fUR4Z8H6O/cXz3q2iEn2N9K9AGfY+ebuad7UiYLKTd/J+lOw9d0O6Swd6x7JoqPQh/z+IOz++JJduV2uotQDGx1CG9PUaiMl4LQ96lbvZ1BcBKEUJ3GTx/k0nLZfw7seTny+SJy3Ii2B85mEa0X0A2Al0VdYhTYPwDpH2BqEfYwfplOuTCXMR93oLII2nXD/q57XgJjbgxgqdebhM59ISn8/x2bSg5gVdUbTG76IwyqVCmULBNJUWUjDALBOPTB8qoq0UEKkUbncSl35ed89dFBjm/RgbetbavCzXE84iCo4cwt5EYZkYui6JONzleVNSaZFN8lyot+LNGck1Iyg8y1FwbuLFGsKzV+Dcs3HnB0LW9lotN1IBDo5g3hcV3DSh4mkQggSrrG7ie5dQ/g2lsH+ZSuVhuqDaA5tW0NXgmv6EMS/u/ADjYfzWju+zyYMeFJyNeYbbua4ncFw11HrcQv4kcCyeSncL95hLZTSGboW5nqcnGAx/Jzad6FVYc7l3ADx9sJ9eMQ43nXhvrgt5Lm4PuqWwjc2k/zzydC7lwk7A5QBhbaLx0Ah7aA8g3RJ3foDxVMJrBHguA2x64kXKwru7mXMHUn6ke8/YjPD97vB4bGcD0LUQO5/G+z3P8yC05/rbgbLA3sryrFbelOHYKGylTbTAjVdOrKTcG+t1Fdrxt0nzWUG8acTcBoD0Ie8GxJ2foFKfNLd3v7fnGdxEV2cWZX9P8mUr5c8syuYErl3q57XgJka6pYrg+TNo8Rb5lPIIxMUq8W3X8H4laldwvDCDvK4tA53GJT3fi1kal/hdwWlMmCelNd9z8fRUVh6XHLi5SPjtaNzEl4C0ENwIbgr9/K3plhpQwguEpLjzU4ArCm7yfd7htJqm0YIaEBdDK78Kbi47Dgl0LSyiG8Ja/t2Vv1EDN6MZX5MruBHcRDPclKV7p9iuglyAAtm8EZWvVcVS0uCGZw5mUFVVRSK4uURcqmArFZW3UQU35cnbMoIbwU3Uwo0UW3AjCW6k2IabEpYWghvBjSS4kQQ3kuBGcCO4EdxIghtJcCMJbgQ3ghvBjSS4kQQ3kuBGcCO4kQQ3kuBGkgQ3ghvBjSS4kQQ3kuBGcCO4EdxIghtJcCMJbgQ3ghvBjSS4kQQ3kuBGcCO4EdzoxRPcSIIbSXAjuBHcSIIbSXAjSYIbwY3gRhLcSIIbSXAjuBHcCG4kwY0kuJEEN4IbwU1hE992WJ4lQ4zJF69sSX/xpKtiF/uVDtIV2E8Pp+VKi7y0qOq0W3BTNIk/0Qozp0FSzGmy0xmlg+RpuNOL/FV6SIXRWqcHlQ55mul0UHBTNHAz1uk5pzVSzGmr07eUDpKn250+5q/SQyqMDGxeVTrkaafTUcFN0XVLTZcLMSZdpja+4h6lhRSyC3VVSldiP52dblZa5KVFJaddgpuiSXwNKI7dF08DiqX8gFcDiqUrsaEiHVDs/iVc5LfSjDVMvkbPogHFghtJcCMJbiTBTV4Yjc3747TUab1BwkXOreZ0yMm+zHCqfpFzzav0gdMWwY3gRhLcSIIbSbomcOP+1Xf6PrDS0ekRp4kXOT/baYjTKqf5lwi7jNN3nJ4V3AhuJMGNJLiRpGsFNzbL6Bs/DOwyG0/OOhsn6pTo1AjPzgCnRU7bnVp7zzEXSFrmVNEpyeltp1OcU5nrbIbXfOuy4vhQp5VOm2zSjeBGcCMJbiTBjSS4uRK4yXB6HcB5BKhJcHoL22zu9AumWddz+qPTh8z8/ZXTCcbVPOw0jjrum8D74/696/QkYT5uXhwg6StmOHV1+gvdYv2cbnWKF9wIbiTBTXGJX4ryWXAjWylZcEMY5mW52+n/0o000unfnJ6h++l3Tsfjzi2S9w9OR7juJROfE+niWu705zgWqwVuHmWszj87nSXMfwSqOjj9HNiZdIXxENwIbiTBTcTiZTMiVpttK58FN5dRid5p3RDK/2LjuanilMrnqXhdjjr9lu6jDnhsMp2ynH5mNsv5rzg9Rb4esYHDBiiA0TTOeRswqu30G6e9Tu2dGhrwcE5NvDt/pmsqXnAjuJEEN0Udr+5x51beLhPhSr90YQs5wU2xjKu17AfHnVuNOSWC4aY6pUW7rVxFuFlKl1JVwOTXTmOcPnN6wymXMTbN6bL6P4BIGud85DQMKLrJaVQwhgfo+QUQVBrQ+cKpVdy5bSMMcvrS5VUJr9FLghvBjSS4KQ7x6uQ0OcJh5lKAdhHcRFV8+xvcXAX7M1tpJLgp1PV9bMCv0wGnhxg3E8/MqWfxuqwBPjpxrnnfWvLbg4DPNr7PwItjcNPb6aTTYcb2NHB6gm4qC6M6z3+awcn3XEk+Cm4EN5LgJpLx2kE/fFaEw7VKf7TgJmrimsyA1Y+DWTIRCjeNyrKz4Cbmy1jBjeBGEtxEJE7ZzG6wSms8xxrj1m7itNDcz975mayRMcFpHi1521C0Gb9bl0UHD5pGetf2pFXZU3BTIuPagoGk1nLvzrF25Ln9tjiYVsxvtZkiPIUpxv0YE1KHdDNbaEp316EAboAos6vxgS0JbgQ3ghvBjSS4KUicJtJ3brCyn2Pmov4x8DKXfnarqFKohK6nwvoBFZa1ujdx7T5zj/PZNsEbwWfry78DN/eJaNmfLcbgZg5dGTbldz3H+uH1Gwf42A7p5YHghxjLcTPjNGzK8MvYVDJ2sIZw7mPgawLrsCylu8U2KR4kuBHcCG4EN5Lg5nLjU5qZD70ZcPgmMy9KM4U0l/Osj74bq5W+zHRR60p4nkrMpo6u49wbne7y4GYIa2jYlNG2HF9KxRYvuCkx8cwEbFuzefAZYLc24zoysJvnqaDqYivpeGqe5nebrjybMPMWi/PgpjXXmR3W4Lh5//YJbgQ3ghvBjSS4udz4tKbyaMDsh9N4cVL5nEOXgXVDdOMaW4X0Fjw+y2iBm0dmFb9bN9Y2Pm9n9dQKrJXRznuHnrrYhn2Cm2IXT+sm2giodAViGjIF+GlWrq3C5wZcsxVvz2xktnSvN8XYwlvK54N4hXKxlVqevR0W3AhuBDdRAjcXa9VSoaRcRhilLqcCYWR9qUvc035PFNxEB9ywrLpVPnO9Y3voVspkddMWeGhep/shlfVwhtJ1leRVQA8BMQeZWZECFE3Avk7TPVGO5eCXR0k6Rj3c4LG7NzR+6knyPYdF3aqzhso7jNXKYI0Vs5vGIRu7G1sxELrd8wJ2w7vzBuNtyjH7ZprgRnAjuCnhcMNgzoFUIFPzW3uEBZlsAGgvvueGp9xSoSywLoKgErpEAX3bxV4wnsemB2ZeIqwcBhYOZ+2DkexF0oE1E/pf6nkEN9ckLnWAj5v4nsoCXsexv+NMG62Hl2U4QHSKJdiPML7CBgnXcnrMaYWtago0NeaceZ6NmodnCV1X6YKbEhPHFoDIZL5XAmL3YRfHWY6/LRDbmXNeZv2VY4ydaYp35iRl001MUW5GGGMIvyNdVmYrN1hjTnAjuBHclGC4YebBcboIGlCJNL7AufcGK8py/pB8zulOZZR6Gfe2xZ8euMjv1anM6l5GOIcpyN4AitYxI6ci3Rklcun2WN9bygCaMTppfN9U0IIo2rx/2lvqguliC8FtDvKbNFoVy7YiuBHcxCTcMEvgcNCS9lrTybSKRgIGVfhtC98TGAzawruuKcc20epOoj98EN6gpt65bfGmGCwdzee5avLyzcPlnOXdY1g+HqO6gFAy925NBZCLJyDwNiUyvmME05GTve6OAcQtnc9TvVVMR3DvcRxP9+7dkGcafDlAJ7gpcPybMUZnADazJBgkHMNpIrjJP1264TXuzftotpKjtBHcCG5iD27K03c9MB+Pya30XdtKkhs5vhUAiKc1fZjjvQGVnpzzDP3YcwGklbiYU2ld7QIyjoY9NwDJfVRm81im2wYO9iKcDlw36ALxOe3DD91Ur/PbYtZSGYzbOpOwXmQK6KvMtunP0t8LeOaTeKOG0U8fDF7twGyOfsR7T6RbfrEON6RBGTw4PSO5kJvgJirTpiLe464l1VsruBHcCG6uPNwMZgn0uoBXJ5H+512e5yboA7eZCPfw+QEDAT73oGurlOcebse6JLWBhOEct+6k+0L3XRcYWty5HWFPM77iIUBrOPuIHLwI3HT2jgXdbgYi32bsxSTWS+kKQAXTiK0/fguf53hrsNzmzcyxvvn3GJxoILSa401YRbWu4EYS3EiCG8GN4Kbo4Ma8Ei/Y7BLvWDwejZvxcMzyKnzrcprEZ/Nq7ODzCW8QZx8GHqcCEdPw7NzHQFG731DOtS6eQ6Fnsqm8u/lcm26met7g0Y50NdXOJz7pwFMn71hn4KYvHpy+eAHaMjPCwtzAudPNY8Xn+R682QDEmXxuyqDFSnhtVnrPagvPNRfcSIIbSXAjuBHcFBHcEPYS4CQdb8QKIOYYlf9yxuXYGJr7DXa47ha6dAyG7sSrUhaPzrMMOD7jrVHxCtBkhfI2uhrWMXsm0XueqQwKrkgf+odM99zIcyXSbZadT1xqOL1vMOUd681z5DB7ogfPnMPzbmTqZzzdVpv5bOlwhDDWMx05jW62IzzHMtKuNFBn3qVyghtJcCMJbgQ3gpuihZtUPBO3UYkfo8/6MBX6IsbINAZmbua6VYy7seur8tsdDLo9CNxsCtaM8FYDrYNnZwXxujdYGdR7HhsUuJuBvAcYa1GesI4BVlXziUt3vCqzvWOjWR+jGpD1IGGOppK4E6BJBXT2AHUbiEcCafMGXix77vqEXY40Ws54oJZXIX+icfuFLGxiKFBoXYBNInyPMqx3U1VwU6LjajM4Z1AZ98dWakf4HlWwlahYKkBwI7gR3Pz/90gJD8CLxGquV2GAbalIxLWA568Put0iEZ7gJm+A+Jt0W9YGiqdehcL7Xw22BTclOq4NGRdo3cn1mTk3MML3sEbLb8OzMAU3ghvBTRTAjXTBtE9jwPSmolgIMErhpgzdee0DAKaLsAzdhmPj2OkZz1k7Zs/15VgSXjhbZqBafkDNwHHrPtwquCnRca3BJIHaXiOsDN3WfbCVRvyWyng8GyvYlWNl8fya16diPuFbl/JSupRvEdwIbgQ3gptYMfzSdKc1K4pVS6MYbp5ian2fYIl9PDkzGMz9CnFfQLdfbwAzGOxus+Ym062ZHgo/h2UImjCN/zrBTYmGm+eBlpHemlVz6EpaxSSCDMbwzaI7+zauXYWNLWKsX1Io/I7YXVdmdJYR3AhuBDeCG0lwU5g4pTG4ey3AEsxQS+ZvbZYTaMB6SzbeqZlXGX3BwHMbt/Mjm+YfCn8+g71rsIbRKMFNiY1rNWY5LmIc3syQrTTHVq5jvJzBbB1+G8HyDyPwznwV/OaFv4ZZkjnYWUfBjeBGcCO4kQQ3hYlTWSqhtnyvwgy1/nhqOjMzrzHHrZX+GhXcQCq73rTI7dzyXtjJ3kKMDRj0vl5wU2LjmkW3VE26IyvR7TgaL19vbCWTbqkV2MdkAPg5JhqYrbQPtvEg7ErYRwds7eGLja0T3AhuBDeCG0lwc7E4lWdWWz/vWEUqos7MqHuJtYjaU2l1xQvThfNyua6ev2oxY3N2x53fPXxIsEK14KZExjWb/GsRqoxeAF7b8blh4HWJO7e79+MAja2Wnsnx+sEWKUDz1GD1dY7NBaRiIV0LDDfAYF3euUbhd4r3dnB+Y5u8c+ozVq78Zd6zBhA75GpN3BDcCG4kwU2k4tQEuLEVoeM9j8s6liCYTuU9im6p9Uy1n8AA49EsJ7CXLodgU81UFoG0RRszODaFxRUHRlH6xRLcdMNrN9E7lsasqT1sr3Ik7vy+divoahqEp2c29nAPW7gE3VkVWL7CwijNMRvL9ZYBk+Am32taOn0v7tx+fxvYrsYmWwR7D45lZlvuRcII3sdsBofbO511iYbQe9y3/FVKC8GN4EYS3EQkTvEXq7gvUJmXCh1Lvtjgz/A9LnZPwU3xt5X88u8CtpKWz6DhUn531GXYYNTYSoThpgpT5t/C82Ves/9kIHYiY+U6eI2N8kzGqMfYqbJ8bgd4Wpfif7B4aiXvGoOo6t59zda/GyyQ6k3yqBF6vsCTlym4EdxIghtJcCPFng0VFm5+YTMZvWOPsp5UbWam/QTw6MlaVsvxvH2bLmfzwv6A2W93O/2N2W4jWVD1GB7cf/C2+jHP3Hfw9LRmxfnV/J3K7MuDeOLW49UtX4B4CW4EN5LgRhLcSIKbvx8zQPkzY2msnvqGtaoMNH7IOfttphqfF3BOc7qd/2LjafitD5BUFw/RQY5bV/VneGxOAzr1GE/1c8bh2TM8jYeocTC2SnAjuJEEN5LgRhLcFBRungJEKuBF+SuwYRDzT2zHY2tWPezBzV9YN2wMn4ONlA1s5jHO7jdx5zcuNlv/FHB5n/E3NiPyEGOvqjL26ndOPy3o+DrBjeBGEtxIghspduGmAnDzAt8NNv7dpuLz3QYL/5dTG7w3ZxjQPT7Yhgd4+SvrCo3Gi9OfRRh/gF1XAVL2cI11S31C95MNRn7de6ZUPDo21qo6M+t+HYzhEdwIbiTBjSS4kQQ3F7vGxsn8yel/MXvxBGsD1WAW4y5g5QY2P/5H7HQva1VVpovqG9YhagCIvMEq0V8wE2s+nhsDmRZOn+OVqcfK5L/n3ru4rhfwM4vVrI+qW0pwIwluJMGNJLi5nGtqMCi4O1untPd+S2CWUyeWerAp9mcBjecBmnHAip3TgOtymcZfA/Xn+oascVWLGVjdvPWKcoOtOLhvaQYwj+C85ALGS3AjuJEEN5LgRopFuClA2NZF9KHT7bbvGwv7fT/YzLQYpoXgRnAjCW4kwY0kuLlk+K2ZBm6Dg290alWM00JwI7iRBDeS4EYS3ERVWghuBDeS4EYS3EiCG8GN4EZwIwluJMGNJLgR3AhuBDeS4EYS3EiCG8GN4EYS3EiCG0kS3AhuBDeS4EYS3EiCG8GN4EZwIwluJMGNJLgR3AhuBDeS4EYS3EiCG8GN4EZwoxdPcCMJbiTBjeBGcCMJbiTBjSQJbgQ3ghtJcCMJbiTBjeBGcCO4kQQ3kuBGEtwIbgQ3ghtJcCMJbiTBjeBGcAPczJchxuSLV8XpgNJC8mwiyemQ/VV6SIW0of5Oq5QWeWlRW3BTdIk/le3jK0gxp4ZOR5UOkqdMpwf4q/SQCqMxThuVDnlq6bRXcFM0cDPa6V1c0VJs6WGnr5QOkqcjTl/zV+khFUYvOn2sdMjTY073C26KrltKY25i02WqMTdS2CY05ka6UhvSmJvzaaExN0UMNwsu8nuCU3mnSnHnxmgkFMM4dHaqV4jrqjp1t7hd5vmWDhOc2kfJi2fxP1AE9y1DWsaHjidhZ4lFnC6JlsdOjULHS+NqtvegmlNGXITGprh/aV7Y1xVh3FOAm5RiYqPppgs8Z8WwDRXB86U6dXGqEzpeFhvPxFYqRsqueX+CLsTMYliuDHBaXYjrajgl5wPbWUWdz9773z2c15e4po7gpmjh5sZLFPTznA7GnRsottppftgIC3lvG/OxwgqIAlzT22luCGweD1dEBfBcvOw04jLOrcaz3uQ0vTi8bKHnm+E0qBDxv7cInjXH6VWnxSFwfMppayRsizCty3UCn8tdLpgDWbc7HQ4dr+50zN4Xp768ExMi9KyZdAUtpnLYHXduPFz8Nc6bYuW5cf86OL3tNN47VsvpNaelkWpsuX8zSfd4s5UCQukBpztDx3OdjlO+DrKuCbOZCD1rfbqU7Z0fZu+w09CS6rmhkdCNstXyoC7HBzstoczfbucU4llaYCeRqK8MKm2w/UZ5bqIAbjhnrtNDFPpWCD/qtCYC9y5HRRdfgGuqBsbPd2s11b+CZ3jQKsHLOM8KqGPFOB/tJapWQuAmHah8z/KTY32cfmAAGcH7ZAEkNbDfmgW41sDivnwq/ueDisT9a2ctuQg9axJwN5oKdpLTOwWpaKMUbrIYv/FM0Ahy/yY7/cRpWoTfn8pOzQGR9AJce4vTlnzeLQP4Nnzv6dQ2Qs+awfvTCc+63f+5ovZ4XgHcmJdrmdNnTvuBVwO4005NeR8mArnXFfBZKtKIjo9Q3AwoNwhuogduLEMPet/HUPAGLkPz5NzqNAd3sVH4DU7rnBbFnZuNdYKKJpfPXSikNuPaHc15R4NWGkZuRr+SAseuX2WEz+89aOmupDKyF304YYymdfM/WnfuX0ee157t+15lZd6DWU4383tZz3tlz/ljvDeTeAnH4zVqaxWnde/ZS21pGnr+VbT47fnvtrTh9/X2u+fFCq6fRItwBwWXHX/SRt5zbifS6i6nTQDfPrwJmbR21uNZqF4M4aYCtnE68JphQxbHRV56LCV+e8ibMsQtSI+95PtR8sJasFuslQZA3UVamv3+EiifTB7v9Gx5P7acTvjmqXwhDLOc84Slf5B+/G1DfmzHTlIo1ObQGt3OtTl4fdZQWMeH4MZa+kOxN7v2gWvdPVQM4aY2afoM71kK78RTnleuDe+ZpfOd5H8mebLQ6VnCmE3Lewywu4K0vg5bGkxZ8jPKm+GEscaz0W3eu7OcY+/l47mpin1n88wZXpm1DJteQb63IL9X4DFMAJwX8n1gKOxKxL8tcV1r9lxcvMmFgJts3um7SdOulMFHQmXG+3h2xpBfMynjVwBAFXjfLIxHeN/sXb+DMJpx7irSthSewQe98mMzNlHfK392BUMXCO92wU30wI0Z0SHvu8GLzbBqRGExlNbxqxQQp5xG8hK2ojvrNfosc3G5l6E18wLX9gVypmKYqRQAEyH7cXh6FlJp53Kfulz/PtBifZzf5XNrp7dCnh47/2kKlDIUfEEFuxVYygDAFnjXTQJkyhKnT4CMHoDaA6SLvRRvUuBuz+f5N3oV6zJeqApUbMH1Z3kx11OIlePF30xLxNKnJQX/KArDI8BaE56vLAAwqRjCTWUKjlsBkAYAhcXvFs7pQFwqkl/d6A68j8piK2liafMB0GJ28AZdlfGAjgVWz+kM4aVhry94oPsK99lM4VeGvDkSeu4UbO424Gwtx7tjd9nMFGlEJbuNazoAa8cZy9OUVmiuF3YC8GX2N8XpI6vgiiBvihvc1Kei20Sl1YoKZr/XiOhO2tch/XPoPt9I+j+Avdn78jnvbHPKhvqk/TE81B2xtyzKIDv2KPcZzW9lKYOmYyt572bouavgXVlAOTDP81BWpXw4Q6PoKFBdBltpgy3Uo1x8PfBwet6IZygrF1EW1y1GdUpB4SaRtB5A938pgGKHd05pGtQTeX8+wxYa8v735N1dSv6Mojywd/0k5f7jlA3WUHqJMt3C/ZCxlDVJ6/bUHbnUBZbnAwQ3sQE3PalEulLJb6PFY0bQj5byRxhaKXQSCBjhwURnKotkKvhWXLsHo7VKp3E+z7Kd537SO/4ErZ8atJgqYMQGL82880YBVIlet9QwKsM3aLEFnqaFIW/Vg3xuTFwr8t1AyaZU30Gh+hTP92w+z78qaOXxvHdx/Xe965+l5WYV3TrOvYFz+/suei/ce4LnBRbaXmpMSBHDzSrS8UEKsla0QFd65+WSDseAm0G0uDOwuRVUXieCPKZSGMTn1YBIFjZRnePWh/8En5sDgfWwi37ee3EwH7g5iY1aGGM8MGnGMz4MRHWk0tnL87bHRtYRz2d9eKEF/ygFbk0qu2NxBRiPFuVw05b0uQt4sTJi+gXSP5f3ZTdpfwQQqMq7mQlInPa8obvI11bYQ2mOG2ge5vMAQKkhlWBgcyvy8dxkYk9D0QAvfVsQ1nHeweFU0HdSMVvD8EvC3YTN1QvBzdOAUjYQt6Okdkt51/mezJ1x3pg3yvK3qF8a8G6k8NtR3qvHg/fXu24Avw8lP8p55eVm4MbyuwnHbep2f6/86cD1gpsohRsrGPaGKujdtIQMQGr7FO51yZiHYZdXkR+mJVPOa50/TMF0Dy99Xz7XwgPSODB8NI1WuxUIr3v3fYSKISjAKgE4Bk853nl9cSMne8Y8kLCf8V8Ov7AAyo7xuRHhBq7KlkHr3zu/Jh6Y8PNbxbaRYwuJSy6tPP/6eAq39R7cbKSVaucmBJUif+8C/CaQP9WBwNHFtFvqVj7vJZ0SKKCWcHwJcBd0GXQHijYCFkPxwqQBNy24zuCnN59vRTWBiQocN0A8yedW5GUmLelxHLcujAOh507CzjqHgGcd71F1KtKgwkwDrp7Co2n2Vcb31oTy2yrOXnxvAvDWvMZ5Uxy7pQKbsHR8zLOboFsqSP8alDE5AMgdNMQGYl9ZhHEdEHHCq9TuppxrG9jGhvNd8kf4PBQYr4bnrZN3/ztCzx14f+uGKuhthNOQCjrL62raif1MCOJ5gYq/HBVyI74PojFZtiTDTSgMK+ef877nAJQ1KC998DmCh+2E34VHnvfBnoPehkx+2867mQIUNfMau92prxaR13u9MmV6Ab1SgpviCjcYyEZcd4OoZI1k6/D7DrpWJqCWEHEwriXwUljB8lOrgL2wxxPuJLq0+lExv01Ftgn4mQrMpNDN8AwV1ikKH6s49lFB2X2/pvAw9+WPAsP0Cp0zFHzdudctHmw8SRfH9DhvBhbP9T4VVk/CDSoxc6keonAah+u0KungP38yHqAgLe/FjZ6Om92/vhIv5YNcZ8D3HK22x2jlTeClTSRNNlJI78FLZl2Ba4oh3DSlkqmB96YrlepTXkVyP+nXA3f0dNLwCAXPKFqttWnl9idvvwxsDDs9SivdWrpr8ATUJw8MYObjUbFC6CZsoz+V0KsBEBFeDYBjSVDZUEk+i5dyAJXMaLwN43nmYzznIWB2LHlXxQvb7OVbHrjfizch+RrnTXGDm55UPuXxfrWicjebuB3bP016DyINB9DC3kseD8fW25HXzagsf0iZk0C+b4g7P4NyMWWW3fNj3st1eKqty2kLnqQe5K89Y5r33C0If5x3rBrv5DTy/1tUvmt55hk0Guvyjq/GhkbFeQPLqdy/h4d5FGXM2rhiskxHhOCmIp6tNdjAWs8z3YQG0XDyfC/v5o3YwlTK2XKk6fs0lo/SYOxJeZtLPfJdGr2Wr59zzb2Upz2xtXk0QO4N57XgpmTDTS8qlzF4MCp5v6fhul2Miz+Rbh4r4Id4XTcJVMQZoQJgAgXKUIyyNddnADMzCLueV9iN5D41qCjsmbK9LpkpFCTZXJ+Tj6t7Pp4jg6Ge3m/DqKh65lPIjseNWZ9w64daZTMBpFyOlcnn+VOAp/G8XMMIs4x3vd8i6881A0n/eO9FnokXJJFCrjOV6BwKzS6BJ6CYwU02AJflHSuNzQznez3yqAcQ2glbsYL8FlpeL5N/k8n3KqR3ay/9Bnjetfle3vSmtdeY8+pgo5Owr0bkTaVQ5XQ9aeu3pFtR+HUi3NY81zjCquu1zm8g7xqG0qQqaTLRe4akIsib4gY3jXlXMkIVn6VRXy9vg/TvQ37MB4QNAA7StdMm7vzYrFpB2UC+2/vTnfC6YhtBmTI8aOxQTmVirzN4L5tS1pUOVWozAu+Od7wr72c73u2mlK9B2Vrd8/zO59ysfLxZU0mXqYGNF6M6JSKL+PE+T6Rc6BRqHL3Eb8MC7ybl4DjK28CT24Z0KktZOZK8buy905Mp0zPJ52aUP/Mof3rEnR/H1598Ki24iYJuKSk6FVfCViim0h3mPfv/NxZBij64KWQcgu7D9nxvhke2vPK45MDNRcLvQhdUsRhjJLgR3EiCmyt93jaM2bqR7oYWykfBTT5xiMdLvABP6Mywp0wq0XAzHBttLLgR3AhupBIPNzxzIl2AxWJ7AMFNsY5LMAszSXkbVXCTRFdisc9XwY3gRhLcSIIbSXATbWkhuBHcSIIbSXAjCW4EN4IbwY0kuJEEN5LgRnAjuBHcSIIbSXAjCW4EN4IbSXAjCW4kSXAjuBHcSIIbSXAjCW4EN4IbwY0kuJEEN5LgRnAjuBHcSIIbSXAjCW4EN4IbwY1ePMGNJLiRBDeCG8GNJLiRBDeSJLgR3AhuJMGNJLiRBDeCG8GN4EYS3EiCG0lwI7gR3AhupILmfVXBjRSyiRTgRhuTSoW1oQGCm7+nRR3BTdHCzTwZYky+eJWd9istJM8mbNf1g/ZX6SEV0ob6Oa1SWuSlRS3BTdEl/mint60FL8WcHnT6XhTG64DTDqe7lccFlnltvuJvLMTXbGW7007lfcT0vNNHSoc8PeJ0v+CmaOBmitOtTlWkmFMTpweiMF6VnEY4TVYeF1g1nB7ibyzEtxJ2MkJ5HzFNcNqsdMhTW6d9gpui65aaLxeiuqWiKF5NnbY6tVM+q1vqEvHt4rTFKUf5r24pdUtFH9xoQHFsvnhROVuK1lKzCIdZz94Tp+wot4mYmS3l/iU4dbW8jXC4zW0co7XcY7Rc0Wyp82mh2VKCG0lwE7F4zXd606lcBMOsxFiCUYKbqIqv/XfKQCeCYWY7vebUUXAjuBHcCG4kwU0k4pTO4ND3nDpzrIxTaadkxpKkhK6p6I2/qMT3ZH4rH1T0DFAe5V1nYdp0+lTBTYmMa3Wnw06vOzXgWFnLT1Q93D3n/mWEbKUCXXkJ2Eoynw8F9ufZpdlKkuBGcCO4EdxIgpuCxqmH0xin1U7rvGNnnW6gMnsA4Il3mmnjA5w2On3GOU84LeLa/U538NmgaSSfWzttclrKrIjGgpsSF9fhToOB1hs4Ns7pDcrFx5l1lwzsLCG/9zh9y2ma05m4czNO05weC8Yvkoad+NzbbMhpOddmCW4EN4IbwY0kuLnc+BisrLMWs1NPp2eolMoBNz2oqF5yak9r+nW6EcwL8yJpcpsHNDcb1HhwM4wwrCtjqOfROSy4KVHxTGXQeQ4zRh/ieD28fg2dqtG9VJPvr2Inds5zALLBylyutfBWeHDTFk+PAVBrjh8PbEtwI7gR3AhuJMHN5cSnNpVKN6dBTm8xc8oqodPW9UCXwZNO3elOuI/KrSctdauM1gSFs3lwnO7i8w5a+hnAUguOz3B6OpLjNgQ3Vz2erZkV1pap4Aa5mXHnVpR9iq7JyuRrAwDZ1izp7zTW6QhdWHvN+0eY5slbxmfrlmqF/ZkdVue4gfNRwY3gRnAjuJEEN5cbnzEMJk6kkjZPyyy+m6elIec9hncniW4pq6zaBAOQ3b87nW7n83qnbXy+h8rNtih410CH4/OozOIFNyUmnnNYjyWRLqX7485tG1AVuAnG1JyigkphttwQbCUYh3XE69Ky7snFnuemGe/YxzaDiuO3GwQJbgQ3ghvBzeXEoSqtq0bmQs7nd2u5N7Y1B/L5LZVrc+280G/ZHE/lezyDDBvgzm6MizpZcFPkccmiO2EN35Noab/HmIfPnXrh3fk+rfUUb1zFWrw0GVRy3wKMbMzNSfL5Xa/bYS4V2GSubx0l6Rj1cMPilZ97UFIWz80pxuF8h3e7ndOP8PJVoZtzC569OZQdM7GxSdjSvZRD3zbbIPzVgHFgK/WiNW0FN4IbwU1k49DR6QVWGbVC50RQgNigPutWcOpAIXN7MFsG1/TdLOS10tzUHE9jAOB4ujfuD9ZNsXEWTAnuazNn6OIokQuARRnclKMyaujBTWO6BmzMRAvApTxdEdU5bt0KU8nXU0GrmtZ5W1rvOfy1lnhd756NsKuoGSAaI3CTwZirOl4Dpxnr09TCVsrRLdUWsLHf9zlNpJx52WkB3ZyduDaDsTkZhFHTu2cz7lk1Bip0wY3gRnAToTg0ZJBo0K/9HDNgSgEfQfeBTdt8n9kNiXRPjOY3K8j6hlrliXy3fvKn+dw5GEzoVYIlssCK1nVuChD/fmw1kI4Xx2wmpjeRjbV1bgpYTu7DTtLx4IxR2ghuBDeCm6sNN88aoPD9QQCmDdM6K3rnHqJgasZAv6qhsBLpc5/pHbOW2acAUHs8Q0m06DNKcLrFOtyksELtTDx+HWNhHRLBTaHSJQ1vrXVVzsYzE6+0EdwIbgQ3V9uA3mYdiu24i1PoNrKVakt75+6nK6I/v5UNhVUaIBrnHTPX9BfMpGjB2IuZeIX6CW4kwY0kCW4EN4KbSMehAeNgGgMvW72X7EMbL+Gde4ixNx2YzlshFFYy61nc4B3rBtCkM67jecZr2EDD+oIbSXAjSYIbwY3gJtJxCNamSKfr6DO6G2zw6DveSqEJ3mDgYGG3nh7U9ODzFn+bejxB9/O5HbMiSuQMKcGNJLiRBDeCG8FNyXmZfmKeFL7fwsDh6sTvSaZq3mRTeb2p3TMAFVvnZLetHsrxbMbVLGM5duvqauNd80ODHMFNsYxTBaZ718OjVz88xf8Kwi7vhV0/khtzCm6KJK4ZvOuBrdSN1D5hzK6rjZ3U9bvGBTeCG8GN4OZy45CFpyaYLZXIrKaKfG/J0vst87m2GavT9vTXn2C10l6EUyVkrH+/l+Cm2MWpJlO655HnNo1/UgTTy6B3Id6/IyzsVuJXJo5RuGnO2jUTGYP3aDBjMgJhNyLsKSz8Z9suTBDcCG4EN4IbSXBTmDiVYap+0MXYIIBaZryUC50fTO0tFTqeHvc/dw9PYTn+/nwfx0D2qGmVxxjcZLGfWC7fWwRrVmFH6aHzUy9gF+lx/3P38KqEHayPtSxYTkJwI7gR3AhuJMFNQeNUlhWF2/A5WMyxLws13sOg8zTGT1lX5WLWMElDM9jGYaff/UjF/wQLO6azUu22aJoSHINwc5q/tlBfDY6Povv6IPtFlcJ+FrAWUjBhoTxrYi1k5eEGIbh5hkUkK2FLKwQ3ghvBjeBGEtwUJk5peG7Wsvp0sB1DK1rj1VgTqQGgs5OB5nVYu+gGpwfollxPN1SC57k5QVeUnfeRhRtl6RdLcBPs+n0TcZ7N8TZ0bTfDU1eDBT+XYSMBMK8FajIBIX8Sgh07Q5fXCjx8tQU3ghvBjeBGEtwUJk7BDuDDGGvVk+PlGFfVl/EPDam8XmQPqmDbBhtY/gprJhkcrQsW9vNWvB7GrtGzGZCeGkXpF0twU4PZk51Qew9MerIlx8MMPO7J+lcHg+02yHuD3Zuxm5tCnptnWfSzEquc3xvuvhLcCG4EN4IbSXBzOXFKpdJpGwKe3QzsrMoK1o09j8wCWvBpeGs2eNcmeJ8TGXTame8dWXagiuCmxNr/Cd+jgn0cYh2shthKtcAW2HPuBLZwwFa29u3D+5xB92g23yeyLEXUgLDgRnAjuJEEN9cuTg3Z9Xuxdywdb451I0xgYcdReGVmM8ZmN5VXM1rcqxiL08ODoGx2k97BMvzWqr9VY25KbFxtJuSPQ6uRV2dTzEV0PX7AHmTbGUC+hHE48XhzrAt0ObbiA3Vb7PA2tvZ40l8YVHAjuBHcCG4kwU1B4mQDQ/vYzJfQcVvLZKTNjAFg6vG5NwCTESqQJrIUQFKoNd6D4zZ1uEMU2kSsdUtZN2Wj0PGmTsODmXasV9OCfO/iz6Jy/5o4TQ4WCvWOV+P8XlT2LWKoXBHcCG4EN5LgRhLcSIIbwY3gRnAjCW4kwY0kuBHcCG4EN5LgRhLcSIIbwY3gRhLcSIIbSRLcCG4EN5LgRhLcSIIbpYXgRnAjCW4kwY0kuBHcCG4EN5LgRhLcSIIbwY3gRnAjCW4kwY0kuBHcCG4kwY0kuJEkwY3gRnAjCW4kwY0kuBHcCG4EN5LgRhLcSIIbwY3gRnAjCW4kwY0kuBHcCG4EN5LgRhLcSIIbwY3gRhLcSIIbSRLcCG4EN5LgRhLcSIIbwY3gpijgZr4MMSZfvCpOB5QWkmcTSU6H7K/SQyqkDfV3Wq20yEuLbMFN0SX+VKelTmWlmFM9pyNKB8lThtP9/FV6SIXRKKc7lA55auq0V3BTNHAz2uk9XNFSbOm401dKB8nTUaev+av0kAqjF50+Vjrk6XFrLAhuiq5baqFTghRzqu50sCju7dlfvHc83jseifvEh8Iv8PP5z3KRdyiSaRN/gbS5VkpzOszfYmGnF0jnEmcrkc7Pq2iDV6rBTmtUvuapfpy6pYoUbhaofzQm+4OrxhXRmBv3r5xTaj7HU+23YpA2lZ26OFXyjqXx3BmkXQWnxKtwbxvoXb6I4p0cd27MTXIxsdEE0jwln99Km+u/GDyjNRI6+c/i/pVxSseOzFbKXwyQC3lfg6VqxSENQs81IE5jboK0qCO4KVq40Wyp2HzximS2FBWWjfV606mZd7y70ztO/SN0n5FOE7xKu0wBrs10esFpvHesRty5MUo3OvWztPN/j8DztnRa5dTNaXtRvJdxxWy2VNy5Ac43kxdZ3vExTm87tY3QfaZbpcznFAPZAlzb0Ol1yzfvWK7Tg5Sv5sk45tQngunSw2k5tnIgknYYgWfTbKnzaaHZUoIbKVbghnv3cfqF02bv2CbGALWJ0D1qOtXm83inOwt4vYHM5FDF/7zTMFrNHZ16RehZzQv0hNMQ4K+z08RYhxueabLTr50WeXBsXWffcsqO0D1scH01Pls3/bICXGvg/KRvC7xbrxl88bx9ndpF0Btw2sLDDg0mhgpuBDeCG8GNVPRwY16a/VQKpXHtb3Z6yqkJYLLEaaPTzqB7yP1rQYvV9IxVeE63GriYl4YBfEPoQtpKC78s9/mae5rHZRPh2cyO3YFr3/1r5XQL3hkDrTGhit8ApBPfq3geF5txuM1pA+clUqHN5Nmme+MRLOzbrXUf8jKdya/7RXCTB5M2wPkBvpt97CAvzG6akv53xZ2bpVOK88yrscxpLbZyA/mz2mkaNtGRrqM9eEOsC+kNp29zzO67lPDmkpcJnvfEwl+BrXT2nrkqAJIN/FTkeFeedRd/k3j+2djdOoClNXay3ryEofQw+DpejMsVwY3gRnAjxSzcWMU/n8qjH0AyDThpZt4bQMbGtzzndRk85jSW8QxWCfWk8vvEui0I4zRwsYUKL4GK5BDh2QzBFwivE10K5UmPk1R4Ns7j6aBbi3Otu+IUXUe32aBJjvdk4KC1/l92as7zvUZllkVlNdJ7BoOzB4IxO+7fYqcTxcAmiiPcWH7NcXoUkJxIPp8gbbuR9qaXsB+Lx7OMm6pNd2cjgMG6Q22Np5V4gBKxwyV83gpoZwASj/IcY7HFeADrFPlejXzv4T1zFY7NA3rncrwfQNaerraaeAhvwma6YCvHiY+9J69YN6kXttn0fsGN4EZwI7iRih/c9KeSGk1Bbq3pBlRYrTinAW79Yx7cHKQFXoWKxgCol9eqb0Olk4RHZyPHDaTu8VrcT/C5OTBUmornpWCgMxXexBDcnOT+du4477dcQOZhKqd4WuEfWEXMOdbt9h6t/Xup1Ep5rfGTgpt8n2kCg1TnAYSLAZjTwTgc96+xl/4tyf9HgeZ6dCdmUd7t5pohnt3sCMpBvGqr+Ww2eoTPAzzQme7ZUNAt1dN75mDM1nCgdpB3blPs/zjvoL0DH3Jfs8MRTl/iybkTyK7vhb05rhgvvim4EdwIbqRYhpvejIMph0t/mVdJNAYgltDK3WstWK4bQTeAAU13r9Lx4eYxPpt3ZD2frWW807v3ST63pMsiGY/Ne8HAYypKv1vKKsxHQt0PKUx7nUblaZ6AFt7vTaiElwFwW7zf/GnO1k131rwFHmQ0FNz83XPTh4rip3yvAgjXBAL89G/OddO8wd/tODYjBDeHPG9I4F0xoFjB56ke3Azx4Ma6O18O8pHu1C7eM2fwfHW9Y+XwJpqnMQdoz/I8Pbt4/gmBDfNbfGjq+0TAKdELt57gRnAjuBHcSEUPNzcylsa6AQYxEymHcTEj6L7ZSGv8XWu1c912uoSuB3BK02XxPp/H0+q9jlkkD1E59KMba4gHMTPw6HzNjJeytPA30j3wpl9IA1pf4DmI51hZPEg3cY9PuMd1dG+0JrybGAD6ApXuBJ4/0QOne6lkOzMOaFusww3gsJ4upHg8Iel0RX0NqD7B2KsBpP9QoPMA3ZGTyc8UxtycIZ7L6K7KAEC3eGXii3QJDcL7NgpP3LfxytTAPpbwDLZo3Qzvuc0j+EPrygrZj3WBTjGvH9f0xp77Yhd78TQ9AcSPQuW8cMrTPbuSeD0UjAsS3AhuBDeCG714RQs3PXHXp3jH6gEqzemSWgQA9KYrySqnu2nh3sqYiruAhklUeu3x+tSgkA1mHyUAPtOoHPoAWE1pSTfkGepz365ARr9Q5TSLLgW/Jd2Oa7pQwbZlQPNYZM+Q7p27nAouPZQm5an0JjDAtJXg5u/wOyCU5s2wlfp43xaSZwNI43QAeRtjpF4FFnri+UnDtqZ6XUO9CDuNbqdxwOsI8r0JoBF4W1px37aE1S0fW+6Sj90vALAHY+t9yXN7hpqcVxsgNviudYF3d5JnKzmCG8GN4EZwIxUx3BTyeZvSog1mNk0MuhWk6ISbK4iHAfGD3nfz4GxWHgtuBDeCG0lwU9yetzSt6bm0fq27oYbyUnCTTzwq4pWZg73YGJnKymPBjeBGcCMJborrc5eN87ZFkAQ3F4lPedmK4EZwI7iRBDeS4CZq4EYS3AhuBDd6MQU3kmxCcCMJbgQ3ghtJcCMJbiRJcCO4EdxIghtJcCMJbgQ3ghvBjSS4kQQ3kuBGcCO4EdxIghtJcCMJbgQ3ghtJcCMJbgQ3kuBGcCO4kQQ3kuBGkgQ3ghvBjSS4kQQ3kuBGcCO4EdxIghtJcCMJbgQ3ghvBjSS4kQQ3kuBGcCO4kQQ3kuBGkgQ3ghvBjVTC8r6q4EYK2UQKcJOi9JAEN1ecFnUEN0ULN3NliDH54lVy2qe0kDybiDfgtb9KD6mQNtTXaaXSIi8tajrtFtwUTeKPdnqHAk2KLT3o9L0ojNdep4ecnlEeF1jmtfmKv7EQ391Ojzk9pbyPmM44faR0yNMjTvcLbooGbqY4rXKqJsWcmgM40RavFk6POi2PYJiZTuX5G802UdvpOH9j4R3oBNjMjGCYVZwq0O0bi+XKZKetKl/z1KGke8dLerfUPLkQY9JlWtlpfxTGq6NT5wiHWdYp2ykpym0iwemg/Y2Rd6C3wXCEwzSwqRWrXXvuXz9rMKuMzUuLWhpzU7RwowHFsfniReVsKfr81zslRzDM+k4vOfWPcpuIqdlS7t94p5sjHGY7p1ciDU0lKE01oPh8Wmi2lOBGEtxEzPNgY25+7NQgwmHvcRotuImauJZxetLpE6eMCIab6HQs0t5DwY3gRnAjuJFiF24amz0zmG82x9o7rXPq5bTNaZZ3flOnG6z1DrxMdFpr3h9+XxQAjfu3w2mkVzFO5V4zogUGYgxubLzNfKcHnIZwrL/TSqc+TrucRnnnW3fnLMYo7sLrYz+0cUrjut4AtqVhJ66rgo0sdJoQ7V1+ghvBjeBGEtxEPk5zqLSG2CyFuHNTm22tia+BkR5O7zo1okI6yRiBrk7fdmoFGG0mvC1OB/i802k4YW4FiOoxIyIqpr7GCtyQh0uxA7OZ7R7A/AjIGeP0BmPTbErv006tOf6hUw72swBvjUHSGsK5D6guhT1NpWvzeafpghvBjeBGcCMJbi43PjaQ8xBjbgxu3qFSMi/L6aCbyv074dQNuHmWMRI2s+EF/t5q3hvPc3OXBzeDmTX1VjCmgsrtqWgYQBpDcGOzwY4CIDMYI1OaQeOnsaVy2Ed97OgMA0RbATrpTveY548wNzkt8+CmFQD0ptkVx+80GxXcCG4EN4IbSXBzufHp4nQHU3CtUHnYaZANLAY+cugyeNw8NVxzIx4YW+9phFdJreTzYvPS8Hm70wAqtfeCMRXu3zTGbghuSk48R7BUgHUZ5eKBsSUEqgM3Gcjspj7XrKYL06Y69+aYwfT1fDYv3xI+30t4BkYfmPeQ46sCT6DgRnAjuBHcSIKbS8WlLN1Di71jR5xOOTV0+pg1JyowgHQ4npvtrPVkYyWyuM7GRrzo1ISuhke57iVvHM8RWuE5jOOZFiXpGPVww1pF5pEZz/cEvDK78eR8ggengdN36IrKxEszzqm7ATTXbsbucvH83Q0UveuB9Skg2Wxln3n/BDeCG8GN4EYS3FxOXGrScp7kVdI34snpztTw5nRHbGPsTRoV0xEqrrN2Pd1OGxls2pdupwa0uscQfgZjNUwjbcyF4KbExDEXCBnM9wp0Rd4C5K5nnFZTbKUFcHOaNYB2Yyt5QGzdloypGcpigDmEEQxKr40Nma0MjIFyRXAjuBHcSIKbIox/P3/8gxXIwcDSGE4T7Qp+4XJym/d9dzC+RhLcCG4EN5LgpjjFvybjLqbyHtjA0tqCG8FNPumSi3fHPHvT6crMVNoIbgQ3ghtJcFNc06FOMGhUaSG4uUjaJDD1v67SQ3AjuBHcSIIbSXAjCW4EN4IbwY0kuJEEN5LgRnAjuBHcSIIbSXAjCW4EN4IbwY3gJsriVJ6BwnUYH2F/S1+F+2QyPbyS4KbExrVSyFZqX414szCg2Up5wY3gRnAjuJEEN4WJU022V5jr1JPdmSdGMPxkVjSeyUactoJta8FNiYxrc9aumcjK08dtw8wIhl+W5QXGsmjkyWClYsGN4EZwI7iRBDcFiVMZNifsyXfbGLGVV3GXyeeaNJTgHSud38J8TAF+0M73CvIGgpsSGdcsVp3O5bvtBdWIz6n5efywk1R/qw1sLj6fc5ezOGQCMsCpLrgR3AhuBDeS4KYwreWTLJmftxEix2012ZVUNnupoFJYt8S8MDv4m8q6NwtYxbaNF7btJP2Ybc8QxTYRa3Bzmr8ZAXgAIStYjfgOdvw2u5rFPmL7Ocf2GJvN5qq2jUe9EBzbdgwjY7BcEdwIbgQ3kuAmwnGylvVzTmuocNZwvA27PNdgH6Fcxly8x/YM6ewndANdWbah4jqnJwKPDjD0sm2cKLiJirjaDvCvASeHvH3D2pPXzbElA5/GbIAZ2E0NNtLcjq3c61dijMmy/aV6CG4EN4IbwY0kuLnSOJWhNT4CoOnjeXS62XfGVjTluO0/9SFdCGl4cF5jXI15eeykJM5NpMtruuAmKuIagG4XbKMTxzMA3qHsLF+NbiWD3ffx4KSwL5l5CZfizVnqhV2R/af6xGC5IrgR3AhuJMFNhONk3UqPh7qTygAqw4jzA4zFSfRa2U+yvL55fG73rk0IhW+bc+73vtvO4bUENyXW/k/4+YctmBemMxtg2viqqh7g1gl2h7dKK/D2BPDr2w0ewDXesZaxsGWD4EZwI7iRBDeRj5NNuf2+dTV4x6w76hl29R7n9LHTIKvUGFfRl+6FyXRFPMsO0Teye7g/0Li+09N0X412etsqQsFNiYxrJ6cfBzu9c8ymbb/CjvAzsZWWeAH3MUPOvDT98fZYt9ViG4fl1DYUfjs8feMZq/OWAZPgRnAjuBHcSIKbgsYpk2m9rfKBntF4WloCKaW8rqp2Xuu8PrOi7HhyPvfIogAfxEDl0lGUfrE2oHhAMFvKO26AOxLPTVvOS2dpAcvvFsHsKM61MrTLRWDbbGUwtpYiuBHcCG4EN5LgRhLcSIIbwY3gRnAjCW4kwY0kuBHcCG4EN4IbSRLcSIIbwY3gRhLcSIIbSRLcCG4EN5LgRhLcSIIbwY3gRnAjCW4kwY0kuBHcCG4EN5LgRhLcSIIbwY3gRhLcSIIbwY0kuBHcCG4kwY0kuJEkwY3gRnAjCW4kwY0kuBHcCG4EN5LgRhLcSIIbwY3gRnAjCW4kwY0kuBHcCG4kwY0kuFF6SIIbwY3gRhLcSIIbSTYkuBHcCG4kwY0kuJEEN4IbwU3EE3+60wwZYsxWZLuVFlLILvYpHaQrsJ8uTkuVFnlpUUlwU3SJP87pBad1Usxpu9OnSgfJkxUKn/FX6SEVRsed3lQ65GmX0wOCm6KBm7JO3Zz6STGnPk6dlA5SSLIJ6UrUA++N0uJcGVtHcCNJkiRJkiS4kSRJkiRJEtxIkiRJkiQJbiRJkiRJEtxIkiRJkiQJbiRJkiRJkgQ3kiRJkiRJghtJkiRJkiTBjSRJkiRJghtJkiRJkiTBjSRJkiRJkuBGkiRJkiRJcCNJkiRJkiS4kSRJkiRJcCNJkiRJkiS4kSRJkiRJEtxIkiRJkiQJbiRJkiRJkgQ3kiRJkiQJbiRJkiRJkgQ3kiRJkiRJghtJkiRJkiTBjSRJkiRJkuBGkiRJkiTBjSRJkiRJkuBGkiRJkiRJcCNJkiRJkiS4kSRJkiRJcCNJkiRJkiS4kSRJkiRJEtxIkiRJkiQJbiRJkiRJkgQ3kiRJkiQJbiRJkiRJkgQ3kiRJkiRJxUj/D2vYzVqFAEfMAAAAAElFTkSuQmCC"/>
						</table-wrap>
					</p>
					<p>Las señales de desviación de frecuencia, ROCOF, y sincrofasores de voltaje y corriente se obtienen del modelo de PMU. Estas señales deben considerar:</p>
					<p>
						<list list-type="bullet">
							<list-item>
								<p> La señal de desviación de frecuencia debe estar en miliHertz [mHz] y se obtiene de la diferencia entre la frecuencia calculada por el modelo de PMU y la frecuencia nominal del sistema.</p>
							</list-item>
							<list-item>
								<p>La señal de ROCOF debe estar en Hertz por segundo [Hz/s].</p>
							</list-item>
							<list-item>
								<p>Las señales de los ángulos de los sincrofasores de voltaje y corriente deben estar en radianes. </p>
							</list-item>
						</list>
					</p>
					<p>Adicionalmente se pueden incluir señales analógicas y digitales al paquete de datos, las cuales estarán asociadas a la estampa de tiempo del paquete de datos. </p>
					<p>En la interfaz de cliente C37.118.2 en HYPERSIM se puede ajustar la taza de datos a enviar al PDC, normalmente este valor se configura a 60 muestras por segundo en un sistema de 60 Hz. Considerando el paso de integración Ts, se determina que no todos los paquetes de datos generados por el modelo se enviarán a un PDC.</p>
				</sec>
			</sec>
		</sec>
		<sec sec-type="results">
			<title>RESULTADOS DEL MODELO DE PMU</title>
			<sec>
				<title>Rendimiento Computacional del Modelo</title>
				<p>El rendimiento computacional del modelo de pruebas se ha obtenido con la utilización del sistema de 9 Barras de los ejemplos de HYPERSIM. En este sistema se ha colocado una PMU en cada unidad de generación, en cada carga, y en un extremo de cada línea de transmisión. En total se ha implementado 12 PMUs en el sistema, de las cuales, las 3 de las unidades de generación reportan a un sistema WAMS de pruebas en tiempo real. </p>
				<p>
					<table-wrap id="t3">
						<label>Tabla 3:</label>
						<caption>
							<title>Resultados Rendimiento Computacional HYPERSIM</title>
						</caption>
						<graphic 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"/>
					</table-wrap>
				</p>
				<p>Se ha configurado el sistema para 6 núcleos del simulador, en el núcleo 3 se ha asignado el sistema de 9 barras y las 12 PMUs, los núcleos restantes manejan otros elementos del modelo, y las comunicaciones. Se ha registrado los datos en el monitor de actividad de HYPERSIM, y se han aplicado eventos a la simulación. Los resultados se presentan en la <xref ref-type="table" rid="t3">Tabla 3</xref>.</p>
				<p>Se puede observar que mientras el núcleo 3 usa un máximo de 55.08% de su capacidad los demás núcleos tienen un uso inferior al 5%. De acuerdo con la documentación de HYPERSIM [20], se recomienda que cada núcleo no supere el 50% de su capacidad para evitar overruns. De acuerdo con estos resultados, es posible configurar el sistema a simular para que nuevas PMUs se asignen a otros núcleos, de modo que se consiga aumentar el total de PMUs y la complejidad del sistema de potencia que se desee simular.</p>
			</sec>
			<sec>
				<title>Índices de Desempeño del Modelo</title>
				<p>Se utiliza el sistema IEEE de 9 barras en ePhasorsim y se aprovecha la integración de dicho paquete con HYPERSIM para calcular los valores de TVE de voltaje y corriente, FE y RFE en estado estacionario y frente a un paso de carga. De ePhasorsim se obtienen los fasores y frecuencia reales, y el ROCOF real se obtiene derivando la frecuencia real, y se comparan contra las estimaciones del modelo de PMU implementado. Los resultados se presentan en la <xref ref-type="table" rid="t4">Tabla 4</xref>.</p>
				<p>
					<table-wrap id="t4">
						<label>Tabla 4:</label>
						<caption>
							<title>Resultados Indicadores Desempeño Estándar C37.118.1</title>
						</caption>
						<graphic 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"/>
					</table-wrap>
				</p>
				<p>En la <xref ref-type="fig" rid="f10">Fig. 10</xref> se muestra evolución en el de los valores de TVE de voltaje y corriente, FE y RFE, para la ventana de tiempo de aplicación del evento paso.</p>
				<p>
					<fig id="f10">
						<label>Figura 10:</label>
						<caption>
							<title>Evolución en el Tiempo de TVE, FE y RFE.</title>
						</caption>
						<graphic 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"/>
					</fig>
				</p>
				<p>Al considerar los límites de TVE, FE y RFE de [6] y [7], se observa que, al comparar la estimación de la PMU frente a los fasores reales, se cumple en estado estacionario los 4 indicadores. En estado dinámico se puede observar que el TVE del fasor de corriente supera ligeramente el límite de 1% en una sola muestra, la cual luego del evento se recupera a valores aceptables.</p>
			</sec>
			<sec>
				<title>Comparación con PMU Comercial</title>
				<p>Se utiliza el mismo sistema de potencia de la sección 4.1, y se instala una PMU para monitoreo del generador 1. Para comparar los resultados del modelo de PMU se ha configurado un entorno de simulación en tiempo real en el que los resultados del modelo de PMU se envían a un WAMS de prueba, y con Sampled Values del estándar 61850 se envía datos a un IED SEL 421 configurado como PMU, el cual se monitorea en el mismo WAMS.</p>
				<p>Se ha realizado la validación del modelo de PMU considerando su desempeño dinámico frente a eventos de un sistema de potencia simulado en tiempo real, y contrastando los resultados de la estimación fasorial contra los datos de una PMU comercial.</p>
			</sec>
			<sec>
				<title>Evento 1: Desconexión y Conexión de Carga</title>
				<p>El primer evento que se ha aplicado en el sistema simulado consiste en la desconexión y posterior conexión de una carga adicional en la barra 8 del sistema IEEE de 9 barras. Los resultados de la simulación en tiempo real del modelo de PMU, y de los datos sincrofasoriales del IED SEL 421, se presentan en la <xref ref-type="fig" rid="f11">Fig. 11</xref>.</p>
				<p>
					<fig id="f11">
						<label>Figura 11:</label>
						<caption>
							<title>Resultados Modelo de PMU y SEL 421 - Evento de Conexión y Desconexión de Carga.</title>
						</caption>
						<graphic 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"/>
					</fig>
				</p>
				<p>De los resultados obtenidos para este tipo de evento se puede observar que en la magnitud de voltaje existe una diferencia de aproximadamente 5 [V] entre los resultados del modelo de PMU y del IED SEL 421, variación mínima considerando que el nivel de voltaje del elemento monitoreado es de 13.8 [kV]. La mayor diferencia se presenta en el ROCOF y la potencia reactiva, principalmente durante los periodos tras la aplicación del evento.</p>
			</sec>
			<sec>
				<title>Evento 2: Cortocircuito Trifásico </title>
				<p>El segundo evento considerado es un cortocircuito aplicado en la barra 8 del sistema IEEE de 9 barras. Se ha considerado un cortocircuito trifásico con una duración de 20 [ms], periodo tras el cual se despeja la falla. Este evento se ha elegido considerando la naturaleza y de mayor afectación sobre las variables eléctricas del sistema, con el fin de determinar el desempeño del modelo de PMU frente a la estimación sincrofasorial de un equipo de protección como es el IED SEL 421. Los resultados de este evento se presentan en la <xref ref-type="fig" rid="f12">Fig. 12</xref>.</p>
				<p>Se observa que la magnitud de corriente, la frecuencia, las potencias activa y reactiva, y principalmente el ROCOF, presentan variaciones entre el modelo de PMU y el IED SEL 421 en el periodo de tiempo que el cortocircuito está presente. Una vez este se despeja, los resultados del modelo de PMU vuelven a estar cercanos a los valores del IED SEL 421. </p>
				<p>En la <xref ref-type="table" rid="t5">Tabla 5</xref> se presenta el error calculado entre las magnitudes y ángulos de voltajes y corrientes, y la frecuencia del modelo de PMU contra el IED comercial para los eventos de paso de carga y cortocircuito, y para estado estacionario. Como referencia se toma los valores del IED SEL 421. </p>
				<p>
					<table-wrap id="t5">
						<label>Tabla 5:</label>
						<caption>
							<title>Resultados Rendimiento Computacional HYPERSIM</title>
						</caption>
						<graphic 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"/>
					</table-wrap>
				</p>
				<p>Se debe considerar que la señal de la frecuencia es relativamente similar entre el modelo de PMU y el IED, pero el ROCOF presenta una variación notable. En este caso es importante tener en cuenta que, como se explica en [10], los IED de protección suelen tener funciones específicas enfocadas a los esquemas de control y protección de este tipo de equipos.</p>
				<p>
					<fig id="f12">
						<label>Figura 12:</label>
						<caption>
							<title>Resultados Modelo de PMU y SEL 421 - Evento de Cortocircuito Trifásico.</title>
						</caption>
						<graphic 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					</fig>
				</p>
			</sec>
		</sec>
		<sec sec-type="conclusions">
			<title>CONCLUSIONES Y RECOMENDACIONES</title>
			<p>Se ha implementado un modelo de unidad de medición fasorial (PMU) con los elementos de la librería nativa de HYPERSIM. La estimación de los sincrofasores de voltaje y corriente se ha conseguido con el cálculo del valor eficaz (RMS) en una ventana de tiempo móvil para la obtención de las magnitudes, y con el uso de controles PLL (Phase-Locked Loop) para la obtención de la frecuencia, ROCOF, y desfase angular de los sincrofasores, considerando los lineamientos de los estándares IEEE C37.118.1 y C37.118.2. </p>
			<p>Se verifica que el modelo de PMU cumple con los requisitos de los estándares IEEE C37.118.1 y IEEE C37.118.1a, en estado estacionario. Para eventos de paso de carga el TVE de voltaje, FE y RFE cumplen con los límites de los estándares, y el TVE de corriente puede presentar incumplimientos por pocas muestras luego de la aplicación de este tipo de evento. </p>
			<p>Se ha considerado que el modelo de PMU implementado pueda ser optimizado en cuanto a recursos computacionales, de modo que este pueda ser utilizado en aplicaciones de simulación digital en tiempo real de sistemas de potencia en donde se requiera un número elevado de PMUs para el monitoreo de elementos de un sistema simulado. </p>
			<p>El modelo de PMU descrito puede ser utilizado para el monitoreo de los sincrofasores de un sistema simulado en tiempo real, así como para el monitoreo de los fasores de un sistema simulado fuera de línea. </p>
			<p>Finalmente, Se recomienda mejorar el algoritmo correspondiente al cálculo del ROCOF, en casos donde se requiera este valor para la implementación de esquemas de control y protección, principalmente considerando la ventana de tiempo sobre la que esta señal se calcula. Alternativas para mejorar el cálculo del ROCOF y que este se asemeje a la estimación de un IED de protección y control, pueden considerar la utilización de otros métodos matemáticos, como DFT ampliada o Taylor-Fourir, o calcular el ROCOF para una ventana de tiempo mayor a la ventana de 16.666 [ms] utilizada.</p>
		</sec>
	</body>
	<back>
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