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

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    CIRED 2019 - 851.pdf (306.4Kb)
    Paper number
    851
    Conference name
    CIRED 2019
    Conference date
    3-6 June 2019
    Conference location
    Madrid, Spain
    Peer-reviewed
    Yes
    Metadata
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    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.
    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

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