A Tap-Changing Algorithm for the Implementation of “Sen” Transformer
Bibliographic record
Abstract
The "Sen" transformer (ST) is made out of a transformer and tap changers and is capable of regulating the active and the reactive power flow selectively in an electric transmission line. This paper focuses on the development of a novel algorithm capable of selecting the best combination of tap-settings for the compensating windings of the ST. Digital simulation model of the ST including a detailed tap-changer model has been developed in the PSCAD/EMTDC software package. The tap-changing algorithm of the ST has been implemented through a FORTRAN code that is interfaced with the rest of the model. Should there be any change in the magnitude of the compensating voltage and its phase angle, the tap-positions are readjusted accordingly. The results obtained from the simulation of the ST are compared with the simulation results of the UPFC which is a power electronics-based power-flow controller. The comparison shows good agreement between the results and hence validates the effectiveness of the proposed algorithm and the performance of the ST.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".