Enhanced Control of Wind Energy Conversion System Based on DFIG Using Adaptive Super Twisting Controllers
Bibliographic record
Abstract
In the control of Wind Energy System (WES), the most serious disturbances to occur are the variations of wind speed which can affect the quality and continuity of the generated power. In this research paper, an enhanced control strategy is proposed for a wind turbine (WT) system equipped with a Doubly Fed Induction Generator (DFIG) connected to the grid network. The proposed strategy design is based on an amended formula of the Super Twisting Control with adaptive gains that can be implemented to the cascaded system scheme comprising the speed and power control loops. This method is effective in reducing and smoothing the control effort by developing a simple formulation of sliding gain despite disturbance regarding variation on the parameters, and the random nature of wind speed. By comparison with the conventional Super Twisting Control, simulation results are given to illustrate the improvements of the use of adaptive Super Twisting Control based controllers in a WES Control.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".