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

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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.

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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