Enhancing Heat Pump FeasibilityStudies Through Improved COP Estimation

Sammanfattning

Heat pumps are central to building and industrial decarbonisation strategies, yet their adoption relies on robust feasibility assessments during the early design phase, a stage often constrained by limited operational data and time for detailed simulations. This thesis aims to improve the reliability of heat pump performance estimation at this stage by developing a practical, data-driven Coefficient of Performance (COP) estimation tool that supports accurate energy and economic evaluations. Three modelling approaches were developed and compared: a theoretical model for trend validation and sensitivity analysis, a manufacturer-based model reflecting realistic equipment behaviour, and the Jensen model from the literature. The analysis demonstrated that using a constant COP typically underestimates actual energy consumption, leading to potential oversizing and misrepresentation of seasonal efficiencies. By employing variable COP models, estimations of seasonal performance become more accurate, aligning better with real operational behaviour and improving the reliability of capital expenditure and return on investment assessments. While the absence of field data limits direct validation, the consistency of the models with manufacturer data and literature benchmarks supports their robustness for early-stage feasibility studies. The work highlights the high sensitivity of the Jensen model to the fQ parameter, underlining the value of site-specific calibration when possible to improve estimation precision. Overall, this thesis contributes a practical approach to enhance the reliability of heat pump feasibility studies, supporting informed decision-making in decarbonisation projects and facilitating the transition toward carbon-neutral heating and cooling solutions in the building and industrial sectors.