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

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

Detalles Bibliográficos
Autores: Vázquez, Tania, Pérez Núñez, Pablo, Díez Peláez, Jorge|||0000-0002-1314-2441, Fernández, Jesús
Tipo de recurso: capítulo de libro
Fecha de publicación:2019
País:España
Institución:Universidad de Oviedo (UNIOVI)
Repositorio:RUO. Repositorio Institucional de la Universidad de Oviedo
Idioma:inglés
OAI Identifier:oai:digibuo.uniovi.es:10651/53588
Acceso en línea:http://hdl.handle.net/10651/53588
Access Level:acceso abierto
Palabra clave:Preference Learning
Smart meter
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spelling Fault detection in low voltage networks with smart meters and machine learning techniquesVázquez, TaniaPérez Núñez, PabloDíez Peláez, Jorge|||0000-0002-1314-2441Fernández, JesúsPreference LearningSmart meter25th International Conference on Electricity Distribution (CIRED 2019), junio, Madrid (Spain)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.CIRED20192019-06-04book parthttp://purl.org/coar/resource_type/c_3248VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/bookParthttp://hdl.handle.net/10651/53588reponame:RUO. Repositorio Institucional de la Universidad de Oviedoinstname:Universidad de Oviedo (UNIOVI)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:digibuo.uniovi.es:10651/535882026-06-07T06:38:51Z
dc.title.none.fl_str_mv Fault detection in low voltage networks with smart meters and machine learning techniques
title Fault detection in low voltage networks with smart meters and machine learning techniques
spellingShingle Fault detection in low voltage networks with smart meters and machine learning techniques
Vázquez, Tania
Preference Learning
Smart meter
title_short Fault detection in low voltage networks with smart meters and machine learning techniques
title_full Fault detection in low voltage networks with smart meters and machine learning techniques
title_fullStr Fault detection in low voltage networks with smart meters and machine learning techniques
title_full_unstemmed Fault detection in low voltage networks with smart meters and machine learning techniques
title_sort Fault detection in low voltage networks with smart meters and machine learning techniques
dc.creator.none.fl_str_mv Vázquez, Tania
Pérez Núñez, Pablo
Díez Peláez, Jorge|||0000-0002-1314-2441
Fernández, Jesús
author Vázquez, Tania
author_facet Vázquez, Tania
Pérez Núñez, Pablo
Díez Peláez, Jorge|||0000-0002-1314-2441
Fernández, Jesús
author_role author
author2 Pérez Núñez, Pablo
Díez Peláez, Jorge|||0000-0002-1314-2441
Fernández, Jesús
author2_role author
author
author
dc.subject.none.fl_str_mv Preference Learning
Smart meter
topic Preference Learning
Smart meter
description 25th International Conference on Electricity Distribution (CIRED 2019), junio, Madrid (Spain)
publishDate 2019
dc.date.none.fl_str_mv 2019
2019-06-04
dc.type.none.fl_str_mv book part
http://purl.org/coar/resource_type/c_3248
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
dc.identifier.none.fl_str_mv http://hdl.handle.net/10651/53588
url http://hdl.handle.net/10651/53588
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
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eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv CIRED
publisher.none.fl_str_mv CIRED
dc.source.none.fl_str_mv reponame:RUO. Repositorio Institucional de la Universidad de Oviedo
instname:Universidad de Oviedo (UNIOVI)
instname_str Universidad de Oviedo (UNIOVI)
reponame_str RUO. Repositorio Institucional de la Universidad de Oviedo
collection RUO. Repositorio Institucional de la Universidad de Oviedo
repository.name.fl_str_mv
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