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Record W2376518237

A preventive control model for static voltage stability considering the power constraints of weak branches

2012· article· en· W2376518237 on OpenAlexaff
Wenyuan Li

Bibliographic record

VenueJournal of Chongqing University. English Edition · 2012
Typearticle
Languageen
FieldEngineering
TopicHigh-Voltage Power Transmission Systems
Canadian institutionsBC Hydro (Canada)
Fundersnot available
KeywordsControl theory (sociology)Maximum power transfer theoremAC powerCorrectnessElectric power systemPower (physics)VoltageStability (learning theory)Power flowEngineeringComputer scienceControl (management)PhysicsElectrical engineeringAlgorithm
DOInot available

Abstract

fetched live from OpenAlex

The voltage instability of power system often occurs when the active power on one or more weak branches exceeds its transfer capability.A preventive control model for static voltage stability is proposed using the active power transfer capability of weak branches as static voltage stability constraints.A local line-based voltage stability index is used to determine the critical contingencies,weak branches and transfer capability of each weak branch.A static security analysis method,which is based on DC power flow equations,is used to establish the non-linear active power flow expressions on weak branches following each critical contingency.The active power constraints on weak branches can be obtained from the active power flow expressions and transfer capabilities of weak branches.A quadratic optimal model for preventive control including the proposed active power constraints on weak branches is presented.The simulation results for IEEEE14-bus system and IEEE118-bus system demonstrate the correctness and effectiveness of the proposed preventive control model.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.202
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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Same venueJournal of Chongqing University. English EditionSame topicHigh-Voltage Power Transmission SystemsFrench-language works237,207