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Record W2115081651 · doi:10.1109/tec.2006.874244

Wind-Driven Self-Excited Induction Generator With Voltage and Frequency Regulated by a Reduced-Rating Voltage Source Inverter

2006· article· en· W2115081651 on OpenAlexaff
Luiz A. C. Lopes, Rogério Gaspar de Almeida

Bibliographic record

VenueIEEE Transactions on Energy Conversion · 2006
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsInduction generatorVoltageWind powerControl theory (sociology)Automatic frequency controlEngineeringVoltage regulationInverterAC powerElectrical engineeringComputer scienceControl (management)

Abstract

fetched live from OpenAlex

This paper discusses the regulation of the voltage and frequency of a stand-alone fixed-pitch wind energy conversion system (WECS) based on a self-excited squirrel-cage induction machine. A shunt connected voltage source inverter (VSI) and a controllable dump load are used for regulation purposes. A battery bank is included in the dc side of the VSI so that it can absorb and inject active power thus increasing the efficiency and availability of the system. A control scheme for the VSI with independent control of active and reactive power allows the state of charge of the batteries to be kept in a safe range while maximizing the voltage regulating capabilities of the VSI. The characteristics of the wind turbine, self-excited generator, and the ratings of the VSI are considered in order to determine the load range for which voltage and frequency can be regulated for a given wind speed range. The feasibility of the proposed system is verified by simulations.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.004
GPT teacher head0.158
Teacher spread0.154 · 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

Citations132
Published2006
Admission routes1
Has abstractyes

Explore more

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