English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

We address the problem of maintaining high voltage power transmissionnetworks in security at all time. This requires that power flowing through alllines remain below a certain nominal thermal limit above which lines mightmelt, break or cause other damages. Current practices include enforcing thedeterministic "N-1" reliability criterion, namely anticipating exceeding ofthermal limit for any eventual single line disconnection (whatever its causemay be) by running a slow, but accurate, physical grid simulator. Newconceptual frameworks are calling for a probabilistic risk based securitycriterion and are in need of new methods to assess the risk. To tackle thisdifficult assessment, we address in this paper the problem of rapidly rankinghigher order contingencies including all pairs of line disconnections, tobetter prioritize simulations. We present a novel method based on neuralnetworks, which ranks "N-1" and "N-2" contingencies in decreasing order ofpresumed severity. We demonstrate on a classical benchmark problem that theresidual risk of contingencies decreases dramatically compared to consideringsolely all "N-1" cases, at no additional computational cost. We evaluate thatour method scales up to power grids of the size of the French high voltagepower grid (over 1000 power lines).

Anticipating contingengies in power grids using fast neural net screening