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Record W2139817038 · doi:10.1109/pes.2004.1373139

Determination of the transient stability boundary

2004· article· en· W2139817038 on OpenAlexfundno aff
A. G. Buddhika P. Jayasekara, U.D. Annakkage

Bibliographic record

VenueIEEE Power Engineering Society General Meeting, 2004. · 2004
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaManitoba Hydro
KeywordsBoundary (topology)Nonlinear systemTransient (computer programming)MathematicsSingular boundary methodBoundary value problemStability (learning theory)Mathematical analysisMixed boundary conditionWork (physics)Transformation (genetics)Control theory (sociology)Computer scienceApplied mathematicsBoundary element methodPhysicsArtificial intelligenceFinite element method

Abstract

fetched live from OpenAlex

This work presents an efficient method to determine the transient stability boundary. In terms of the power system variables, the required boundary is nonlinear. The method adopted in This work is to transform the original power system variables into a higher dimensional feature space using a nonlinear transformation. It has been shown that well established linear estimation methods can be used in the feature space to determine a linear boundary. This linear boundary is equivalent to a nonlinear boundary in the original power system variable space.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.007
GPT teacher head0.197
Teacher spread0.190 · 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 teacher head, 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

Citations1
Published2004
Admission routes1
Has abstractyes

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