Real-Time Implementation of a Novel Vector Control Strategy for a Self-Excited Asynchronous Generator Driven by a Wind Turbine
Bibliographic record
Abstract
This paper proposes a novel idea to governing wind power conversion plants supplying DC loads characterizing an isolated site based on self-excited squirrel-cage induction generators (IG). In this wind power converting application, the induction generator produces an active power from the mechanical power provided by a wind-turbine to variable DC loads through a static converter with an output capacitor under constant voltage levels. For this reason, A specific vector control technique has been developed for controlling the induction machine in an analogous manner with a separated DC machine case. Thus, in order to satisfy the active power demand characterizing a variable DC load at a given rotor mechanical speed, the corresponding control laws are performed in steady-state conditions from a new control variable introduction defined by the ratio of the desired output DC-bus voltage square value and the rotor velocity. Computer simulations validated by experimental results demonstrate that the projected control approach including just one conventional controller ensures excellent tracking performances of the DC-bus voltage to its reference trajectory under simultaneous variations of the load-power demand and the rotor velocity profiles.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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)
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".