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Record W2152600223 · doi:10.14355/ijes.2013.0305.02

Design of a Control System for Active and Reactive Power Control of a Small Grid- Connected Wind Turbine

2013· article· en· W2152600223 on OpenAlexaff
Md. Alimuzzaman

Bibliographic record

VenueInternational Journal of Energy Science · 2013
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAC powerTurbineWind powerGridControl (management)Power gridPower (physics)EngineeringControl theory (sociology)Marine engineeringComputer scienceElectrical engineeringMathematicsPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

Reactive power flow between a wind turbine system and the \ngrid is an important issue especially when the wind turbine is connected to a remote grid. In this research, a control system has been developed that allows wind turbine to provide reactive power to the local load connected between the grid and the wind turbine. The supplied reactive power from the wind turbine is controlled by changing the phase angle of Pulse Width Modulation (PWM) in the wind turbine inverter. A proportional controller is used to maintain the reactive power supplied by the wind turbine. Another PI controller is used to maintain the wind turbine operation at an optimum tip speed ratio (TSR) to extract maximum power from the wind. The proposed system along with all sub‐systems has been modelled and simulated in Matlab/ Simulink. The simulation results confirm that the \ndesigned system is able to control the wind turbine and \ncapable of providing the required reactive power. Results \nshow that the designed system is able to maintain the system power factor close to unity for a range of wind speeds.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.203
Teacher spread0.195 · 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 designBench or experimental
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

Citations2
Published2013
Admission routes1
Has abstractyes

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