Parameter identification from SSFR tests and d-q model validation of synchronous generator
Bibliographic record
Abstract
This paper introduces a fast parameter identification technique for a two-order d-q model of a synchronous generator from Standstill Frequency Response (SSFR) tests. This identification method is based on a modified SSFR test and the curves of the no-load and sustained short-circuit tests. This allows the lowest SSFR frequency to be 0.01Hz instead of 0.001Hz. The phase and field resistances are measured from fast and precise DC tests during the SSFR test. In this work, the value of the unsaturated synchronous inductance is defined from the no-load air gap linearization and the short-circuit saturation curve. This definition fits better when the saturation is considered and we present how to implement this approach with the Matlab-Simulink SimPowerSystem standard d-q models. Validations are made using sudden short-circuit tests at nominal field current to evaluate d-q model performances with magnetic saturation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".