15 May 2023

Presentation No 805 – Maximizing operational efficiency of heat pumps with Model Predictive Control: An experimental case study for residential application – 14th IEA Heat Pump Conference, Chicago, USA

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In residential heating applications, electrically-driven heat pump systems enable the integration of renewable
energy sources (RES) and, thus, systematic sector defossilation. Since the heating demand of buildings and
RES availability are time-variant and time-shifted, it is challenging to ensure optimal heat pump system
operation. Optimal heat pump system operation requires access to reliable system interfaces and consistent use
of higher control strategies such as model predictive control (MPC). However, missing interfaces prevent the
spread of MPC in the field and call for conventional controls such as heating curves reducing the overall
potential.
This work shows the potential of MPC for heat pump systems by exploiting system interfaces in an
experimental case study. We use a heat pump test bench coupled to a dynamic building performance simulation
model in the hardware-in-the-loop approach and investigate two control levels: The refrigerant cycle controller
ensures stable superheat and resilient operation; the system controller minimizes the heat pump power
consumption within the comfort constraints. We analyze two MPC interfaces to control the system: First, the
MPC sets the flow temperature, while a PID controls the compressor speed. Second, the MPC directly adjusts
the compressor speed. We compare both MPC strategies with a conventional heating curve controller.
The results highlight the need for heat pump interfaces to widespread MPC. Both MPC strategies reduce the
heat pump power consumption by up to 20.25 %. Adjusting the flow temperature by MPC results in the lowest
energy consumption but many compressor starts and comfort losses. Direct compressor-controlled systems
claim the best results concerning comfort constraints and lead to a resilient operation by reducing on-off
behavior.