Analyzing subsynchronous torsional interactions in large-scale power systems in frequency domain
Bibliographic record
Abstract
This paper presents a generic technique for analyzing subsynchronous torsional interaction (SSTI) between series capacitors and multi-mass shaft system in steam turbinegenerators. The proposed method focuses on application of the method in large-scale power systems where the SSTI study is to be carried out for large number of generators, different compensation levels, and various contingencies. The proposed methodology encompasses three steps: 1) Performing a network frequency scan to identify generators that are likely to show SSTI, also called critical generators; 2) Finding local mode of critical generators to identify critical torsional modes that are likely to interact with series capacitors; 3) Using frequency of critical modes as initial guess to trace them in the full system and find associated damping. This three-step procedure reduces computational cost while minimizing possibility of missing any torsional interaction in the system. Moreover, the developed procedure highly automates the process of finding subsynchronous modes and minimizes user interaction.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".