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Record W1998370578 · doi:10.1109/iecon.2012.6388616

Optimization of a stand-alone PMSG wind generation system

2012· article· en· W1998370578 on OpenAlexaff
Tahar Tafticht, A. Chériti

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsWind powerPermanent magnet synchronous generatorTurbineWind speedComputer scienceAutomotive engineeringControl theory (sociology)Power optimizerMaximum power point trackingEngineeringElectrical engineeringControl (management)MagnetMeteorologyVoltageAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

This paper proposes the modeling and the simulation of a stand-alone wind energy system. A permanent magnet synchronous generator (PMSG) is used as a variable speed generator in the proposed wind energy system. In order to achieve the wind turbine maximum power control across a large wide range of wind speeds, a dynamic modeling and control of the wind system with battery energy storage including wind disturbances is presented in this paper. The simulation results show that the power gain obtained clearly increases the energy production from the wind energy system.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.185
Teacher spread0.173 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

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