FAULT DETECTION IN LOW VOLTAGE NETWORKSWITH SMART METERS AND MACHINE LEARNING TECHNIQUES

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CIRED 2019 - 851.pdf (306.49 KB)
Paper number
851
Working Group Number
Conference name
CIRED 2019
Conference date
3-6 June 2019
Conference location
Madrid, Spain
Peer-reviewed
Yes
Short title
Convener
Authors
VAZQUEZ, TANIA, EDP España, Spain
PEREZ, PABLO , OVIEDO UNIVERSITY, Spain
DIEZ, JORGE, OVIEDO UNIVERSITY, Spain
FERNÁNDEZ, JESÚS, EDP España, Spain
Abstract
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.
Table of content
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Publisher
AIM
Date
2019-06-03
Published in
CIRED 2019 Conference
Permanent link to this record
https://cired-repository.org/handle/20.500.12455/170
http://dx.doi.org/10.34890/333
ISSN
2032-9644
ISBN
978-2-9602415-0-1