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Record W2042220707 · doi:10.1109/tpwrd.2015.2394464

Enhanced Phasor Estimation Technique for Fault Location in Series-Compensated Lines

2015· article· en· W2042220707 on OpenAlexafffund
Tirath Pal S. Bains, Mohammad R. Dadash Zadeh

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2015
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhasorFault (geology)Series (stratigraphy)Computer scienceElectric power systemEstimationControl theory (sociology)Fault indicatorElectric power transmissionElectronic engineeringEngineeringFault detection and isolationPower (physics)Electrical engineeringPhysicsArtificial intelligenceActuator

Abstract

fetched live from OpenAlex

Accurate phasor-based fault location in series capacitor-compensated transmission lines is a challenging task due to the presence of subsynchronous frequency components in the measured voltage and current signals. In this letter, an enhanced technique is proposed based on Prony analysis and discrete Fourier transform to accurately estimate voltage and current phasors for the purpose of offline fault location. A comprehensive simulation and fault-location analysis is performed using PSCAD and Matlab to establish the successful application of the proposed technique to the fault location.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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

Citations25
Published2015
Admission routes2
Has abstractyes

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