Multiple model multiple-input multiple-output predictive control for variable speed variable pitch wind energy conversion systems
Why this work is in the frame
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Bibliographic record
Abstract
A multivariable control strategy based on model predictive control techniques for the control of variable-speed variable pitch wind energy conversion systems (WECSs) in the above-rated wind speed zone is proposed. Pitch angle and generator torque are controlled simultaneously to provide optimal regulation of the generated power and the generator speed while minimising torsional torque fluctuations in the drive train and pitch actuator activity. This has the effect of improving the power quality of the electrical power generated by the WECS and increasing the life time of the mechanical parts of the system. Furthermore, safe and acceptable operation of the system is guaranteed by incorporating most of the constraints on the physical variables of the WECS in the controller design. In order to cope with the non-linearity in the WECS and the continuous variation in the operating point, a multiple model predictive controller is suggested to provide near optimal performance within the whole operating region.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 it