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Record W2109822621 · doi:10.1109/tec.2006.889621

Adaptive Distance Relay Setting for Lines Connecting Wind Farms

2007· article· en· W2109822621 on OpenAlexaff
Ashok Kumar Pradhan, G�za Jo�s

Bibliographic record

VenueIEEE Transactions on Energy Conversion · 2007
Typearticle
Languageen
FieldEngineering
TopicPower Systems Fault Detection
Canadian institutionsMcGill University
Fundersnot available
KeywordsRelayWind powerGridWind speedLine (geometry)VoltageElectrical engineeringPower (physics)Boundary (topology)Protective relayElectric power systemTopology (electrical circuits)Computer scienceControl theory (sociology)EngineeringMathematicsMeteorologyPhysicsGeometryArtificial intelligence

Abstract

fetched live from OpenAlex

Wind speed varies continuously throughout a day resulting in fluctuating wind farm output power. When such a farm is connected to the grid through a line, the transmitted power and the relay end voltage (with respect to grid voltage) fluctuate continuously. In this paper, the protection of such a line with distance relay is investigated. The ideal trip characteristic for distance relay is studied with change in conditions of the wind farm. A method is proposed to set the boundary adaptively using local information only.

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)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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

Citations186
Published2007
Admission routes1
Has abstractyes

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