Blar i SINTEF Open på forfatter "Rosenlund, Gjert Hovland"

Viser treff 1-6 av 6

    • Clustering and Dimensionality-reduction Techniques Applied on Power Quality Measurement Data 

      Rosenlund, Gjert Hovland; Høiem, Kristian Wang; Torsæter, Bendik Nybakk; Andresen, Christian Andre (Chapter; Peer reviewed, 2020)
      The power system is changing rapidly, and new tools for predicting unwanted events are needed to keep a high level of security of supply. Large volumes of data from the Norwegian power grid have been collected over several ...

    • Comparative Study of Event Prediction in Power Grids using Supervised Machine Learning Methods 

      Høiem, Kristian Wang; Santi, Vemund Mehl; Torsæter, Bendik Nybakk; Langseth, Helge; Andresen, Christian Andre; Rosenlund, Gjert Hovland (Chapter; Peer reviewed, 2020)
      There is a growing interest in applying machine learning methods on large amounts of data to solve complex problems, such as prediction of events and disturbances in the power system. This paper is a comparative study of ...

    • 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 ...

    • Exploring household's flexibility of smart shifting atomic loads to improve power grid operation and cost efficiency 

      Fjelldal, Bjørnar; Fodstad, Marte; Rosenlund, Gjert Hovland; Sæle, Hanne; Degefa, Merkebu Zenebe (International Conference on the European Energy Market;2020, Chapter; Peer reviewed, 2020)
      This paper explores the possibilities of shifting certain household consumer-based loads in time, to reduce unnecessary load peaks to the grid which again can cause challenges for Distribution System Operators (DSOs). ...

    • Lessons for Data-Driven Modelling from Harmonics in the Norwegian Grid 

      Hoffmann, Volker; Torsæter, Bendik Nybakk; Rosenlund, Gjert Hovland; Andresen, Christian Andre (Peer reviewed; Journal article, 2022)
      With the advancing integration of fluctuating renewables, a more dynamic demand-side, and a grid running closer to its operational limits, future power system operators require new tools to anticipate unwanted events. ...

    • The value of multiple data sources in machine learning models for power system event prediction 

      Hoffmann, Volker; Klemets, Jonatan Ralf Axel; Torsæter, Bendik Nybakk; Rosenlund, Gjert Hovland; Andresen, Christian Andre (Chapter; Peer reviewed, 2021)
      We describe a method for assessing the value of additional data sources used in the prediction of unwanted events (voltage dips, earth faults) in the power system. Using this method, machine learning models for event ...