Influence of control strategy on the energetic performance of an air source heat pump coupled with a solar air collector for domestic hot water in a cold climate
Bibliographic record
Abstract
Air source heat pumps (ASHPs) are becoming famous for heating applications, particularly in regions with moderate climatic conditions . However, in colder climates, their efficiency and capacity are reduced significantly and require high auxiliary heating loads . As such, coupling ASHPs with solar energy and energy storage is receiving considerable interest. This study investigates the performance of a solar-assisted air source heat pump for domestic hot water in an extremely cold climate. The operation of the air source heat pump (ASHP) is controlled based on the outdoor temperature and solar radiation. The rated capacity of the ASHP is 2 tons, while the rated minimum outdoor air temperature is −25°C. Since the heat pump capacity reduces at temperatures lower than −10°C, the potential improvement in performance when coupled with an SAC for a lower threshold of ambient temperatures between −10 and −25°C is evaluated. The designed control strategy also includes a lower threshold of solar radiation intensity , i.e. ≥300 W/m 2 or ≥200 W/m 2 or ≥100 W/m 2 or ≥0 W/m 2 . In addition, the study explores the effect of recirculating air in the SAC on the overall heat pump performance. Results show that the coefficient of performance (COP) of the ASHP increases by 18%, and the heat pump fraction (HPF) is 94% when the heat pump is controlled to work for solar intensities greater than or equal to 300 W/m 2 and outdoor temperatures greater than or equal to −25°C. With the same limits, energy savings of 20% are realized. Moreover, the performance improves by 24% when air is recirculated in the SAC at the same conditions. This comprehensive analysis highlights the potential of the control strategy and air recirculation in ASHPs coupled with solar air collectors in cold climates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".