Investigation of a Photovoltaic Thermal-Direct Expansion Solar-Assisted Heat Pump (PVT-DXSAHP) Collector with Different Photovoltaic Characteristics in Cold Climates
Bibliographic record
Abstract
In this paper, the performance of a direct expansion solar-assisted heat pump (DX-SAHP) with a photovoltaic thermal (PVT) collector made with different solar cells was investigated. A thermodynamic model of a direct expansion solar-assisted heat pump with a PVT collector and a 180 L water tank for thermal energy storage was developed. The model was implemented in MATLAB, with the CoolProp library for the retrieval of working fluid thermodynamic properties. The solar collector cells considered were ®Solartech, ®LG, ®Prime, ®VOLT, and ®VSUN. The performance of the system is characterized by the coefficient of performance, thermal efficiency, electrical efficiency, heat pump ratio and auxiliary heat ratio. The highest average coefficient of performance of the heat pump was with ®Solartech solar cells on a sunny day in winter was 4.08 , and 7.91 on a sunny summer day. On a cloudy summer day, the ®Prime solar cell had the highest average coefficient of performance at 6.45. The highest electrical efficiency of the collector was observed with ®Prime solar cells, with an efficiency of 14.4%, 16.5% and 13.6%, respectively, from a sunny day in winter, a sunny day in summer and a cloudy day in the summer. The highest thermal efficiency was obtained by ®Solartech solar cells for all weather conditions. With a collector area of 5 m2 and a consumer load of 0.001 kg/s, the heat pump meets an average of 15.6% of the total heat needed for domestic hot water demand on a sunny winter day. This increases to 38.2% and 49.0% on cloudy and sunny summer days, respectively. KEYWORDS: Coefficient of Performance; Direct Expansion; Heat Pump Ratio; Photovoltaic Thermal ; Water Heating; Solar-Assisted Heat Pump
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".