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Record W2356101117

An overview of setting method of under voltage load shedding

2012· article· en· W2356101117 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePower System Protection and Control · 2012
Typearticle
Languageen
FieldEngineering
TopicSmart Grid and Power Systems
Canadian institutionsnot available
Fundersnot available
KeywordsLoad SheddingScheme (mathematics)Transient (computer programming)Electric power systemVoltageKey (lock)Power (physics)Computer scienceReliability engineeringEngineeringControl (management)Control theory (sociology)Control engineeringOperations researchElectrical engineeringMathematicsComputer security
DOInot available

Abstract

fetched live from OpenAlex

Under voltage load shedding is considered as the most economic and efficient emergent control for transient voltage collapse,and is applied to power system as the last defense.In this paper,typical design methods of UVLS in different power grids of America,Canada,and Japan are overviewed,including motivation of applications,principles of design,setting methods and typical parameters of UVLS.UVLS schemes of several provinces in China are also introduced.As two kinds of major design schemes,difference between decentralized scheme and centralized scheme is compared thoroughly.Based on above materials,we analyze the key factors and general principles which should be taken into consideration during designing UVLS scheme,which may be referred by power system planners and operators.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.971
Threshold uncertainty score0.505

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 head0.021
GPT teacher head0.269
Teacher spread0.248 · 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