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Record W7046195248

Development of a novel methodology for the determination of the total solar energy transmittance of Building-Integrated Photovoltaic window technologies using outdoor measurements

2023· dissertation· en· W7046195248 on OpenAlexafffund

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsOntario Drive & Gear (Canada)
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotovoltaic systemRenewable energySolar energyTransmittanceElectricitySolar gainPyranometerGlazingElectricity generation
DOInot available

Abstract

fetched live from OpenAlex

The urgent need to combat global warming and transition towards sustainable energy sources has focused attention on the building sector, a major contributor to energy consumption and greenhouse gas emissions. To achieve net-zero energy building performance, a comprehensive approach is essential, involving energy conservation measures, enhanced building systems efficiency, and integrating on-site renewable energy generation. Within this context, the integration of photovoltaic window technologies become essential for the generation of renewable electricity and reduction of solar heat gains which impacts building heating, cooling, and electric lighting loads as well as visual and thermal comfort. \n The aim of this thesis is to introduce the theoretical background of a novel experimental methodology for the determination of total solar energy transmittance (TSET) of building-integrated photovoltaic (BIPV) windows using outdoor measurements. Existing studies and standards dictate the use of indoor test facilities consisting primarily of a hot box calorimeter where the window is mounted and characterized under a steady state solar simulator. The calorimetric (thermal) methods require steady state conditions that have been proven challenging to achieve for windows that incorporate advanced shading devices or photovoltaic cells, potentially resulting to significant measurement errors of the TSET. Also, these studies rarely characterize the angular dependency of TSET. \nTo overcome these challenges, a novel experimental methodology is proposed to measure TSET using optical measurements under outdoor conditions. The experimental setup uses pyranometers (for solar transmittance measurements), pyrheliometer (for direct incident measurements), several Resistance Temperature Detector (RTD) sensors and infrared cameras (for surface temperature measurements), allowing the determination of TSET (and its angular dependency) based on a series of instantaneous outdoor measurements under sunny conditions that could result to reliable and repeatable TSET values. For the case of BIPV windows, a load at maximum power point (MPP) is connected to the window, allowing the maximum fraction of the absorbed solar energy to be converted into electricity. Finally, a new approach is proposed for the conversion of measured TSET to TSET under standard conditions, using a reference window of known TSET. \nThe unique aspects of the proposed TSET methodology are: i) the use of optical measurements ii) performed under transient outdoor test conditions. Current standard TSET calorimetric tests use thermal measurements that require long window conditioning under steady state conditions. The new methodology is also able to perform TSET measurements under a range of solar angle of incidence (i.e., 0 to 60 degrees), including normal TSET. The limitation of the proposed methodology is that it is not applicable to products with angular selective properties (e.g., microshade film). While it is developed for BIPV windows, and can be applied for TSET determination of coated, reflective, and electrochromic windows, under outdoor test conditions. \nIn summary, a novel experimental methodology is proposed for the determination of the total solar energy transmittance of Building-Integrated Photovoltaic windows using outdoor measurements. The proposed methodology aims to provide a framework to quick, accurate, consistent, and repeatable approach to TSET testing that can potentially be standardized for BIPV windows and other advanced window technologies. The proposed methodology intends to support the advancement of sustainable building practices, enhance energy efficiency, and foster the integration of renewable energy technologies into building design and construction, paving the way for a more sustainable built environment.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.066
GPT teacher head0.280
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2023
Admission routes2
Has abstractyes

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