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001029191 0247_ $$2datacite_doi$$a10.34734/FZJ-2024-05021
001029191 0247_ $$2doi$$a10.1109/CoDIT62066.2024.10708077
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001029191 037__ $$aFZJ-2024-05021
001029191 1001_ $$0P:(DE-Juel1)180103$$aAlthaus, Philipp$$b0$$eCorresponding author$$ufzj
001029191 1112_ $$a10th International Conference on Control, Decision and Information Technologies$$cValletta$$d2024-07-01 - 2024-07-04$$gCoDIT 2024$$wMalta
001029191 245__ $$aCloud-based controller architecture for the testing of conventional and model predictive room heating controllers in a real-world environment
001029191 250__ $$a10th ed.
001029191 260__ $$c2024
001029191 300__ $$a1-6
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001029191 520__ $$aThe prevailing problem of climate change urges the shift to climate-neutral energy supply and efficient energy use in all areas of society and industry. The share of energy usage for room heating is relatively high and therefore an important field to improve the efficiency as well as CO2-footprint of the energy supply. Currently, there is still a gap between scientific knowledge about possible energy savings by the application of dedicated control strategies and a wide application in society. Within this work, we contribute to close this gap by showing the design of a cloud-based, configurable room heating control algorithm and investigate the effects on energy demand and occupant comfort in a living-lab field test. Results indicate that the use of forecasted schedules in combination with control algorithms to exploit them can significantly change the thermal demand while maintaining thermal comfort and is well applicable.
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001029191 7001_ $$0P:(DE-Juel1)187426$$aJohnen, Sascha$$b1$$ufzj
001029191 7001_ $$0P:(DE-Juel1)8457$$aXhonneux, André$$b2$$ufzj
001029191 7001_ $$0P:(DE-Juel1)172026$$aMüller, Dirk$$b3$$ufzj
001029191 773__ $$a10.1109/CoDIT62066.2024.10708077
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