MétaCan
Menu
Back to cohort

Emulation of A Self-Excited Induction Generator Feeding Nonlinear Loads

2021· article· en· W3214371779 on OpenAlexaff
Yupeng Liu, Pragasen Pillay

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Turbine Control Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsEmulationInduction generatorHarmonicsNonlinear systemControl theory (sociology)Generator (circuit theory)Computer scienceElectricity generationControl engineeringEngineeringPower (physics)Electrical engineeringVoltagePhysics

Abstract

fetched live from OpenAlex

The induction generator, in particular the self-excited induction generator (SEIG) is adopted in remote areas and can work in isolated systems. In such isolated systems, there are nonlinear loads, which may inject harmonics into the SEIG systems. However, it is difficult to test the nonlinear load condition of a real SEIG system in the laboratory. In this paper, a power electronic converter-based SEIG emulator is developed to investigate the SEIG feeding nonlinear loads. The mathematical model of induction generator (IG) and emulator converter are established and verified from the SEIG emulator. The comparison of the emulation results and actual experimental results demonstrate the validity of the proposed solution.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

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 science0.0000.000
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 head0.009
GPT teacher head0.198
Teacher spread0.189 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicWind Turbine Control SystemsFrench-language works237,207