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Record W4310908178 · doi:10.18280/jesa.550502

Energy Transfer from an Electrical Network-Connected Synchronous Machine

2022· article· en· W4310908178 on OpenAlexvenueno aff
Inchirah Sari-Ali, Bachir Chikh-Bled, Omolayo M. Ikumapayi, Zahira Dib, Giulio Lorenzini, Younes Menni

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2022
Typearticle
Languageen
FieldEngineering
TopicPower System Optimization and Stability
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceElectric power systemMaximum power transfer theoremSynchronous motorPermanent magnet synchronous generatorElectric powerElectricityElectromagnetic coilPower (physics)Electrical engineeringVoltageEngineeringPhysics

Abstract

fetched live from OpenAlex

Any alternating electric power supply is always characterized by three reference quantities, which are voltage, electric power and frequency. The generators of power stations are synchronous machines. The present work is based on the modelling of the synchronous machine for a study of the stability of the electricity transmission network. The example considered is a thermal power station of the national network. i.e., Algiers port power station. We have developed a computer program based on MATLAB to simulate the calculations of our multi-variable system. The study presented in this article examines the static stability of a thermal power plant. To make this study a reality, it is necessary to model the synchronous machine. We present the three models of the synchronous machine by emphasizing the role of the shock absorbers and the smoothness of the model with three windings. This work is supported by a spectral analysis based on the eigenvalues of the system.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.724
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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.

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
Published2022
Admission routes1
Has abstractyes

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