Experimental evaluation and climate-based feasibility of thermoelectric energy harvesting in PVT systems
Bibliographic record
Abstract
This study evaluates the feasibility of integrating thermoelectric generators (TEGs) with photovoltaic-thermal (PVT) systems to enhance power generation and heat recovery. A laboratory-scale prototype was developed, and an approximation equation was derived based on temperature differential and flow rate to estimate the TEG power output. In the first experiment, TEG performance was assessed under varying surface temperatures. At a temperature difference of 30 °C between the hot and cold sides, a 55 × 55 mm TEG module generated 0.74 V and 0.37 A, yielding a power output of 0.3 W. Under an irradiance of 1000 W/m², the PVT-TEG module exhibited a temperature difference of 1.9 K, generating power outputs of 0.96–0.98 W from the PV panel, 0.006 W from the TEG, and 15 W of additional heat recovery. Furthermore, a TRNSYS18-based simulation was used to analyze the PVT-TEG system performance across six climate zones, revealing significant energy output variations. Cairo, characterized by high solar radiation and large diurnal temperature fluctuations, recorded the highest power generation (PVT: 265 kWh/(m²·yr), TEG: 48.5 kWh/(m²·yr)). The results highlight a strong correlation between climatic conditions and system performance, demonstrating that variations in solar radiation and temperature gradients significantly impact energy output.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".