PowerFlowNet: Power flow approximation using message passing Graph Neural Networks

Nan Lin; Stavros Orfanoudakis; Nathan Ordonez Cardenas; Juan S. Giraldo; Pedro P. Vergara

doi:10.1016/j.ijepes.2024.110112

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PowerFlowNet: Power flow approximation using message passing Graph Neural Networks

Nan Lin Stavros Orfanoudakis Nathan Ordonez Cardenas Juan S. Giraldo Pedro P. Vergara

Year: 2024 Journal: International Journal of Electrical Power & Energy Systems Vol: 160 Pages: 110112-110112 Publisher: Elsevier BV

DOI: 10.1016/j.ijepes.2024.110112

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Keywords:

Message passing Computer science Power flow Artificial neural network Graph Flow (mathematics) Power (physics) Distributed computing Computer network Theoretical computer science Artificial intelligence Electric power system Mathematics Physics

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Optimal Power Flow Distribution

Physical Sciences → Engineering → Electrical and Electronic Engineering

Power System Optimization and Stability

Physical Sciences → Engineering → Electrical and Electronic Engineering

Power Quality and Harmonics

Physical Sciences → Engineering → Electrical and Electronic Engineering

PowerFlowNet: Power flow approximation using message passing Graph Neural Networks

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