Synchronous Generator Parameter Estimation Using Data Collected with Machine in Closed-loop Operation
Why this work is in the frame
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Bibliographic record
Abstract
Knowledge of synchronous generator physical parameters (such as rotor inertia, inductances, etc.) is desirable for power system analysis and control. Experiments for parameter identification of a synchronous generator, multi-variable, non-linear system can be carried out only with the controllers in action. In this article, estimation of the physical parameters of such systems is investigated using data collected from the machine in closed-loop operation. To obtain good accuracy of parameter estimates, both discrete and continuous-time model structures have been considered. Continuous-time generalized Poisson moment functional method has proven to be very effective. Results of simulation studies with the machine in closed-loop operation show the effectiveness of this approach. Monte Carlo simulations are also used to show the low variance of the estimates in a noisy environment.
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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 it