Parametric Regression Applied for Determination of Electrical Parameters of Synchronous and Induction Generators Operating in Parallel on the Electrical Energy Repowering System
Bibliographic record
Abstract
The purpose of this work is to determine the values of electrical parameters of synchronous and induction machines to validate electrical interactions between an induction generator and a synchronous generator. The generators are connected in two ways: (i) isolated from the common bus and (ii) parallel to the common bus in steady state, subject to nonlinear load. They are old and refurbished machines; thus, the parametric regression methodology is used to determine the electrical parameter values. After the computational model validation, analyses are performed by various system configurations to confirm the repowering and to analyze the system harmonic current flow. The results obtained comparing the computer simulation and experimental tests prove that the validated model represents the real system. With an experimentally validated computational model, it is possible to verify the occurrence of system repowering and the increased value of harmonic distortions in the induction generator terminals, acting as a preferential path for harmonic currents.
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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".