Adaptive filter based sub-synchronous oscillation damping strategy for doubly-fed induction generators
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Bibliographic record
Abstract
To address the technical challenge that the conventional sub-synchronous oscillation (SSO) damping strategy for doubly-fed induction generator can only suppress SSO in a specific frequency band for series compensated network, this paper proposes an Adaptive Filter Based SSO Damping (AF-SSOD) strategy for Doubly-fed Induction Generators. The AF-SSOD controller consists of a filter-based SSO Damper (SSOD) suppressing module to extract and whittle down the amplitude of the dominant SSO frequency bands, a frequency identification module to obtain real-time dominant SSO frequency by Kaiser window enhanced Fast Fourier transformation (FFT) as well as a frequency locking module to update the central frequency of SSOD, achieving the high adaptability of SSO suppression under various operating conditions. The key parameters of AF-SSOD are analyzed and optimized via small signal analysis (SSA). Finally, simulation verification and comparisons are carried out, showing that AF-SSOD can effectively suppress SSO in different frequencies with satisfactory robustness and superior performance over existing SSO suppressing strategies. • AF-SSOD aims at improving the damping of the DWF+SC system in the SSO bands. • AF-SSOD consists of three modules with high adaptability of SSOs suppression. • AF-SSOD can suppress SSO in different frequencies with satisfactory robustness. • AF-SSOD shows superior performance over classical SSO suppressing strategies. • AF-SSOD, with relatively simple structure, can be easily implemented and fine-tuned.
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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 | 0.001 | 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) | 0.000 | 0.000 |
Machine scores (provisional)
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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