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Record W2071252864 · doi:10.1109/icelmach.2014.6960157

An efficient model of synchronous generator for hydraulic power plant dynamic simulations

2014· article· en· W2071252864 on OpenAlexaff
J. W. Tsotie, R. Wamkeue

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsStatorControl theory (sociology)Permanent magnet synchronous generatorVoltage regulatorVoltageEngineeringLoad rejectionElectric power systemMATLABElectric generatorHydroelectricityPower (physics)Computer scienceElectrical engineeringPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

The paper is concerned with practical modelling of the synchronous generator (SG) as the main component of the hydroelectric power plant. The generation system under study comprises the hydraulic circuit, the speed regulator, the excitation system and the SG. Each system component is formatted into state form. The SG state model developed with field voltage as the only controlled input variable and with stator currents, field currents and stator voltages as output observed variables, includes both the saturation phenomenon and the mechanical motion. The resulting flexible SG model connected to other power plant components allows predicting various tests such as: the classical three-phase sudden short-circuit test, the field short-circuit test with the stator in open circuit and the load rejection and line-switching tests. In order to prove the effectiveness of the proposed power plant modeling framework, extensive simulations using the Matlab/Simulink program are performed and discussed for different tests and plant scenarios (automatic voltage regulator (AVR) on and off).

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.798
Threshold uncertainty score0.311

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 head0.008
GPT teacher head0.219
Teacher spread0.212 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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