| Summary: | Thermal mass of buildings and domestic hot water tanks represent interesting sources of thermal energy storage readily available in the existing building stock. To exploit them to their full potential, advanced control strategies and a coupling to the power grid with heat pump systems represent the most promising combination. In this paper, model predictive control (MPC) strategies are developed and tested in a semi-virtual environment laboratory setup: a real heat pump is operated from within a controlled climate chamber and coupled with loads of a virtual building, i.e., a detailed dynamic building simulation tool. Different MPC strategies are tested in this laboratory setup, with the goals to minimize either the delivered thermal energy to the building, the operational costs of the heat pump, or the CO2 emissions related to the heat pump use. The results highlight the ability of the MPC controller to perform load-shifting by charging the thermal energy storages at favorable times, and the satisfactory performance of the control strategies is analyzed in terms of different indicators, such as costs, comfort, carbon footprint, and energy flexibility. The practical challenges encountered during the implementation with a real heat pump are also discussed and provide additional valuable insights.
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