• 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, 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 ...
    • Fault Detection and Prediction in Smart Grids 

      Andresen, Christian Andre; Torsæter, Bendik Nybakk; Haugdal, Hallvar; Uhlen, Kjetil (Chapter, 2018)
      Modern society is to a larger and larger extent dependant on electric energy, and hence the reliance on and utilization of the electric grid is increasing steadily. At the same time the production and consumption patterns ...
    • Impact of the Temporal Distribution of Faults on Prediction of Voltage Anomalies in the Power Grid 

      Tyvold, Torfinn Skarvatun; Torsæter, Bendik Nybakk; Andresen, Christian Andre; Hoffmann, Volker (Chapter, 2020)
      Is it possible to reliably predict voltage anomalies in the power grid minutes in advance using machine learning models trained on large quantities of historical data collected by power quality analysers (PQA)? Very little ...
    • Topology of fracture networks 

      Andresen, Christian Andre; Hansen, Alex; Le Goc, Romain; Davy, Philippe; Hope, Sigmund Mongstad (Journal article; Peer reviewed, 2013)
      We propose a mapping from fracture systems consisting of intersecting fracture sheets in three dimensions to an abstract network consisting of nodes and links. This makes it possible to analyze fracture systems with the ...