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Record W2133309654

An accelerated zone 2 trip algorithm for non-pilot distance relays

2007· article· en· W2133309654 on OpenAlexaff
G. Rosas-Ortiz, T.S. Sidhu

Bibliographic record

Venueinternational conference on Modelling and simulation · 2007
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsWestern University
Fundersnot available
KeywordsBackupRelayComputer scienceTerminal (telecommunication)AlgorithmFault (geology)Circuit breakerProtective relayReal-time computingChannel (broadcasting)Real Time Digital SimulatorDigital signal processingEngineeringComputer hardwareElectrical engineeringElectric power systemTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

This paper presents an algorithm able to accelerate the zone 2 trip of non-pilot distance relays by detecting remote breaker operation following a zone 2 fault. It is based on monitoring changes in proposed composite signals. The performance of the proposed algorithm was extensively evaluated using dynamic simulations in an electromagnetic transients program EMTDC/PSCAD. Also, a real-time implementation of the proposed algorithm was done using a real time digital simulator RTDS and general purpose DSP hardware. Simulation results show that the performance of the proposed technique was superior to other techniques in literature for three terminal lines, while it performs similar to other techniques for two terminal lines. It is proposed this algorithm can be used as a fast backup protection scheme for two and three terminal lines when communication channel fails or is not available.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
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)0.0040.001

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 head0.067
GPT teacher head0.323
Teacher spread0.256 · 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
GenreMethods

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

Citations0
Published2007
Admission routes1
Has abstractyes

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