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

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).