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Record W2906125261 · doi:10.1109/tpwrs.2018.2889510

Standstill Frequency Response Test and Validation of a Large Hydrogenerator

2018· article· en· W2906125261 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Power Systems · 2018
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsPolytechnique MontréalHydro-Québec
Fundersnot available
KeywordsStatorWaveformEngineeringElectromagnetic coilRotor (electric)Transient (computer programming)Control theory (sociology)SalientVoltageComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

This paper intends to contribute to the revision process of the IEEE Standard 115 by demonstrating the applicability of the standstill frequency response (SSFR) test on large salient pole hydrogenerators. The presented SSFR tests are carried out on a 55.6-MVA salient pole machine with laminated rotor, non-continuous damper windings, and a nonintegral slot number. The IEEE-115 SSFR test procedure is applied with special care to rotor positioning as well as accurate data acquisition in the low-frequency range. The maximum likelihood estimation method is utilized for machine parameter identification from the SSFR tests. Obtained parameters are compared with design values in addition to the ones obtained using traditional “sudden no-load three-phase short-circuit,” Dalton-Cameron and “open stator d-axis transient time constant” methods. The accuracy of parameters is also confirmed by comparing the measured three-phase short-circuit current waveforms with the ones obtained by simulating the SSFR-based machine models in an electromagnetic transient -type software. Unlike previous SSFR test cases on large salient pole hydrogenerators, accurate results are obtained.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.534

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 head0.013
GPT teacher head0.242
Teacher spread0.230 · 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