Optimization of Cooled Building-Integrated Photovoltaics Using Powell’s Conjugate Direction Method in Canada
Bibliographic record
Abstract
The majority of sustainable buildings integrate solar PV panels for energy production. The most common drawback of PVs is the efficiency degradation at elevated temperatures. Using EnergyPlus and MATLAB, the current work proposed a novel integration of an optimization method and an energy flow model to decrease the PVs’ temperature and increase the power generation. The model decision variables were the water mass flow rate, the eccentricity between pipes, and the PV tilt angle. Such decision variables were optimized using Powell’s Conjugate Direction Method. The optimization was performed for 13 different cities covering all Canadian provinces for each of the 12 months. Results showed that the optimum eccentricity for all cases tended to the lower limit, 0.1 m, to increase the number of pipes and hence increase the surface area enhancing heat transfer. Consequently, such a high surface area decreased the required water, and the optimum required water flow rate was 0.44 kg/s maximum. The optimum tilt angle decreased in summer to face the high sun elevation and increased in winter to compensate for the decrease in the sun elevation. The proposed system was most efficient in Vancouver City in the summer when the energy generation was increased by an average of 58%. In all cities, the average power increments in summer and winter were 67.5 and 23.5 W/panel, respectively. The cooling system initial investment, which was 10.4 CAD per panel, achieved monthly savings of up to 6.1 CAD per panel and annual savings of up to 25 CAD per panel. For all optimized cases, the simple payback period was between 5 and 13 months.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".