• Balancing the Norwegian regulated power market anno 2016 to 2022 

      Austnes, Pål Forr; Riemer-Sørensen, Signe; Bordvik, David Andreas; Andresen, Christian Andre (Peer reviewed; Journal article, 2024)
      The balancing market for power is designed to account for the difference between predicted supply/demand of electricity and the realised supply/demand. However, increased electrification of society changes the consumption ...
    • Deep Reinforcement Learning for Long Term Hydropower Production Scheduling 

      Riemer-Sørensen, Signe; Rosenlund, Gjert Hovland (Chapter; Peer reviewed, 2020)
      We explore the use of deep reinforcement learning to provide strategies for long term scheduling of hydropower production. We consider a use-case where the aim is to optimise the yearly revenue given week-by-week inflows ...
    • Graph Convolutional Networks for probabilistic power system operational planning 

      Sheikh-Mohamed, Yasmin Bashir; Jakobsen, Sigurd Hofsmo; Bødal, Espen Flo; Haugseth, Fredrik Marinius; Kiel, Erlend Sandø; Riemer-Sørensen, Signe (Chapter; Peer reviewed, 2023)
      Probabilistic operational planning of power systems usually requires computationally intensive and time consuming simulations. The method presented in this paper provides a time efficient alternative to predict the ...
    • Predictions of prices and volumes in the Nordic balancing markets for electricity 

      Backe, Stian; Riemer-Sørensen, Signe; Bordvik, David Andreas; Tiwari, Shweta; Andresen, Christian Andre (International Conference on the European Energy Market;19, Chapter; Peer reviewed, 2023)
      The electricity market is driven by complicated interactions that are hard to model analytically. This is particularly the case for the balancing market, where imbalances between supply and demand after the day-ahead market ...