RUO Principal

Repositorio Institucional de la Universidad de Oviedo

Ver ítem 
  •   RUO Principal
  • Producción Bibliográfica de UniOvi: RECOPILA
  • Capítulos de libros
  • Ver ítem
  •   RUO Principal
  • Producción Bibliográfica de UniOvi: RECOPILA
  • Capítulos de libros
  • Ver ítem
    • español
    • English
JavaScript is disabled for your browser. Some features of this site may not work without it.

Listar

Todo RUOComunidades y ColeccionesPor fecha de publicaciónAutoresTítulosMateriasxmlui.ArtifactBrowser.Navigation.browse_issnPerfil de autorEsta colecciónPor fecha de publicaciónAutoresTítulosMateriasxmlui.ArtifactBrowser.Navigation.browse_issn

Mi cuenta

AccederRegistro

Estadísticas

Ver Estadísticas de uso

AÑADIDO RECIENTEMENTE

Novedades
Repositorio
Cómo publicar
Recursos
FAQs

Fault detection in low voltage networks with smart meters and machine learning techniques

Autor(es) y otros:
Vázquez, Tania; Pérez Núñez, PabloAutoridad Uniovi; Díez Peláez, JorgeAutoridad Uniovi; Fernández, Jesús
Palabra(s) clave:

Preference Learning

Smart meter

Fecha de publicación:
2019-06-04
Editorial:

CIRED

Versión del editor:
https://www.cired-repository.org/bitstream/handle/20.500.12455/170/CIRED%202019%20-%20851.pdf?sequence=1&isAllowed=y
Resumen:

Smart grid data analytics and artificial intelligence techniques are playing an increasingly critical role, becoming the focal point to understanding low voltage real-time grid performance. This new point of view, (advanced analytics in combination with electrical knowledge expertise), makes flexibility and efficiency in electrical grid management approach real. HDCE (Hidrocantábrico Distribución Eléctrica) is the Electrical Distribution System Operator for EdP (Electricity of Portugal) around Spain who supplies energy to 650.000 customers. Starting from 2012, this company has nowadays replaced 99% of traditional meters by smart meters. Based on the analysis of smart metering voltage alarms, recorded from EdP LV distribution network, an automatic learning system has been implemented that groups and orders these alarms helping the grid distribution operator to drive the network technicians to the right and more urgent places where a grid failure is happening, starts to happen or will happen.

Smart grid data analytics and artificial intelligence techniques are playing an increasingly critical role, becoming the focal point to understanding low voltage real-time grid performance. This new point of view, (advanced analytics in combination with electrical knowledge expertise), makes flexibility and efficiency in electrical grid management approach real. HDCE (Hidrocantábrico Distribución Eléctrica) is the Electrical Distribution System Operator for EdP (Electricity of Portugal) around Spain who supplies energy to 650.000 customers. Starting from 2012, this company has nowadays replaced 99% of traditional meters by smart meters. Based on the analysis of smart metering voltage alarms, recorded from EdP LV distribution network, an automatic learning system has been implemented that groups and orders these alarms helping the grid distribution operator to drive the network technicians to the right and more urgent places where a grid failure is happening, starts to happen or will happen.

Descripción:

25th International Conference on Electricity Distribution (CIRED 2019), junio, Madrid (Spain)

URI:
http://hdl.handle.net/10651/53588
Colecciones
  • Capítulos de libros [6507]
  • Informática [872]
Ficheros en el ítem
Thumbnail
untranslated
Versión editorial (306.4Kb)
Compartir
Exportar a Mendeley
Estadísticas de uso
Estadísticas de uso
Metadatos
Mostrar el registro completo del ítem
Página principal Uniovi

Biblioteca

Contacto

Facebook Universidad de OviedoTwitter Universidad de Oviedo
El contenido del Repositorio, a menos que se indique lo contrario, está protegido con una licencia Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Creative Commons Image