Low voltage ride through capability enhancement of wind turbine generator system during network disturbance
Bibliographic record
Abstract
The energy capacitor system (ECS), composed of power electronic devices and electric double layer capacitor to enhance the low voltage ride through (LVRT) capability of fixed speed wind turbine generator system (WTGS) during network disturbance, is discussed. Control scheme of ECS is based on a sinusoidal pulse width modulation voltage source converter and DC–DC buck/boost converter composed of insulated gate bipolar transistors. Two-mass drive train model of WTGS is adopted because the drive train system modelling has great influence on the characteristics of wind generator system during network fault. Extensive analysis of symmetrical fault is performed with different voltage dip magnitudes and different time durations. Permanent fault because of unsuccessful reclosing is also analysed, which is one of the salient features of this study. A real grid code defined in the power system is considered and LVRT characteristic of WTGS is analysed. Finally, it is concluded that ECS (20 MW) can significantly enhance the LVRT capability of grid connected WTGS (50 MW) during network disturbance, where simulations have been carried out by using PSCAD/EMTDC.
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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 | 0.000 | 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) | 0.001 | 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".