Energy and economic evaluation of thermal regulation of PV panels using a hybrid phase change material-evaporative clay cooling system
Bibliographic record
Abstract
A hybrid cooling system that combines Phase Change Material (PCM) and evaporative cooling clay (PV/PCM-Clay) is employed to investigate the thermal regulation of Photovoltaic (PV) solar cells. The study assesses PV performance improvement and economic viability through energetic and economic analyses in comparison with PV cooling systems utilizing PCM, clay-based evaporative cooling, and naturally air-cooling systems. A comprehensive transient mathematical model is developed and numerically solved in MATLAB, based on Upper Egypt’s climate data over the past decade. Results revealed that the PV/Clay cooling system outperformed other cooling methods. The cells’ operating temperature ultimately dropped by 9.9 °C, 15.2 °C, and 17.2 °C while the cells’ efficiency improved by 3 %, 5.9 %, and 6.9 % utilizing PV/PCM, hybrid PV/PCM-Clay, and PV/Clay, respectively, compared to conventional PV. Additionally, the PV/Clay cooling system achieved the highest power output, enhanced by 8.8 %, but also incurred the greatest electricity production cost, rising by 24.6 % over the standard PV system. The conventional PV system required 18.23 years to achieve payback, while the PV/PCM cooling system reduced this to 8.2 years, reflecting a 55 % improvement. Conversely, utilizing the Clay cooling system extended the payback period to 19.75 years, which is an 8.3 % increase over the conventional system. The hybrid PCM/Clay cooling system showed the most significant payback improvement of 40.3 % when only 20 % of the rear surface was covered with evaporative clay, whereas an 80 % coverage resulted in the smallest improvement of 7.5 %. These cooling methods demonstrated their effectiveness, particularly evaporative cooling, which significantly enhances PV system performance. However, the economic feasibility of evaporative cooling varies widely, depending on water availability and cost effectiveness across different regions.
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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".