A novel methodology assessing the use of Semi-Transparent Photovoltaics integrated onto Double Skin Facades and their impact on the energy consumption of buildings
Bibliographic record
Abstract
Building-integrated Photovoltaics (BIPV) can replace building elements in both facades and roofs improving at the same time the thermal, the electrical and the daylighting performance of the building. A novel approach in BIPV is the Double Skin Façade (DSF) that integrates Semi-Transparent Photovoltaics (STPV). In this approach, the air that passes within the cavity created between the layer of the STPV and the building, acts as a buffer zone and depending on the preferred strategy, it can be used for heating, cooling or ventilating the building. In addition, the STPV is the exterior layer of the envelope, controlling the solar gains but also allowing daylight into the interior space. \nThis thesis identifies the important parameters of a double skin façade integrating semi-transparent photovoltaics (DSF-STPV) as well as the gaps in the existing literature, namely the lack of experimental studies on mechanically-ventilated DSF-STPV buildings and the lack of investigation of heat transfer coefficients within the cavity in the presence of wind effects. In addition, it appears that there are neither tools to simulate such complex systems nor guidelines to assist architects and engineers to optimally design a DSF-STPV system. \nA methodology was developed to assess the use of STPV integrated onto DSF and their impact on the energy consumption of buildings. The thermal model employed was verified in an outdoor experimental set-up of a mechanically-ventilated DSF-STPV and an insulating glazing unit (IGU) integrating STPV (IGU-STPV) built at Concordia University (Montreal, Canada). The forced convection within the cavity of the DSF-STPV has been investigated and three Nusselt number correlations were developed and validated. An experimental test-room was also used for a comparison between the DSF-STPV and the IGU-STPV under specific outdoor conditions. From the experimental analysis it has been found that a DSF-STPV can reduce the exterior heat losses due to wind, by more than 20%, whereas the total combined efficiency of the DSF-STPV, can reach the 75% level. The comparison between the DSF-STPV and the IGU-STPV presents increased electrical performance of the DSF-STPV up to 9% and lower average temperature difference that reaches up to 10oC. \nThe developed Nusselt number correlations were used for the development and validation of a parametric numerical model of a DSF-STPV. The model also allows the user to perform a parametric analysis changing the design parameters of the thermal zone and the DSF-STPV. This model can also simulate battery storage and its effect on peak demand. A parametric analysis was carried out for sixteen (16) different ASHRAE climate zones, two (2) insulation cases for every climate location (baseline and advanced), nine (9) different cavity widths, nine (9) different cavity velocity set-points and twelve (12) different strategies, changing the operation of the DSF-STPV. \nAn analysis of the optimal operation for all sixteen (16) ASHRAE climate zones was presented, concluding that the climate locations can be separated into three main categories based on their behaviour, i.e. hot and mild, cold, and extreme cold locations, as they present similar patterns and strategies to achieve minimal energy consumption. In addition, the parametric analysis has shown that, for most cases, practical cavity widths under or over 0.50 m - 0.60 m show similar behaviour. \nThe mismatch between the electricity production by the STPV and the electricity needed for heating and lighting by the adjacent building perimeter zones was investigated, for Montreal, Canada. With the use of a predictive heating strategy, the peak demand of the building can coincide with the peak of the electricity production, resulting in more than 80% reduction in the electricity consumption by the grid during the peak hours.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".