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    Using Big Data analytics to improve flood resilience of the distribution grid

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    CIRED 2019 - 1779.pdf (1.010Mb)
    Paper number
    1779
    Conference name
    CIRED 2019
    Conference date
    3-6 June 2019
    Conference location
    Madrid, Spain
    Peer-reviewed
    Yes
    Metadata
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    Authors
    Folleville, Sébastien, Enedis, France
    Mérigeault, Jérémie, Enedis, France
    Faivre, Odilon, Enedis, France
    Tholon, Alain, Enedis, France
    Broussard, Didier, Enedis, France
    Aubujeault, Olivier, Enedis, France
    Abstract
    In order to limit impacts of flood on electrical networks, Enedis has developed a flood impact visualization tool based on cartographic software and leveraging on Big Data technologies.This tool highlights electrical weakness points and is to be used by network investment planners to improve the grid, for example by selecting the best way to reorganize the network or by upgrading substations at risk (increasing substations elevation, installation of water resistant materials...).With dedicated computing intensive algorithms, Enedis was able to automate and rationalize all the data processing steps using internal data as well as government flood scenarios with two main benefits:faster computation time, homogenize computational assumptions.This tool has been developed for Paris metropolitan area (“Ile de France”), which represents 6 million customers. Scaling up this tool to France will be accelerated thanks to Big Data technology and to homogeneous data sets across the whole network managed by Enedis (95 % of France distribution network).
    Publisher
    AIM
    Date
    2019-06-03
    Published in
    • CIRED 2019 Conference
    Permanent link to this record
    https://cired-repository.org/handle/20.500.12455/570
    http://dx.doi.org/10.34890/797
    ISSN
    2032-9644
    ISBN
    978-2-9602415-0-1

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