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Record W1965346904 · doi:10.1049/iet-gtd.2010.0229

Suitability analysis of practical directional algorithms for use in directional comparison bus protection based on IEC61850 process bus

2011· article· en· W1965346904 on OpenAlexaff
Mohammad R. Dadash Zadeh, T.S. Sidhu, A. Klimek

Bibliographic record

VenueIET Generation Transmission & Distribution · 2011
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsPowertech Labs (Canada)Western University
Fundersnot available
KeywordsProcess (computing)Local busFault (geology)Circuit breakerMATLABSlack busComputer scienceCAN busBus networkSystem busControl busVoltageEngineeringEmbedded systemElectrical engineeringComputer hardwarePower-flow studyAC power

Abstract

fetched live from OpenAlex

A directional comparison bus protection can provide a high-speed bus fault clearing in an IEC61850 process-bus environment. This technique is based on fault direction for each circuit connected to the protected bus. Compared to biased current differential protection, the loss of accurate time synchronisation of the individual merging units does not cause the bus protection based on directional comparison to lose security. The suitability of various practical directional techniques is investigated from the viewpoint of directional comparison bus protection for an IEC61850 process bus. A modification in the superimposed directional algorithm for bus protection is proposed to overcome the major problems resulted from breaker operations. As a part of this modification, a new technique is proposed to determine the bus voltage from feeder voltages to avoid the need for an additional three-phase CVT on the bus. PSCAD/EMTDC and MATLAB are utilised to simulate the power system and various directional algorithms, respectively. Results are reported and compared.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.319
Teacher spread0.222 · 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

Citations19
Published2011
Admission routes1
Has abstractyes

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