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

Nauck, Christian; Lindner, Michael; Schürholt, Konstantin; Hellmann, Frank

doi:10.5281/zenodo.7357903

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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_2

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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: Published Online: 2022-11-24Finally published : 2022-11

Publication Status: Finally published

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Publishing info: Geneva : CERN / Zenodo

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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)

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