Simulation of a wind turbine with doubly-fed induction generator by FAST and Simulink
Bibliographic record
Abstract
In order to fully study the electrical, mechanical and aerodynamic aspects of a wind turbine with a doubly-fed induction generator (DFIG), a detailed model that considers all these aspects must be used. A drawback of many works in the area of wind turbine simulation is that either a very simple mechanical model is used with a detailed electrical model, or vice versa. Hence the effects of interactions between electrical, and mechanical components are not accurately taken into account. In this paper, three simulation programs-TurbSim, FAST, and Simulink- are used to model the wind, mechanical and electrical parts of a wind turbine and its controllers. Simulation results obtained from the model are used to observe the interaction of all three factors affecting the operation of a wind turbine system. For example, it is shown how an electrical disturbance can cause dangerous tower vibrations under high speed and turbulent wind conditions, which may not be feasible using a simple model of the wind and wind turbine.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".