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Record W4236488975 · doi:10.22215/etd/2014-10332

Environmental Effects on the Operation of Triple-Junction Flexible Photovoltaic Panels

2014· dissertation· en· W4236488975 on OpenAlexaffabout
K. Graff

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsPhotovoltaic systemTilt (camera)Triple junctionAmorphous siliconPower (physics)Environmental scienceEngineeringAutomotive engineeringElectrical engineeringSolar cellMaterials scienceCrystalline siliconOptoelectronicsMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

This thesis contains a complete description of a solar photovoltaic experiment to monitor and predict the performance of solar technology in the temperate climate in Ontario. An experiment was designed and built to monitor weather data and determine the operating characteristics of the modules using high-resolution equipment. The data gathered were used in i the one-diode model to predict the power produced by the modules. A large sample of data was not achievable due to the experiment taking place during the winter where snow and a low solar angle heavily reduced the module performance. Results were nevertheless obtained for a Uni-Solar PVL-144 thin-film triple junction amorphous silicon module, and the power predicted was within 25% of what was measured. The module efficiency was found to be 7% -8% and the ideal tilt angle for Ottawa to be 50 10 . The findings presented in this thesis form a basis for future work in characterizing other types of solar modules in the Ontario climate, as well as furthering research in snow accumulation effects on photovoltaic systems. Most importantly, I am grateful for my thesis supervisor, Dr. Steven McGarry, for his dedicated efforts in keeping me motivated and pushing me to finish this work. I am

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.495
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.231
Teacher spread0.221 · 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

Citations2
Published2014
Admission routes2
Has abstractyes

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