In this research, a modelling tool is presented to de- rive surrogate models of thermal energy transfers in buildings, to support the development and testing of smart control algorithms. A data-driven approach is used to identify a model that is able to predict the indoor temperature in a case-study building when an electric heater is turned on. The approach is demon- strated on data obtained from EnergyPlus simula- tions, which resolve the heat balance equations to simulate the thermal response of a building. The model structure that was selected is a second-order ARMAX transfer function whose parameters were identified with a Least Squares optimisation criterion. The model inputs were limited to the heater’s power, the global horizontal solar radiation and the outdoor dry-bulb temperature.
|Title of host publication||Building Simulation Conference proceedings|
|Publication status||Accepted/In press - 2021|