FAULT DETECTION IN LOW VOLTAGE NETWORKSWITH SMART METERS AND MACHINE LEARNING TECHNIQUES
Paper number
851Conference name
CIRED 2019Conference date
3-6 June 2019Conference location
Madrid, SpainPeer-reviewed
YesMetadata
Show full item recordAuthors
VAZQUEZ, TANIA, EDP España, SpainPEREZ, 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.Publisher
AIMDate
2019-06-03Published in
Permanent link to this record
https://cired-repository.org/handle/20.500.12455/170http://dx.doi.org/10.34890/333