Browsing Institutt for matematikk og statistikk by Author "Hansen, Jonas Berg"

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    • Power Flow Balancing With Decentralized Graph Neural Networks 

      Hansen, Jonas Berg; Anfinsen, Stian Normann; Bianchi, Filippo Maria (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-01)
      We propose an end-to-end framework based on a Graph Neural Network (GNN) to balance the power flows in energy grids. The balancing is framed as a supervised vertex regression task, where the GNN is trained to predict the current and power injections at each grid branch that yield a power flow balance. By representing the power grid as a line graph with branches as vertices, we can train a GNN that ...

    • Power Flow Optimization with Graph Neural Networks 

      Hansen, Jonas Berg (Mastergradsoppgave; Master thesis, 2021-06-01)
      Power flow analysis is an important tool in power engineering for planning and operating power systems. The standard power flow problem consists of a set of non-linear equations, which are traditionally solved using numerical optimization techniques, such as the Newton-Raphson method. However, these methods can become computationally expensive for larger systems, and convergence to the global optimum ...

    • Total Variation Graph Neural Networks 

      Hansen, Jonas Berg; Bianchi, Filippo Maria (Journal article; Tidsskriftartikkel, 2023-07)
      Recently proposed Graph Neural Networks (GNNs) for vertex clustering are trained with an unsupervised minimum cut objective, approximated by a Spectral Clustering (SC) relaxation. However, the SC relaxation is loose and, while it offers a closed-form solution, it also yields overly smooth cluster assignments that poorly separate the vertices. In this paper, we propose a GNN model that computes cluster ...