Issues in identification of control-oriented thermal models of zones in multi-zone buildings

There is significant recent interest in applying model-based control techniques to improve the energy efficiency of buildings. This requires a predictive model of the building´s thermal dynamics. Due to the complexity of the underlying physical processes, usually system identification techniques are used to identify parameters of a physics-based model. We investigate the effect of various model structures and identification techniques on the parameter estimates through a combination of analysis and experiments conducted in a commercial building. We observe that a second order model can reproduce the input-output behavior of a full-scale model (with 13 states). Even a single state model has enough predictive ability that it may be sufficient for control purposes. We also show that the application of conventional techniques to closed-loop data from buildings (that are collected during usual operation) leads to poor estimates; their inaccuracy becomes apparent only when forced-response data is used for validation where there is sufficient difference among various inputs and outputs. The results of this investigation are expected to provide guidelines on do´s and don´ts in modeling and identification of buildings for control.