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Record W2227667317

Multiple-inlet Building Integrated Photovoltaics: Modeling and Design including Wind Effects

2015· dissertation· en· W2227667317 on OpenAlexfundaboutno aff
Efstratios Dimitrios Rounis

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2015
Typedissertation
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaTrakya ÜniversitesiConcordia University
KeywordsBuilding-integrated photovoltaicsPhotovoltaic systemRenewable energyPhotovoltaicsAirflowEnvironmental scienceThermal energyHeat exchangerEngineeringAutomotive engineeringMechanical engineeringElectrical engineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

Air-based, open loop Building Integrated Photovoltaic/Thermal (BIPV/T) systems have proven to be an efficient means for generating renewable energy. They produce electrical energy, converting part of the incident solar radiation, and recover part of that radiation that turns to heat, while acting as the outer shell of the building. However, for the typical BIPV/T design with air entering at the bottom of the installation, flowing within a continuous air channel and exiting at the outlet of the system high PV temperatures may still occur. This is due to the fact that as air moves inside the air channel it accumulates heat and the heat exchange efficiency between the PV panels and the flowing air drops along the flow path of the air channel. In large building integrated PV installations, high PV temperatures may lead to quicker PV panel degradation, as well as lower electrical efficiency.
\nA multiple-inlet BIPV/T system aims to increased heat extraction from the PV panels, with the introduction of several intakes of fresh air along the height of the installation. This may lead to lower and more uniform PV temperatures, enhanced PV panel durability and higher electrical and thermal performance.
\nThis study presents the development of a methodology for the modelling and design of multiple-inlet systems, as well as a numerical study of such a system. The modelling component consists of two aspects, namely, the fluid mechanics and the energy balance of the system. A flow model was developed, based on flow networking techniques, in order to assess the inlet flow distributions. The flow model incorporates wind effects in the form of exterior pressures, acquired through wind tunnel testing. The inlet flow distributions were used in a modified energy balance model that accounts for the flow conditions of the inlets and the air channels of the system. This was an improvement on the assumption of uniform flow from all the openings of the system, which has been common in the limited number of studies of multiple-inlet systems so far.
\nThe developed models were applied for the numerical investigation of variations of multiple-inlet BIPV/T systems for a potential retrofit project on an office building in Montreal. The investigation was carried out assuming summer and winter conditions, as well as several cases of wind direction and velocity. A multiple-inlet system with optimized geometric features of the inlets was found have up to 1% higher electrical efficiency and 14% to 25% higher thermal efficiency than that of a single-inlet system, also resulting in lower and more uniform PV operating temperatures. The latter can be a crucial factor for the durability of large building integrated PV installations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.056
GPT teacher head0.297
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2015
Admission routes2
Has abstractyes

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