Investigation of power quality and structural loads for two‐bladed wind turbines with rigid and teetered rotors using a wind turbine emulator
Bibliographic record
Abstract
Two‐bladed wind turbines (WTs) are recently discussed as a potential alternative to reduce the cost of energy in offshore wind farms which have a higher cost compared to onshore wind farms. However, the dynamic response and performance of these WTs are different from the three‐bladed WTs. In this study, new and comprehensive models for rigid and teetered rotor WTs are developed in FAST and emulated with a setup of the previous simulation‐based works. Then, the power quality issues are discussed and compared for two‐bladed WTs with rigid and teetered rotors as the main contribution of this study. The performance of a WT with different rotors is evaluated and compared in terms of power fluctuations, voltage fluctuations, flicker emission level. In addition, the structural loads of the turbine are studied and compared with both rotor types. This was done in emulation and simulation by varying linear horizontal and logarithmic vertical wind shear as well as utilising a turbulent wind time series without shear. The study presents results obtained by simulation and by emulation, using a scaled‐down WT emulator. It presents conclusions as to which type of rotor offers better performance for various operating conditions.
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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) | 0.000 | 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".