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Record W2407363875 · doi:10.1109/ever.2016.7476363

Modeling and control of a Wind Energy Conversion System based on DFIG driven by a Matrix Converter

2016· article· en· W2407363875 on OpenAlexaff
Bekhada Hamane, Mamadou Doumbia, Mohamed Bouhamida, Hicham Chaoui, Mustapha Benghanem

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsControl theory (sociology)StatorWind powerVector controlInduction generatorMATLABRotor (electric)Controller (irrigation)Transient (computer programming)AC powerDoubly fed electric machineWind speedPower (physics)EngineeringComputer scienceVoltageInduction motorControl (management)PhysicsElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents the control study of a variable speed Wind Energy Conversion System (WECS) based on the Doubly Fed Induction Generator (DFIG). The generator is connected directly to grid by its stator and fed by a Matrix Converter (MC) at its wound rotor. The indirect vector control is adopted. The stator flux is oriented for controlling the power and current, which are regulated by PI controller via the pole placement technique, and the Venturini Modulation Method (VMM) is applied to control the MC. The performance of the whole system is verified by Matlab/Simulink simulation. Results in transient and steady-state regimes are presented to validate the effectiveness of the proposed wind conversion system. Results confirm the high performance of the control strategy adopted in the wind power generation system based on a DFIG powered by a MC.

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.

How this classification was reachedexpand

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: none
Teacher disagreement score0.868
Threshold uncertainty score0.468

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 head0.003
GPT teacher head0.163
Teacher spread0.160 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2016
Admission routes1
Has abstractyes

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