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Record W2018240427 · doi:10.1080/15325000902762208

Out-of-step Detection Using Energy Equilibrium Criterion in Time Domain

2009· article· en· W2018240427 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueElectric Power Components and Systems · 2009
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsRectangleEnergy (signal processing)ComputationTransient (computer programming)Time domainElectric power systemDomain (mathematical analysis)AlgorithmPower (physics)Scheme (mathematics)Computer scienceMathematicsMathematical optimizationControl theory (sociology)Artificial intelligenceGeometry

Abstract

fetched live from OpenAlex

Abstract This article introduces a new algorithm to detect the out-of-step condition in a power system based on energy equilibrium criterion in the time domain. The proposed energy equilibrium criterion is developed using the concept of equal area criterion in the power-angle domain, and it eliminates the numerical computations required to find the critical clearing time to detect the out-of-step condition. The proposed algorithm detects the out-of-step condition based on the real-time transient energy information available from the local substations. The effectiveness of the proposed algorithm is tested on a single-machine infinite-bus system, a two-machine infinite-bus system, and a three-machine infinite-bus system. The performance of the proposed algorithm is compared with an existing concentric rectangle scheme. The simulation results show that the proposed algorithm can be applied to larger systems and is faster compared to the concentric rectangle scheme.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.643

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 head0.013
GPT teacher head0.216
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