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Record W1973933961 · doi:10.1109/psamp.2006.285397

Impact of Shunt-FACTS on Distance Protection of Transmission Lines

2006· article· en· W1973933961 on OpenAlexaff
Fadhel A. Albasri, T.S. Sidhu, Rajiv K. Varma

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsWestern University
Fundersnot available
KeywordsShunt (medical)RelayControl theory (sociology)Transmission lineElectric power transmissionProtective relayTransmission systemComputer scienceVoltageTransmission (telecommunications)EngineeringElectronic engineeringElectrical engineeringControl (management)Telecommunications

Abstract

fetched live from OpenAlex

This paper presents the performance of distance protection of transmission lines when compensated with shunt flexible AC transmission system (FACTS) controllers/devices. The performance of distance protection is evaluated for shunt-FACTS controllers applied for mid-point voltage control. The impact of two types of shunt FACTS controllers, static VAr compensators (SVC) and static synchronous compensators (STATCOM) on the transmission line distance protection are studied for different fault types, fault locations and system conditions. The dynamics of the shunt-FACTS controllers with their associated control systems are considered and simulated using RSCAD/RTDS testing environment. The performance of both the basic/non-pilot distance scheme and a directional comparison blocking (DCB) scheme are evaluated in this paper. The results of the commercial relay testing show the adverse effects of mid-point shunt-FACTS compensation of transmission line on both non-pilot and DCB distance protection schemes

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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

Citations31
Published2006
Admission routes1
Has abstractyes

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