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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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Dynamic stability of synthetic power grid models

Research datakeyboard_double_arrow_right Dataset 23 May 2022Publisher:Zenodo
Authors: Nauck, Christian; Lindner, Michael; Hellmann, Frank;

doi: 10.5281/zenodo.8204334 , 10.5281/zenodo.6572972

Dynamic stability of synthetic power grid models

Abstract

This repository contains three datasets of synthetic power grids and their dynamic stability. 1. 10,000 grids of size 20 (ds20) stored in dataset020.zip 2. 10,000 grids of size 100 (ds100) stored in dataset100.zip 3. 1 Texan power grid model with 1,910 nodes (texas) stored intexas.zip There are three tasks SNBS (regression) and the identification of troublemakers using regression and thresholding based on the maximum frequency deviation or classification based on binary targets.

Keywords

Power grids, dynamic stability, dataset for Machine Learning, Graph Neural Networks

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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