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Record W2786847606 · doi:10.1109/epec.2017.8286145

Demonstration of voltage stability by comparing dynamic simulations and quasi steady state analysis

2017· article· en· W2786847606 on OpenAlexaff
Sarin Y. S. Rajapakse, U.D. Annakkage

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAdmittanceSteady state (chemistry)Control theory (sociology)VoltageSteady State theoryStability (learning theory)Power (physics)Computer scienceElectric power systemMechanicsEngineeringPhysicsElectrical impedanceElectrical engineeringThermodynamicsControl (management)

Abstract

fetched live from OpenAlex

In this paper, Power-Voltage Curves obtained from quasi steady state analysis is used to demonstrate the concept of voltage stability. This method is shown to be applicable to analyze the voltage stability when the load consists of constant admittance as well as dynamic induction motor loads. The results obtained from quasi steady state analysis is compared with the results of detailed real time simulations. As expected, the paper confirms that quasi steady state analysis can be used to predict the voltage collapse point of radial power systems with reasonable accuracy even when the loads consist of dynamic loads. The simulations and analysis programs developed in the research can be used as teaching tools.

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 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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.255
Teacher spread0.238 · 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 teacher head, 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
Published2017
Admission routes1
Has abstractyes

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