MétaCan
Menu
Back to cohort
Record W1968694443 · doi:10.1049/iet-gtd.2012.0498

Identification and location of long‐term voltage instability based on branch equivalent

2013· article· en· W1968694443 on OpenAlexaff
Juan Yu, Wenyuan Li, Venkataramana Ajjarapu, Wei Yan, Xia Zhao

Bibliographic record

VenueIET Generation Transmission & Distribution · 2013
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsBC Hydro (Canada)
FundersNational Natural Science Foundation of China
KeywordsIdentification (biology)Term (time)InstabilityComputer scienceControl theory (sociology)PhysicsMechanicsBiologyArtificial intelligenceBotany

Abstract

fetched live from OpenAlex

A new branch equivalent is proposed to identify and locate long‐term voltage instability in both distribution and transmission network. In the proposed equivalent, not only the power flow and the sensitivity information remain consistent before and after the equivalence, but also the equivalent voltages and admittances are completely independent of loads, which ensure the equivalent accuracy in voltage stability analysis. Based on the proposed equivalent, an approach is presented to identify system voltage stability. The proposed approach also locates weak branches and buses, where an enhancement or operational measure can be used to improve system voltage stability. The effectiveness of the proposed equivalent and approach is demonstrated using two radial systems, five IEEE systems and four actual utility systems with a system size from 5‐buses to 3120‐buses.

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)0.000
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.014
GPT teacher head0.228
Teacher spread0.215 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueIET Generation Transmission & DistributionSame topicPower System Optimization and StabilityFrench-language works237,207