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Record W2115166720 · doi:10.1109/tpwrd.2013.2253497

A Saturation Suppression Approach for the Current Transformer—Part II: Performance Evaluation

2013· article· en· W2115166720 on OpenAlexaff
Mahdi Davarpanah, Majid Sanaye‐Pasand, Reza Iravani

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2013
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsResistorRelayTransformerCurrent transformerDigital controlEngineeringElectronic engineeringReal Time Digital SimulatorProtective relayVoltageElectric power systemControl engineeringComputer scienceElectrical engineeringControl theory (sociology)Control (management)Power (physics)

Abstract

fetched live from OpenAlex

Part I of this two-part paper introduces a hardware-based mechanism to prevent/suppress the saturation phenomenon of the current transformer (CT). The mechanism includes an electronically switched resistor which is in series with the CT secondary winding. Part II performs a set of 1) offline digital time-domain simulation studies in the PSCAD/EMTDC environment and 2) control-hardware-in-the-loop (CHIL) test cases in a real-time digital simulation platform, to demonstrate technical feasibility of the proposed approach. The investigations also report the effect of CT saturation and the proposed desaturation mechanism on a digital distance relay. The digital algorithms of the relay and the control of the electronic switch are implemented in two NI-CRIO platforms for the CHIL studies. The investigation results demonstrate and verify the effectiveness of the proposed CT desaturation mechanism.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.237
Teacher spread0.217 · 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 designSimulation or modeling
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

Citations27
Published2013
Admission routes1
Has abstractyes

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