Predicting Dynamic Stability of Power Grids using Graph Neural Networks

Nauck, Christian; Lindner, Michael; Schürholt, Konstantin; Zhang, Haoming; Schultz, Paul; Kurths, Jürgen; Isenhardt, Ingrid; Hellmann, Frank

doi:10.5281/zenodo.5148085

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Predicting Dynamic Stability of Power Grids using Graph Neural Networks

Nauck, C., Lindner, M., Schürholt, K., Zhang, H., Schultz, P., Kurths, J., Isenhardt, I., Hellmann, F. (2021): Predicting Dynamic Stability of Power Grids using Graph Neural Networks.
https://doi.org/10.5281/zenodo.5148085

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_27286 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_27286_3

Genre: Data Publication

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Creators:
Nauck, Christian¹, Author
Lindner, Michael¹, Author
Schürholt, Konstantin², Author
Zhang, Haoming², Author
Schultz, Paul¹, Author
Kurths, Jürgen¹, Author
Isenhardt, Ingrid², Author
Hellmann, Frank¹, Author

Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13
2External Organizations, ou_persistent22

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Dates: Finally published : 2021-08

Publication Status: Finally published

Pages: -

Publishing info: Geneva : CERN / Zenodo

Table of Contents: -

Rev. Type: No review

Identifiers: DOI: 10.5281/zenodo.5148085
BibTex Citekey: nauck_christian_2021_5148085
MDB-ID: No MDB - stored outside PIK (see DOI)
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Energy
Research topic keyword: Nonlinear Dynamics
Model / method: Machine Learning

Degree: -

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