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Stability Augmentation of a Fixed Speed Wind Generator by Using VSWT-PMSG

2014· article· en· W2059232708 on OpenAlexvenueno aff
Zinat Tasneem, M.R.I. Sheikh, A. N. Pinky

Bibliographic record

VenueJournal of Technology Innovations in Renewable Energy · 2014
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsnot available
Fundersnot available
KeywordsControl theory (sociology)Permanent magnet synchronous generatorStability (learning theory)Generator (circuit theory)Computer sciencePhysicsPower (physics)ThermodynamicsControl (management)

Abstract

fetched live from OpenAlex

This paper proposes an optimized model of a variable speed wind turbine equipped with permanent magnet synchronous generator (VSWT-PMSG) which also has been used for the stability augmentation of a wind farm including fixed speed wind generators, like Induction generator (IG). An effective control strategy with two-level IGBT converter-inverter set along with DC link capacitor and maximum power point tracking (MPPT) system assures the real power exchange to the grid and also a perfect reactive power compensation that maintains the grid side voltage constant. Moreover, it is shown that the proposed model can enhance the stability of a conventional IG based wind farm when used in combination with PMSG. Thus it eliminates the need of external controlling devices and makes the system simple and cost effective. A comparison for the stability augmentation capability between IG and PMSG has been explained. Both the dynamic and transient analyses of the proposed system have been carried out by using the laboratory standard power system software package, PSCAD/EMTDC.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.011
GPT teacher head0.222
Teacher spread0.210 · 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 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

Citations1
Published2014
Admission routes1
Has abstractyes

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