Predictive Control-Oriented Models of a Domestic Air-to-Water Heat Pump Under Variable Conditions

Air-to-water heat pumps are quite often integrated with a hot-water tank, to better decouple the generation from the delivery of heat in buildings and to improve the overall performance of the system. The estimation and prediction of the coefficient of performance of the heat pump is extremely important to enforce efficiency, but it is also a very challenging task, due to the strong dependency of the performance on disturbances and operating conditions. Another source of potential model mismatch is the variable water flow rate in the condenser side induced by the heat pump low-level control logic, which gives rise to a non-trivial nonlinear system. In this letter, we tackle the problem to develop and properly tune an equivalent control-oriented model for the system, i.e. heat pump and tank, under variable flow rate conditions on both the condenser and load side, while still preserving good prediction capabilities of the model, with no tank temperature nor mass flow rate sensors. In particular, we focus on a real case study consisting in an air-to-water heat pump system and a 150m
²
building located in SYSLAB, Department for Electrical Engineering, Risoe Campus, Denmark Technical University. The quality of the developed models is then evaluated through a nonlinear model predictive controller suitably designed and checked against detailed reference models previously developed. Finally, different sensitivity analyses are performed, which witness the robustness of the proposed algorithm.