Abstract
Dynamical model identification is an essential element in the implementation of a model predictive controller. In this work, a control-oriented first order model was identified in a dedicated experiment on a super-insulated single-family house. First, parameters resulting from CTSM and the MATLAB System Identification toolbox were compared. Then, a comparison of model predictions and measurements showed that this simple model captures well the main dynamics of the building-averaged indoor temperature, after one week of training on rich data with sample time below 15 min. It was also observed that this prediction performance was not affected by the configuration of internal doors.
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Project links: http://www.zeb.no/ | http://www.fp7-advantage.eu/ | http://www.annex67.org/.
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Acknowledgements
The authors would like to acknowledge valuable input from Eirik Selvnes, Stein Kristian Skånøy, Martin Thalfeldt, Peng Liu, Francesco Goia (NTNU), Maria Justo-Alonso (SINTEF), Glenn Reynders (KU Leuven), Peder Bacher (DTU Compute), and the 2 anonymous reviewers. Access to the LivingLab was provided and funded by the Research Centre on Zero Emission Buildings project (and its successor: the Research Centre on Zero Emission Neighbourhoods in Smart Cities), while the main author’s work was part of the ADVANTAGE project funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 607774. This work was initiated as part of a collaboration within the IEA EBC Annex 67 “Energy Flexible Buildings”.Footnote 1
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Vogler-Finck, P.J.C., Clauß, J., Georges, L., Sartori, I., Wisniewski, R. (2019). Inverse Model Identification of the Thermal Dynamics of a Norwegian Zero Emission House. In: Johansson, D., Bagge, H., Wahlström, Å. (eds) Cold Climate HVAC 2018. CCC 2018. Springer Proceedings in Energy. Springer, Cham. https://doi.org/10.1007/978-3-030-00662-4_44
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