• Corpus ID: 238253140

Leveraging power grid topology in machine learning assisted optimal power flow

@article{Falconer2021LeveragingPG,
  title={Leveraging power grid topology in machine learning assisted optimal power flow},
  author={Thomas Falconer and Letif Mones},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.00306}
}
—Machine learning assisted optimal power flow (OPF) aims to reduce the computational complexity of these non-linear and non-convex constrained optimization problems by consigning expensive (online) optimization to offline training. The majority of work in this area typically employs fully connected neural networks (FCNN). However, recently convolutional (CNN) and graph (GNN) neural networks have also been investigated, in effort to exploit topological information within the power grid. Although… 

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