| Issue |
E3S Web Conf.
Volume 689, 2026
14th International Symposium on Heating, Ventilation, and Air Conditioning (ISHVAC 2025)
|
|
|---|---|---|
| Article Number | 08003 | |
| Number of page(s) | 8 | |
| Section | HVAC System Modelling, Simulation, and Evaluation | |
| DOI | https://doi.org/10.1051/e3sconf/202668908003 | |
| Published online | 21 January 2026 | |
From static to adaptive: A virtual testing framework for continuous commissioning and performance optimization of ground source heat pump systems
1 College of Urban Construction, Nanjing Tech University, Nanjing, China
2 Energy Efficient Cities Initiative, Department of Engineering, University of Cambridge, Cambridge, United Kingdom
3 Department of Mechanical Engineering, Indian Institute of Technology Delhi, New Delhi, India
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
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Abstract
Traditional commissioning, conducted at system handover, often fails to identify and address operational inefficiencies in ground-source heat pump (GSHP) systems over time. This study proposes a model-based adaptive commissioning framework that combines physics-based modeling and simulation with continuous performance monitoring to detect and address system deficiencies. This method is applied to a GSHP system that is not performing well: the system had an annual average coefficient of performance (COP) of only 2.37, with 74% of its operating time below 50% load capacity. A high-fidelity Modelica- based model is developed to enable virtual testing of operational strategies, allowing assessment of possible improvements in system performance without disrupting building operations. Results show that changing from the original dual-unit operation to a single-unit operation with timely preheating can reduce energy use by 16% while keeping indoor thermal comfort. The heat pump COP can also rise to 4.39. The proposed model-based approach transforms commissioning from a one-time verification into an adaptive process, achieving £965.9 in cost savings over 14 days through control optimization without hardware modifications.
Publisher note: A typographic mistake in the DOI has been corrected in the PDF article on January 26, 2026.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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