IEEE Power & Energy - Spanish - May/June 2018 - 30

Sincrofasores en
la distribución
Por Hamed Mohsenian-Rad,
Emma Stewart y Ed Cortez

E

En la Evolución dE tEcnologías dE dEtEcción avanzada, los sistemas de transmisión han liderado
la distribución. la visibilidad y el diagnóstico de la red de
transmisión se han transformado en la última década, con
la implementación sistemática de las unidades de medición
de fasores (PMu). nuevas fuentes de información similares e incluso más avanzadas están ahora disponibles en la
red de distribución, mediante las PMu de nivel de distribución, también denominadas micro PMU (µPMU). las
µPMu proporcionan mediciones de tensión y corriente con
una resolución y precisión más altas para facilitar un nivel
de visibilidad en la red de distribución que no es factible en
la actualidad. sin embargo, la simple disponibilidad de datos
en sí no conducirá a una mayor conciencia de la situación
ni inteligencia operativa. los datos deben combinarse con
análisis útiles para convertir estos datos en información
procesable. En este artículo, exploramos algunas de las
oportunidades para aprovechar los datos de las µPMu, en
conjunto con análisis basados en datos y así ayudar a los
planificadores y a operadores de sistemas de distribución
eléctrica a superar los problemas a medida que estos surjan.
los datos generados por las µPMu son un ejemplo claro
de "big data" en los sistemas de potencia. cada µPMu
genera 124,416,600 lecturas por día. Por lo tanto, las µPMu
que se instalan en algunos alimentadores de distribución de
Identificador de Objeto Digital 10.1109/MPE.2018.2790818
Fecha de publicación: 18 de abril de 2018

30

ieee power & energy magazine

servicios públicos pueden generar terabytes de datos a diario. como las µPMu transmiten sus mediciones de forma
continua, los datos tienen que recolectarse, limpiarse y procesarse en tiempo real.
los datos recolectados de las μPMu luego tienen que
diseccionarse en análisis descriptivos, predictivos y prescriptivos. Mientras que el análisis descriptivo se enfoca en
lo que sucedió en el pasado, el análisis predictivo apunta a
lo que puede pasar en el futuro. ambos son un trampolín
hacia el análisis preceptivo, optimizando así el futuro con
decisiones informadas. aquí, consideramos los estudios de

1540-7977/18©2018IEEE

mayo/junio 2018



Table of Contents for the Digital Edition of IEEE Power & Energy - Spanish - May/June 2018

Contenidos
IEEE Power & Energy - Spanish - May/June 2018 - Cover1
IEEE Power & Energy - Spanish - May/June 2018 - Cover2
IEEE Power & Energy - Spanish - May/June 2018 - Contenidos
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IEEE Power & Energy - Spanish - May/June 2018 - Cover3
IEEE Power & Energy - Spanish - May/June 2018 - Cover4
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