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Record W2766188963 · doi:10.3390/en10111726

Implementation, Comparison and Application of an Average Simulation Model of a Wind Turbine Driven Doubly Fed Induction Generator

2017· article· en· W2766188963 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

VenueEnergies · 2017
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsResearch ManitobaUniversity of Manitoba
Fundersnot available
KeywordsInduction generatorTurbineDoubly fed electric machineWind powerConvertersTransient (computer programming)Control theory (sociology)EngineeringPower electronicsPower (physics)Control engineeringComputer scienceAC powerElectrical engineeringVoltagePhysicsMechanical engineering

Abstract

fetched live from OpenAlex

Wind turbine driven doubly-fed induction generators (DFIGs) are widely used in the wind power industry. With the increasing penetration of wind farms, analysis of their effect on power systems has become a critical requirement. This paper presents the modeling of wind turbine driven DFIGs using the conventional vector controls in a detailed model of a DFIG that represents power electronics (PE) converters with device level models and proposes an average model eliminating the PE converters. The PSCAD/EMTDC™ (4.6) electromagnetic transient simulation software is used to develop the detailed and the proposing average model of a DFIG. The comparison of the two models reveals that the designed average DFIG model is adequate for simulating and analyzing most of the transient conditions.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.393

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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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