Standstill Frequency Response Test and Validation of a Large Hydrogenerator
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".