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Record W2118622102 · doi:10.5370/jeet.2010.5.1.061

Modeling and Control of a Doubly-Fed Induction Generator (DFIG) Wind Power Generation System for Real-time Simulations

2010· article· en· W2118622102 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

VenueJournal of Electrical Engineering and Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsRTDS Technologies (Canada)
Fundersnot available
KeywordsStatorControl theory (sociology)Real-time simulationVector controlReal Time Digital SimulatorWind powerInduction generatorAnemometerRotor (electric)ConvertersEngineeringWind speedPower (physics)Computer scienceElectric power systemInduction motorSimulationVoltageControl (management)Electrical engineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents a study of a DFIG wind power generation system for real-time simulations. For real-time simulations, the Real-Time Digital Simulator (RTDS) and its user friendly interface simulation software RSCAD are used. A 2.2MW grid-connected variable speed DFIG wind power generation system is modeled and analyzed in this study. The stator-flux oriented vector control scheme is applied to the stator/rotor side converter control, and the back-to-back PWM converters are implemented for the decoupled control. The real-wind speed signal extracted by an anemometer is used for a realistic, reliable and accurate simulation analysis. Block diagrams, a mathematical presentation of the DFIG and a control scheme of the stator/rotor-side are introduced. Real-time simulation cases are carried out and analyzed for the validity of this work.

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: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.456

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 head0.005
GPT teacher head0.199
Teacher spread0.194 · 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