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Record W2027530021 · doi:10.1109/tpel.2011.2173353

A General Approach for Quantifying the Benefit of Distributed Power Electronics for Fine Grained MPPT in Photovoltaic Applications Using 3-D Modeling

2011· article· en· W2027530021 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 Power Electronics · 2011
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhotovoltaic systemMaximum power point trackingPower electronicsIrradianceElectronicsMaximum power principleSolar micro-inverterSolar irradianceEnergy harvestingEngineeringComputer scienceAutomotive engineeringElectrical engineeringElectronic engineeringEnergy (signal processing)MeteorologyMathematics

Abstract

fetched live from OpenAlex

This paper deals with photovoltaic power installations in urban environments. A general simulation method is developed to quantify the total energy yield for photovoltaic (PV) installation sites exploiting different levels of Distributed Maximum Power Point Tracking (DMPPT) granularity. The process includes 3-D modeling, shading evaluation of the installation site, and irradiance calculations on the PV surfaces on an hourly basis throughout the year. Three leading microconverter topologies are analyzed and the cost/performance tradeoff is discussed for panel-level DMPPT. The energy yield evaluation technique is confirmed by means of several miniature PV acquisition units for frequent irradiance and temperature measurements in the installation site. The yearly energy yield benefit is shown to be highly dependent on the relative shading in the three installation sites. It is found that the energy yield benefit easily outweighs the power electronics costs in two of the three installations for panel-level DMPPT. The analysis method can be used by PV installers and system designers for accurate energy yield prediction, as well as power electronics engineers who need to bound the cost of their design based on the net energy benefit of the installed PV system.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.899
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.051
GPT teacher head0.281
Teacher spread0.230 · 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