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Record W2171630433 · doi:10.1109/tpwrd.2009.2028818

Analysis and Suppression of the Coupling Capacitor Voltage Transformer Ferroresonance Phenomenon

2009· article· en· W2171630433 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.

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2009
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFerroresonance in electricity networksTransformerOvervoltageSnubberControl theory (sociology)CapacitorEngineeringElectrical engineeringVoltageEddy currentElectronic engineeringComputer science

Abstract

fetched live from OpenAlex

This paper provides a detailed core model for the step-down transformer (SDT) of the coupling capacitor voltage transformer (CCVT) to investigate the CCVT transients and ferroresonance behavior. The core model represents hysteresis symmetric and asymmetric minor loops, remnant flux, and the eddy current effects. Based on the developed model, the impacts of passive and active ferroresonance suppression circuits (PFSC and AFSC) and overvoltage protection devices (OPDs) for fast suppression of the CCVT ferroresonance phenomenon are also studied. This paper also presents a generalized methodology to select the AFSC parameters. The simulation results, in the PSCAD/EMTDC environment, indicate that the hysteresis and eddy current effects of the SDT core significantly influence the CCVT ferroresonance behavior. The study results also show that: 1) in both the presence and the absence of arresters and spark gaps, the AFSC can mitigate the phenomenon faster than the PFSC, i.e., in about two cycles and 2) the output fidelity of the AFSC-based CCVT is less dependent on the burden as compared with that of the PFSC.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.590

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)0.0010.000

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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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