# April, Tuesday 3rd

14:30 (room 2014, 'Digiteo Shannon' 660 building) (see location)# Benjamin Donnot

(TAU team)# Title: Fast Power system security analysis with Guided Dropout

# Abstract

We propose a new method to efficiently compute load-flows(the steady-state of the power-grid for given productions, consumptions

and grid topology), substituting conventional simulators based on differ-

ential equation solvers. We use a deep feed-forward neural network trained

with load-flows precomputed by simulation. Our architecture permits to

train a network on so-called ”n-1” problems, in which load flows are eval-

uated for every possible line disconnection, then generalize to ”n-2” prob-

lems without re-training (a clear advantage because of the combinatorial

nature of the problem). To that end, we developed a technique bearing

similarity with ”dropout”, which we named ”guided dropout”.

Contact: guillaume.charpiat at inria.fr

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