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Record W4416050830 · doi:10.3103/s0003701x24603090

Operation of Two-axis Tracking Monofacial and Bifacial Photovoltaic Systems in Humid Continental Climate

2025· article· en· W4416050830 on OpenAlexaff
Mohammad Sadegh Talebi, Maïté Volatier, David Chuet, Vincent Aimez, Jean-François Lerat, Gwénaëlle Hamon, Sylvain Nicolay, Maxime Darnon

Bibliographic record

VenueApplied Solar Energy · 2025
Typearticle
Languageen
FieldComputer Science
TopicSolar Radiation and Photovoltaics
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPhotovoltaic systemAlbedo (alchemy)SnowSoftware deploymentRenewable energyClimate change

Abstract

fetched live from OpenAlex

Abstract With the large-scale deployment of renewable energy, photovoltaic systems are installed worldwide, including in regions with humid continental climate. We present here the energy production of 2-axis tracking systems equipped with either monofacial or bifacial modules. We show that severe weather conditions, especially in winter, force the systems to operate in a degraded mode (i.e. 10° fixed tilt) that leads to yearly losses of ~4%. Other losses that include snow-induced losses lead to 12 and 9% additional losses for monofacial and bifacial systems, respectively. Bifacial modules are better suited than monofacial modules in the studied climate and system configuration, thanks to a higher sensitivity to albedo and higher ability to shed snow during winter, that both amplify the bifaciality gain during snowy months.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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