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Daniel Rohde
Researcher at SINTEF
Publications - 18
Citations - 263
Daniel Rohde is an academic researcher from SINTEF. The author has contributed to research in topics: Thermal energy storage & Waste heat. The author has an hindex of 6, co-authored 16 publications receiving 150 citations. Previous affiliations of Daniel Rohde include Norwegian University of Science and Technology.
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Dynamic modeling of local district heating grids with prosumers: A case study for Norway
TL;DR: In this paper, the technical, energetic and environmental impacts of including prosumers in a local low-temperature district heating (DH) grid were investigated. And the results show that utilizing local surplus heat is a significant measure to reduce the heat demand and the environmental impact of the DH grid.
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Analysis of an integrated heating and cooling system for a building complex with focus on long–term thermal storage
TL;DR: In this paper, an integrated heating and cooling system for a building complex in Oslo, Norway was analyzed using simulation models developed in Modelica with focus on the long-term thermal energy storage.
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Dynamic optimization of control setpoints for an integrated heating and cooling system with thermal energy storages
TL;DR: In this paper, the authors analyzed the control of an integrated heating and cooling system for a building complex in Oslo, Norway, focusing on the control setpoints for the main heat pumps, which had a total heating capacity of about 1MW and were connected to thermal storage tanks.
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Dynamic modelling of local low-temperature heating grids: A case study for Norway
TL;DR: In this article, a local LTDH grid for a new development planned in Trondheim, Norway, has been modelled in the dynamic simulation program Dymola in order to study the effect of lowered supply temperatures to heat losses and circulation pump energy use.
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Optimize heat prosumers' economic performance under current heating price models by using water tank thermal energy storage
TL;DR: In this paper, a dynamic optimization problem was formulated to explore prosumers' economic potentials, and the size parameter of WTTESs was swept in prosumers to obtain the optimal storage size considering the trade-off between the payback period and the heating cost saving.