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Record W2550318620 · doi:10.1109/fps.2005.204236

Online pre-analysis and real-time matching for controlled splitting of large-scale power networks

2005· article· en· W2550318620 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

Venue2005 International Conference on Future Power Systems · 2005
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsWestern University
Fundersnot available
KeywordsSynchronismScheme (mathematics)Computer scienceMatching (statistics)Power (physics)PollingElectric power systemReal-time computingComputer networkMathematics

Abstract

fetched live from OpenAlex

System splitting is that the dispatching center controls the splitting of a power network to form designed islands when loss of synchronism occurs. This paper describes and compares three possible ways to realize real-time decision-making of system splitting, and shows that online pre-analysis & real-time matching (ONPARM) is a recommendable way under current technological conditions. An ONPARM system-splitting scheme is presented, and related techniques are described. Simulations on the IEEE 118-bus system show that the scheme can meet the requirement of real-time decision-making. The scheme can be combined with existent emergency control (non-system-splitting) schemes to form a unified real-time security control scheme containing system splitting

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 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 score0.865
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.254
Teacher spread0.246 · 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