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Record W2097060502 · doi:10.1109/pes.2007.386230

Mitigation of Adverse Effects of Midpoint Shunt- FACTS Compensated Transmission Lines on Distance Protection Schemes

2007· article· en· W2097060502 on OpenAlexaff
Fadhel A. Albasri, T.S. Sidhu, Rajiv K. Varma

Bibliographic record

VenueIEEE Power Engineering Society General Meeting · 2007
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsWestern University
Fundersnot available
KeywordsMidpointStatic VAR compensatorShunt (medical)Transmission lineComputer scienceElectric power transmissionControl theory (sociology)Real Time Digital SimulatorTransmission (telecommunications)VoltageElectronic engineeringElectrical engineeringEngineeringElectric power systemAC powerTelecommunicationsControl (management)Mathematics

Abstract

fetched live from OpenAlex

This paper presents practical solutions to mitigate the adverse effects on distance protection schemes when they are used to protect transmission networks that are compensated by shunt connected flexible AC transmission system (FACTS) controllers/devices. Two types of shunt-FACTS devices, static var compensator (SVC) and static synchronous compensator (STATCOM), are considered and designed to regulate the midpoint voltage of the transmission line. The mitigation techniques are implemented in commercial relays and tested using real time digital simulator (RTDS). The results show the effectiveness of the proposed modifications to the channel aided distance protection schemes under various faults and varying operating conditions.

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)0.0010.000
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 head0.005
GPT teacher head0.208
Teacher spread0.203 · 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

Citations21
Published2007
Admission routes1
Has abstractyes

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