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Record W1989056965 · doi:10.1109/tsg.2013.2242498

Identification of Critical Components for Voltage Stability Assessment Using Channel Components Transform

2013· article· en· W1989056965 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 Smart Grid · 2013
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhasorElectric power systemIdentification (biology)VoltageChannel (broadcasting)Stability (learning theory)EngineeringComputer scienceElectronic engineeringComponent (thermodynamics)Control theory (sociology)Power (physics)Control engineeringReliability engineeringElectrical engineering

Abstract

fetched live from OpenAlex

Channel Components Transform (CCT) is a recently developed technique to decouple interconnected power networks. This paper aims to further explore the CCT and extend its applications. Methods and algorithms are proposed to extend its application in identifying the critical generators and branches of a network from the voltage stability perspective. The proposed methods are verified by case studies conducted on multiple test systems. This paper also demonstrates the capability of the CCT to work properly when a limited number of phasor measurement units are available. For this purpose, a strategy is proposed to determine the number and location of PMU installations that are sufficient to track the modes of voltage collapse and associated critical components. The proposed allocation strategy is examined through case studies of an actual power system.

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: none
Teacher disagreement score0.790
Threshold uncertainty score0.822

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 head0.043
GPT teacher head0.283
Teacher spread0.241 · 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