• Characterizing the energy flexibility of buildings and districts 

      Junker, Rune Grønborg; Azar, Armin Ghasem; Lopes, Rui; Lindberg, Karen Byskov; Reynders, Glenn; Relan, Rishi; Madsen, Henrik (Journal article; Peer reviewed, 2018)
      The large penetration rate of renewable energy sources leads to challenges in planning and controlling the energy production, transmission, and distribution in power systems. A potential solution is found in a paradigm ...
    • Control of Heat Pumps with CO2 Emission Intensity Forecasts 

      Leerbeck, Kenneth; Bacher, Peder; Junker, Rune Grønborg; Tveit, Anna; Corradi, Olivier; Madsen, Henrik; Ebrahimy, Razgar (Peer reviewed; Journal article, 2020)
      An optimized heat pump control for building heating was developed for minimizing CO 2 emissions from related electrical power generation. The control is using weather and CO 2 emission forecasts as inputs to a Model ...
    • Implementing flexibility into energy planning models : Soft-linking of a high- level energy planning model and a short-term operational model. 

      Dominkovic, Dominik Franjo; Junker, Rune Grønborg; Lindberg, Karen Byskov; Madsen, Henrik (Journal article; Peer reviewed, 2020)
      The operation of electric and heat grids alike is complicated due to the dynamic demand, with the increasing penetration of renewable energy sources adding to the problem. In order to improve the integration of variable ...
    • Short-term forecasting of CO2 emission intensity in power grids by machine learning 

      Leerbeck, Kenneth; Bacher, Peder; Junker, Rune Grønborg; Goranović, Goran; Corradi, Olivier; Ebrahimy, Razgar; Tveit, Anna; Madsen, Henrik Tams (Peer reviewed; Journal article, 2020)
      With the aim of enabling effective flexible electricity demand, a machine learning algorithm is developed to forecast the CO2 emission intensities in European electrical power grids distinguishing between average and ...