Abstract

This study models the energy used for heating in buildings by applying system identification methodology. The model development is grounded in physics to provide guidance and interpretability when evaluated. Time-series of heating demand, outdoor temperature, indoor temperature and solar irradiation are considered for the modelling purpose. Evaluation is done through simulation and relies on quantitative measures, residual analysis and visual inspection of model output. Through model development, the study seeks to extrapolate information of physical properties that drives heating demand in buildings. Seven buildings located in the same geographic area are studied. It is found that linear ARX-models can simulate heating demand with high precision but at times low accuracy. A common system model structure can be identified between buildings, indicating that physical properties shared between buildings can be identified through this methodology. A sensitivity analysis is conducted to derive the contributions from model constituents to simulation results. Two buildings were also modelled as OE-models. These models performed better than the respective ARX-models but were deemed more difficult to use for the purpose of this study. The study finds difficulties in implementing aggregated time-series of indoor temperature, which could be explored further in future studies for more detailed interpretations. An interpretation of the physical properties identified is proposed.