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Record W4254077127 · doi:10.32920/ryerson.14653236.v1

Improved Low Voltage Ride Through Capability of Wind Farm using STATCOM

2021· preprint· en· W4254077127 on OpenAlexaff
Miad Mohaghegh Montazeri

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCrowbarLow voltage ride throughWind powerInduction generatorFault (geology)TurbineControl theory (sociology)ConvertersAC powerGridRotor (electric)VoltagePower (physics)Automotive engineeringElectrical engineeringEngineeringComputer sciencePhysicsControl (management)MathematicsAerospace engineering

Abstract

fetched live from OpenAlex

Using power electronic converters with reduced capacity in doubly-fed induction generator (DFIG) based wind turbines make them vulnerable to over-current during grid disturbances. This thesis aims to analyze the behaviour of doubly-fed induction generators based wind farm for various timing schemes of crowbar deactivation and resumption of rotor side converter (RSC) in the case of grid fault. Also, usage of a static synchronous compensator (STATCOM) for the purpose of stabilizing the grid voltage after a three-phase fault is studied in this these. Moreover, finding minimum capacity of STATCOM which ensures low-voltage ride through (LVRT) of wind farm is studied. Finally, coordination of reactive power from wind turbine generators and STATCOM in steady-state condition is performed. All the results in this thesis show that STATCOM improves low voltage ride through (LVRT) capability of wind farm and assists for an uninterrupted operation of wind turbine generators during grid faults.

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 score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.236
Teacher spread0.219 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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