MétaCan
Menu
Back to cohort
Record W2899505173

Grid Fault Performance of Brushless Doubly-Fed Reluctance Machines in Wind Turbine Applications

2018· article· en· W2899505173 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

VenueEuropean Conference on Power Electronics and Applications · 2018
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMagnetic reluctanceControl theory (sociology)Fault (geology)TurbineGridCoupling (piping)Computer scienceRotor (electric)TorqueWind powerControl engineeringEngineeringElectrical engineeringPhysicsMagnetMechanical engineeringMathematicsControl (management)
DOInot available

Abstract

fetched live from OpenAlex

The DFIG and the BDFRM have very similar dynamic equations, however the BDFRM's complex flux coupling produces machine parameters very different to the DFIG. These parameter differences result in different intrinsic machine behaviour under fault conditions. This paper develops and uses a simple model to explain the fault performance differences between the machines, and then verifies these predictions using a combination of simulation and experimental results. The general conclusion is that the intrinsic large leakage inductances of the BDFRM assist with protecting the rotor side converter during grid side fault 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.846

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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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