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Record W1900292521 · doi:10.1109/ccece.1995.528102

EMTP based study of self-excitation phenomenon in an induction generator

2002· article· en· W1900292521 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh-Voltage Power Transmission Systems
Canadian institutionsHydro-QuébecPolytechnique Montréal
Fundersnot available
KeywordsFerroresonance in electricity networksEmtpInduction generatorIslandingTransformerExcitationOvervoltageElectrical engineeringEngineeringGenerator (circuit theory)Electric power systemVoltageControl theory (sociology)Computer sciencePower (physics)PhysicsDistributed generation

Abstract

fetched live from OpenAlex

A study of the application of an induction generator in power systems, conducted under Hydro-Quebec sponsorship, is presented in this paper. The phenomenon of self-excitation is investigated using the Electromagnetic Transients Program (EMTP). The results demonstrate that, if the induction generator is sufficiently compensated, it may become self-excited when disconnected from the power grid. High overvoltages then occur which can be dangerous for the insulation integrity of the nonutility generator (NUG) equipment, the local loads and, even worse, for the maintenance personnel. Taking into account the nonlinear aspect of the transformer, simulation results also demonstrate that, after islanding, ferroresonance will occur when the generator voltage level exceeds the saturation voltage level of the transformer. The wave shapes being extremely distorted, this could cause the protective devices to respond incorrectly.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score0.403

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 head0.027
GPT teacher head0.231
Teacher spread0.204 · 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

Quick stats

Citations6
Published2002
Admission routes2
Has abstractyes

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