Modelling and evaluation of the performance of building-integrated open loop air-based photovoltaic/thermal systems
Bibliographic record
Abstract
Building-Integrated Photovoltaic/Thermal Systems (BIPV/T) systems are photovoltaic installations incorporated as the exterior layer of the building envelope with the additional function of recovering thermal energy, which can then be used for space heating, domestic water heating and possibly for cooling. Some advantages of a BIPV/T system over an autonomous PV array include lower installation costs due to the replacement of cladding material, elimination of extra support structures and reduced electrical transmission losses. In addition, recovering the heat from the photovoltaic panels cools them and thus improves their electrical efficiency. Due to the novelty of BIPV/T systems, there is a need for the measurement of convective heat transfer coefficients and development of correlations for their prediction. The development of an integrated energy model, including correlations for the prediction of convective heat transfer coefficients in BIPV/T systems was one of the main objectives of this thesis. Accurate measurements of convective heat transfer coefficients have been carried out for two open loop BIPV/T configurations: smooth and ribbed. The BIPV/T systems were tested at 30°-45° tilt angles and had a length/hydraulic diameter ratio of 38 which is representative of roof applications. It was found that for the BIPV/T ribbed case, the calculated Nusselt numbers are on average 2.6 times higher than the Nusselt numbers predicted by the Dittus-Boelter correlation. Pressure drop measurements were performed for the two configurations and the results are presented in terms of the Darcy friction factors and compared to the Blasius equation. For both cases, the friction factors are higher compared to the ones predicted by the Blasius equation. Previous existing electrical photovoltaic models have been used to couple their features to the lumped parameter thermal network modelling approach used in this thesis. Two thermal network models, steady state and transient, have been developed in this work and validated against experimental data. The steady state model is useful for a quick evaluation of the thermal/electrical performance, while the transient model gives a more accurate representation of the system by considering the thermal storage capacity of the materials. Finally, conclusions and general recommendations and guidelines for the design and construction of BIVP/T systems are provided
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".