The impact of tower shadow, yaw error, and wind shears on power quality in a wind-diesel system
Bibliographic record
Abstract
To study the impact of aerodynamic aspects of a wind turbine (i.e. tower shadow, wind shears, yaw error, and turbulence) on the power quality of a wind-diesel system, all electrical, mechanical and aerodynamic aspects of the wind turbine must be studied. Moreover, the contribution of the diesel generator system and its controllers should be considered. This paper, describes how the aerodynamic and mechanical aspects of a wind turbine can be simulated using TurbSim, AeroDyn, and FAST, where the electrical parts of wind turbine, diesel-generator, its controllers, and electrical loads are modelled by Simulink blocks. Simulation results obtained from the model are used to observe the power and voltage variations at the wind turbine generator terminals under different operating conditions. Furthermore, the effects of tower shadow, wind shears, yaw error, and turbulence on the power quality in a stand-alone wind-diesel system utilizing a fixed speed wind turbine are studied.
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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) | 0.000 | 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) | 0.000 | 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".