Graph neural networks on factor graphs for robust, fast, and scalable linear state estimation with PMUs

Graph neural networks on factor graphs for robust, fast, and scalable linear state estimation with PMUs

As phasor measurement units (PMUs) become more widely used in transmission power systems, a fast state estimation (SE) algorithm that can take advantage of their high sample rates is needed. To accomplish this, we present a method that uses graph neural networks (GNNs) to learn complex bus voltage e...

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Bibliographic Details
Main Authors: Cosovic, M. (Author), Kundacina, O. (Author), Miskovic, D. (Author), Vukobratovic, D. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2023
Subjects:
Complex networks
Electric power transmission
Electric power transmission networks
Factor graphs
Fast state
Graph neural networks
Interactive computer systems
Linear state estimation
Machine learning
Machine-learning
Phasor measurement units
Power
Power system
Power systems
Real - Time system
Real time systems
State estimation
State estimation algorithms
Transmission power systems
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