Roel De Coninck
E nv., Brussels, Belgium/KU Leuven, Department of Mechanical Engineering, Heverlee, Belgium
Fredrik Magnusson
Department of Automatic Control, Lund University, Lund, Sweden
Johan Åkesson
Department of Automatic Control, Lund University, Lund, Sweden/Modelon AB, Ideon Science Park, Lund, Sweden
Lieve Helsen
KU Leuven, Department of Mechanical Engineering, Heverlee, Belgium,
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http://dx.doi.org/10.3384/ecp14096657Published in: Proceedings of the 10th International Modelica Conference; March 10-12; 2014; Lund; Sweden
Linköping Electronic Conference Proceedings 96:69, p. 657-666
Published: 2014-03-10
ISBN: 978-91-7519-380-9
ISSN: 1650-3686 (print), 1650-3740 (online)
As automatic sensing and Information and Communication Technology (ICT) get cheaper; building monitoring data is easier to obtain. The abundance of data leads to new opportunities in the context of energy efficiency in buildings. This paper describes ongoing developments and first results of data-driven grey-box modelling for buildings. A Python toolbox is developed based on a Modelica library with thermal building and Heating; Ventilation and Air-Conditioning (HVAC) models and the optimisation framework in JModelica.org. The tool chain facilitates and automates the different steps in the system identification procedure; like data handling; model selection; parameter estimation and validation. The results of a system identification and parameter estimation for a singlefamily dwelling are presented.
