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Record W1978639263 · doi:10.1109/ias.2014.6978503

Speed sensorless based adaptive maximum power point tracking control of IPM synchronous wind generator

2014· article· en· W1978639263 on OpenAlexaff
M. Nasir Uddin, Nirav Patel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsLakehead University
Fundersnot available
KeywordsMaximum power point trackingControl theory (sociology)Permanent magnet synchronous generatorWind speedMaximum power principleTurbineWind powerElectronic speed controlVariable speed wind turbineRotor (electric)Computer sciencePower optimizerPower (physics)Vector controlEngineeringMagnetControl (management)VoltagePhysicsElectrical engineering

Abstract

fetched live from OpenAlex

In the variable speed wind turbine, generator speed can be operated at maximum power operating points by adjusting the shaft speed optimally. This paper presents a speed sensorless based adaptive maximum power point tracking (MPPT) control of interior permanent magnet synchronous wind generator (IPMSWG). For the proposed control system a model reference adaptive system is incorporated to estimate the rotor position. Furthermore, without requiring the knowledge of wind speed, air density or turbine parameters, the MPPT algorithm generates optimum speed command for speed control loop of vector controlled machine side converter. The MPPT algorithm uses the estimated active power output of the generator as its input and generates command speed so that the maximum power is transferred to the dc-link. The performance of the proposed speed sensorless adaptive MPPT control of IPMSWG is tested in both simulation and experiment at variable wind speed conditions.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.183
Teacher spread0.176 · 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.

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

Citations1
Published2014
Admission routes1
Has abstractyes

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