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Record W2142461803 · doi:10.1109/tste.2015.2412694

Accuracy Improvement of the Ideal PV Model

2015· article· en· W2142461803 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Sustainable Energy · 2015
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDatasheetIrradiancePhotovoltaic systemIdeal (ethics)Solar irradianceSimplicitySaturation currentMonocrystalline siliconComputer scienceElectronic engineeringEngineeringVoltageElectrical engineeringOpticsPhysics

Abstract

fetched live from OpenAlex

The only photovoltaic (PV) model in the literature featuring low computational effort is the ideal PV circuit model because it uniquely relies on a simple nontranscendental equation. Unfortunately, it suffers from a deteriorated accuracy at low irradiance levels. This letter enhances the accuracy of the ideal PV model at low irradiance levels without affecting its simplicity. The proposed approach modifies the equation of the saturation current such that it takes the irradiance variations into consideration. The effect of the proposed modification on the complexity of the model is shown to be negligible. The accuracy improvement is also demonstrated by comparing the proposed and existing ideal models to the measurements provided by the manufacturing datasheet of a monocrystalline PV module.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.248
Teacher spread0.231 · 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