Using ground-source heat pumps (GSHPs) instead of fossil-fuel based energy systems can significantly reduce the building sector's considerable carbon footprint. Most GSHPs rely on borehole heat exchangers (BHEs), which use the subsurface as a heat source in winter and a heat sink in summer. Realizing the full carbon-saving potential of GSHPs requires accurate design, installation, and operation of both the heat pumps and BHEs over their 30–50-year service life. In practice, however, uncertainties in subsurface thermal properties, simplified design tools, and limited information about future energy demand often lead to operational performance falling short of design expectations. This design–operation gap prevents GSHPs from operating at maximum efficiency. The work presented in this thesis aims at bridging the gap by identifying its causes, demonstrating the benefits of optimized operation, and contributing to model development. A GSHP system with 40 BHEs serves as the case study. An extensive monitoring system provides six years of high-resolution data on fluid temperatures and flow rates for each BHE. Based on the data, four studies focusing on different aspects of the design-operation gap are conducted. In the first study, the data is used to reveal the design–operation gap for the studied BHE field. The monitored field delivers, on average, 116 % of the planned cooling energy but only 6 % of the intended heating. Moreover, the data is analyzed with a focus on two commonly overlooked factors in design practice: (i) different heat exchange between BHEs and (ii) thermal gains and losses in the horizontal pipes connecting BHE heads to underground vaults. BHE heat exchange differs by around 20 %, which is partially attributed to horizontal pipes: A BHE with a 45 m horizontal pipe has an up to 75 % higher volumetric energy yield for cooling, while the energy yield is reduced for heating by about 50 %, both during cold months. The analysis highlights the design–operation gap and underscores the need for improved models and control strategies that can account for the analyzed influencing factors. In the second study, the dataset is used to assess the predictive accuracy of four BHE models (a numerical, transfer function, resistance-capacitance, and hybrid model) through sensitivity analysis, calibration, and forward simulation. Excluding horizontal header pipes, the hybrid model best matches measured outlet temperatures over both short (one-month) and long (four-year) periods. Transfer functions and resistance-capacitance models rely more heavily on calibration, but they are easier to implement in optimization frameworks due to their simpler structure. The third study evaluates the real-world impact of BHE optimization, which is often explored through simulation but rarely tested in practice. We analyzed data of 15 months of optimized operation in the BHE field, where model predictive control selected only a subset of BHEs to operate, and compared it to standard operation, where all 40 BHEs were operated simultaneously. Optimized operation reduced pumping electricity by two-thirds and tripled BHE field performance, i.e., resulted in significant energy savings. Finally, we explored whether the thermal effect of horizontal piping can be embedded in thermal response functions, a standard model used for BHE simulation. To this end, we derived data-driven response functions for each BHE and, in parallel, simulated model-based counterparts using a physics-based model that includes horizontal pipes. The results show that the inclusion of horizontal pipes in the model results in a better alignment with the data. As expected, data-driven response functions perfectly reproduce the measured data, but only 38 % of the physics-based response functions achieved similar accuracy. The results show that data-driven methods offer both speed and accuracy but are sensitive to measurement errors and uncertainty, thus requiring validation with physical models. Together, the studies demonstrate that the analyzed BHE field can serve as a demonstrator for bridging the design-operation gap. Applying these learnings to other BHE fields demands a site-specific integration of geosciences, energy planning, uncertainty analysis, continuous monitoring, and operation optimization. Further research should explore how these methods can be incorporated into existing planning processes and standards to support more adaptive and data-informed BHE system design.
Elisa Heim (Wed,) studied this question.