Flexibility Estimation of Hybrid Heat Pumps based on Grey Box Model Identification

Hybrid Heat Pumps (HHPs) have emerged as a promising technology on the residential side, but estimating their potential flexibility quantity in extrapolated scenarios with different thermal profiles remains a critical challenge. We currently have real measurement data from a pilot project in the Netherlands, but it is difficult to determine the specific parameters of existing and potential households when assessing the overall flexibility potential. To address this, we propose a greybox identification method to fit thermal parameters from real project data, and apply the corresponding clustering algorithm to generate representative user profiles. Based on these, we formulate both a flexibility provision model and an extrapolation model for future HHP adoption scenarios. Among the tested regression methods, Huber robust regression achieves the best accuracy and robustness. The results indicate that HHPs provide higher flexibility at lower outdoor temperatures, while the extrapolation case shows that the added flexibility benefit of new users is more pronounced in colder conditions.