Improving Cost Efficiency of Heat Pump-Based Heating and Cooling Systems

Heating and cooling systems based on heat pumps offer high energy efficiency but face challenges in operational cost due to suboptimal control strategies. This thesis investigates methods to improve the cost efficiency of a heat pump-based system consisting of nine ground-source heat pumps (each 90-kW max output with four gear levels) by treating the heat pump array as a flexible energy resource. We develop an optimized control strategy that integrates (i) a model for demand-based power calculation, (ii) a priority-based scheduling of heat pumps by time of day and gear efficiency, and (iii) a mixed-integer linear programming (MILP) optimization for cost-minimal gear selection each hour. We also implement an on/off control scheme that allows room temperature to float between 21°C and 25°C, reducing run-time during low-demand periods. A MATLAB/Simulink simulation model is built to evaluate the approach under varying outdoor temperatures and dynamic electricity pricing. Results show that the optimized control significantly reduces daily operating cost compared to a conventional continuous operation. In a representative 24-hour scenario, the proposed on/off optimized strategy achieved the required indoor comfort while cutting the energy cost by nearly 70% (down to about €63 per day) relative to a normal control approach. The results are based on a specific single day in wintertime. The thesis concludes with a discussion of key findings, system limitations, and recommendations for future research on integrating heat pumps as flexible resources in smart energy grids.