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Record W2969269043 · doi:10.5539/mas.v13n9p10

Grid-Connected Control of Wind Turbine with Differential Speed Regulation Based on Fuzzy Decision Makings

2019· article· en· W2969269043 on OpenAlexvenueno aff
Xiaoming Rui, Lubing Xie, Xiaochao Fan, Changkai Xiu

Bibliographic record

VenueModern Applied Science · 2019
Typearticle
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsnot available
Fundersnot available
KeywordsControl theory (sociology)Wind speedComputer scienceTurbineWind powerTip-speed ratioController (irrigation)Electronic speed controlGridEngineeringControl (management)Electrical engineeringMathematicsPhysics

Abstract

fetched live from OpenAlex

To solve the problem of grid-connected control of differential speed-regulating wind turbines, the wind turbine, transmission chain, speed-regulating motor, and generator model of the unit are constructed using the MATLAB/Simulink platform. The differential speed-regulating control system is designed on the basis of slip-frequency and fuzzy control theories. The speed control function and characteristics on maximum power tracing of wind turbine is tested via simulation. Meanwhile, the experimental bench for the differential speed-regulating wind power system is set up. Test results indicate that the generator speed is controlled by speed-regulating motor with output voltage and frequency that are approximately synchronized with those of power grid under idle load condition. The maximum wind-power utilization coefficient is maintained by fuzzy controller under the rated wind speed. Thus, the accuracy and efficiency of the designed control system is proven and provide important implications for further investigations on the grid-connected control of wind turbines with differential speed regulation.

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: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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