Non-linear Model Predictive Control for Smart Heating of Buildings

Christian Ankerstjerne Thilker*, Hjörleifur G Bergsteinsson, Peder Bacher, Henrik Madsen, Davide Cali, Rune Grønborg Junker

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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Smart and flexible operation of components in district heating systems can play a crucial role in integrating larger shares of renewable energy sources in energy systems. Buildings are one of the crucial components that will enable flexibility in the district heating by using intelligent operation. Recent work suggests that such improved operation at the same time can increase thermal comfort and lower economic costs. We have digitalised the heating system in a Danish school by adding IoT devices, such as smart thermostats and temperature sensors to demonstrate the possibilities of making buildings smart. Based on experimental data, this paper introduces a non-linear grey-box model of the thermal dynamics of the building. A non-linear model predictive control method is presented for the thermostatic set-point control of the building's radiators. Based on the building model and the control algorithm, simulation studies are carried out to show the flexibility potential of the building. When used for lowering the return temperature the results suggest that operational costs can be lowered by around 10% using predictive control.
Original languageEnglish
Title of host publicationProceedings of Cold Climate HVAC & Energy 2021
Number of pages8
Publication date2021
Article number09005
Publication statusPublished - 2021
EventCold Climate HVAC & Energy 2021 - Virtual event, Tallinn , Estonia
Duration: 20 Apr 202121 Apr 2021


ConferenceCold Climate HVAC & Energy 2021
LocationVirtual event
Internet address
SeriesE3S Web of Conferences


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