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  Paper companion: Towards dynamic stability analysis of sustainable power grids using graph neural networks (Neurips Workshop Climate Change AI)

Nauck, C., Lindner, M., Schürholt, K., Hellmann, F.(2022): Paper companion: Towards dynamic stability analysis of sustainable power grids using graph neural networks (Neurips Workshop Climate Change AI), Geneva / CERN : Zenodo.
https://doi.org/10.5281/zenodo.7357903

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_27578 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_27578_1
Genre: Software

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 Creators:
Nauck, Christian1, Author              
Lindner, Michael1, Author              
Schürholt, Konstantin2, Author
Hellmann, Frank1, Author              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2External Organizations, ou_persistent22              

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 Abstract: This repository contains the relevant information to reproduce the results of the paper "Towards dynamical stability analysis of sustainable power grids using Graph Neural Networks" published at Tackling Climate Change with Machine Learning: workshop at NeurIPS 2022.

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Language(s): eng - English
 Dates: 2022-11-242022-11
 Publication Status: Finally published
 Pages: -
 Publishing info: Geneva / CERN : Zenodo
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.5281/zenodo.7357903
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
MDB-ID: No MDB - stored outside PIK (see DOI)
 Degree: -

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