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Record W1607829366 · doi:10.1109/pesc.2006.1712212

Power electronic converter control techniques for improved low voltage ride through performance in WTGs

2006· article· en· W1607829366 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsWind powerLow voltage ride throughTurbineRealization (probability)VoltagePower (physics)SizingElectrical engineeringLimit (mathematics)Computer scienceLow voltageEngineeringAutomotive engineeringAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

The low voltage ride through (LVRT) requirement that has recently been imposed on the majority of new wind park projects has direct implications on the design and sizing of the power electronic conversion component. This paper considers three wind energy conversion systems and compares them in terms of the additional power electronic infrastructure and control that is required to meet the LVRT requirement. The complete detailed models are developed using electromagnetic transients programming and are compared for various low voltage events. The results convincingly show that the turbine that is interfaced through a full converter, using a dump load to limit dc over voltages, is simple in terms of realization and demonstrates superior performance.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.779
Threshold uncertainty score0.851

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 head0.002
GPT teacher head0.176
Teacher spread0.174 · 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

Quick stats

Citations50
Published2006
Admission routes1
Has abstractyes

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