solar-assisted heat pump, BIPV/T, MPC, load management, simplified modelling
This paper presents a simulation study of a model-based predictive control (MPC) strategy applied to a BIPV/T-assisted cold climate heat pump. When innovative technologies are brought into play, reaching their full potential depends on proper operation and control. For instance, the coordination of renewable energy systems with a highly variable output, thermal energy storage devices and fluctuating building load conditions can significantly benefit from advanced control and operating strategies. MPC strategies, combined with adequate energy storage capabilities, can make a critical positive impact in the implementation of innovative solutions. The mechanical system under study, designed during the early design phase of a 2000-m2 net-zero energy building, consists of a BIPV/T roof with an electrical output of nearly 52 kW and a total area of 320 m2, a set of two air-source cold-climate heat pumps (PUHY-HP96, Mitsubishi) and a 20-m3 energy storage tank. Frost and de-frost cycles of the heat pump are considered in this study, as well as the power used by the fans in the BIPV/T system. The performance of the system is compared with a more conventional ground-source system. The dynamic simulation of the building and its systems was implemented in MATLAB/Simulink using relatively simple, low-order models with inputs from expected occupancy levels and typical meteorological year (TMY) weather data. Models for the BIPV/T system and the TES tank were also developed. A look-up table model was used for the simulation of the heat pumps. Simulation results shed light on design decisions concerning the building systems and facilitate the development of control strategies to achieve a smooth and successful operation. Model-based predictive control algorithms were used to select the sequence of optimal states of charge for the TES tank as a function of expected weather conditions and occupancy patterns.