Modulated Predictive Current Control of PMSG-Based Wind Energy Systems
Bibliographic record
Abstract
This paper presents an efficient modulated model predictive current control for direct driven wind energy system composed of surface-mounted permanent magnet synchronous generator and back-to-back connected voltage source converter. The proposed control method fulfils the generator-side control requirements such as maximum power point tracking, and grid-side control objectives such as DC-link voltage control and power factor correction. These objectives are achieved through the regulation of generator and grid currents with fast transient response, smooth steady-state and fixed switching frequency operation simultaneously. The proposed controller predicts the future behavior of generator and grid currents using quasi-exact discrete-time models and eight voltage vectors, and then evaluates them by two independent cost functions. Finally, the switching sequence is designed by the space vector modulation using three stationary voltage vectors corresponding to the optimal cost function. The performance of the proposed method is validated through the MATLAB simulations using a 750-kW wind energy system at different wind speeds and grid reactive powers.
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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".