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

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Paper number
1779
Working Group Number
Conference name
CIRED 2019
Conference date
3-6 June 2019
Conference location
Madrid, Spain
Peer-reviewed
Yes
Short title
Convener
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).
Table of content
Keywords
Publisher
AIM
Date
2019-06-03
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