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Record W4411446394 · doi:10.1109/tec.2025.3581237

Multi-Scale Modeling of Synchronous Machine With Constant Admittance Matrix in Phase Domain

2025· article· en· W4411446394 on OpenAlexaff
Peng Zhao, Yue Xia, Shaahin Filizadeh, Kai Strunz

Bibliographic record

VenueIEEE Transactions on Energy Conversion · 2025
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of Manitoba
FundersNational Natural Science Foundation of China
KeywordsAdmittance parametersConstant (computer programming)AdmittanceScale (ratio)Matrix (chemical analysis)Frequency domainPhase (matter)Domain (mathematical analysis)Computer scienceControl theory (sociology)MathematicsPhysicsMathematical analysisEngineeringVoltageElectrical impedanceElectrical engineeringMaterials scienceArtificial intelligenceControl (management)

Abstract

fetched live from OpenAlex

Synchronous machines form the principal source of electrical power in power systems. Modeling of the synchronous machines for transient analysis has always been an active topic of research. In this paper, a novel wound-field three-phase synchronous machine model is developed for the accurate and efficient simulation of multi-scale transients. The machine stator equations are expressed with analytic signals in the phase domain, thus providing direct interface between machine and external network models. Frequency shifting is applied to stator quantities to eliminate the ac carrier in the stator windings which enables the use of large time-step size. An artificial damper winding is introduced to eliminate the numerical saliency. To provide accurate and stable solutions with multiple time-step sizes, the artificial winding parameters setting algorithm is established. The proposed machine model is expressed in terms of a Norton equivalent with constant admittance matrix without introduction of prediction of any electrical quantity. The update of the admittance matrix at each time-step is avoided. The analysis of test cases demonstrates the effectiveness of the proposed multiscale synchronous machine model and the artificial winding parameters setting algorithm.

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 score0.908
Threshold uncertainty score0.562

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 studies0.0000.000
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 head0.006
GPT teacher head0.219
Teacher spread0.213 · 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
Published2025
Admission routes1
Has abstractyes

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