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Record W2054882063 · doi:10.1109/iecon.2010.5675037

Cost effective method for DFIG fault ride-through during symmetrical voltage dip

2010· article· en· W2054882063 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 institutionsToronto Metropolitan University
Fundersnot available
KeywordsCrowbarControl theory (sociology)StatorWind powerFault (geology)Rotor (electric)TurbineResistorChopperInduction generatorEngineeringLow voltage ride throughComputer scienceVoltageAC powerElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

This paper presents a cost-effective scheme to improve the fault ride through capability of wind turbines with doubly fed induction generators. As an alternative to using crowbar, the proposed scheme includes the stator side series-connected braking resistors, dc-link chopper and coordinated control strategy of the whole system. The proposed scheme enable the rotor converter always be connected to the system such that the DFIG will not lose controllability during fault and can almost immediately generate reactive power to support the grid after the beginning of the fault. The series-connected braking resistors can help the transient decay very fast and, at the same time, dissipate the energy of the wind turbine to reduce the rotor speed deviation during fault. Dynamic behavior of DFIG-based wind turbines during grid faults is discussed based on theoretical analysis and simulation results. It is shown that the proposed scheme can not only help the whole system ride through the fault but also reduce the stress on turbine mechanical systems.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.902
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.011
GPT teacher head0.272
Teacher spread0.262 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

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