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Record W2345204546 · doi:10.1109/tpwrs.2015.2496302

Post-Disturbance Transient Stability Status Prediction Using Synchrophasor Measurements

2015· article· en· W2345204546 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

VenueIEEE Transactions on Power Systems · 2015
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTransient (computer programming)Disturbance (geology)Control theory (sociology)Electric power systemVoltageStability (learning theory)EngineeringRotor (electric)Power (physics)Computer sciencePhysicsElectrical engineering

Abstract

fetched live from OpenAlex

This paper presents a novel method to early predict the transient stability status of a power system after being subjected to a severe disturbance. The proposed technique is based on rate of change of voltage vs. voltage deviation (ROCOV-ΔV) characteristics of the post-disturbance voltage magnitudes obtained from synchrophasor measurements. Converging and diverging nature of the post-disturbance trajectories on ROCOV-ΔV plane is used to recognize the transient stability status. The proposed technique is computationally simple and fast compared to the rotor angle based transient stability prediction methods. Offline simulations and real-time experimental studies carried out for the IEEE 39-bus test system showed over 99% overall success rate under symmetrical and asymmetrical faults as well as changes in pre-disturbance conditions and network topology changes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.054
GPT teacher head0.243
Teacher spread0.189 · 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