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Record W1982012763 · doi:10.1109/tpwrd.2012.2225848

Communication-Aided High-Speed Adaptive Single-Phase Reclosing

2012· article· en· W1982012763 on OpenAlexaff
Mohammad R. Dadash Zadeh, R. Rubeena

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2012
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsWestern University
Fundersnot available
KeywordsTransmission lineTransient (computer programming)Electronic engineeringVoltageElectric power transmissionControl theory (sociology)EngineeringShunt (medical)Line (geometry)Sensitivity (control systems)GroundComputer scienceElectrical engineeringMathematics

Abstract

fetched live from OpenAlex

A new communication-aided high-speed single-phase reclosing algorithm is proposed in this paper for transposed transmission lines based on predicted and measured voltage of faulted phase. Analytical analysis based on the distributed line model is performed to derive an equation which can be used to predict the faulted phase voltage after arc extinction in case of transient faults. Error analysis is performed to determine the sensitivity of the predicted voltage to various sources of error. The performance of the proposed technique is verified for a 500-kV transmission line with and without shunt reactor and with different grounding options for several cases simulated in PSCAD/EMTDC which include detailed arc, voltage, and current transducer models and different possible errors in measurement and transmission-line parameters.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.024
GPT teacher head0.241
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

Citations63
Published2012
Admission routes1
Has abstractyes

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