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Record W2144728297 · doi:10.1109/melcon.2006.1653253

Tools for Voltage Collapse Assessment

2006· article· en· W2144728297 on OpenAlexaff
Claudio A. Cañizares, S.K.M. Kodsi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceElectric power systemMarket clearingComputationElectricity marketElectricityMathematical optimizationVariety (cybernetics)Maximum power transfer theoremVoltagePower (physics)Reliability engineeringEngineeringEconomicsElectrical engineeringAlgorithmMathematics

Abstract

fetched live from OpenAlex

A variety of tools and techniques used for voltage stability analysis in power systems are discussed in this paper, with particular emphasis on their application to electricity markets. Thus, the computation of transfer capability limits, which are directly associated with the security constraints used in energy auction systems, by means of continuation power flows (CPF) as well as maximum loadability optimal power flows (OPF) are discussed in some detail. The paper also describes a "standard" security-constrained (SC) OPF auction, as well as two recently proposed voltage-stability-constrained (VSC) OPF-based techniques used to better represent security limits in market clearing and power dispatch techniques. A simple 6 bus example is utilized to illustrate the application of all these methodologies, and discuss and compare the various market prices, power and system security levels obtained from the different techniques, showing the advantages of the VSC-OPF techniques over the standard SC-OPF

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)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.004
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0370.013

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 head0.008
GPT teacher head0.222
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

Citations6
Published2006
Admission routes1
Has abstractyes

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