Performance Testing and Control of a Small Wind Energy Converter
Bibliographic record
Abstract
Responding to more demand in coming years, the task of the small wind energy industry requires progress on several fronts-from public policy initiatives, to technology development, to market growth. Enhanced technologies such as contra-rotating blades, transmission systems, lubrication, airfoils, generators, and power electronics will lower cost and increase energy production. This paper mainly considers two key technological points of a small wind energy converter (SWEC) namely, the performance of the rotor system and induction generator. Small-scale prototypes have been built to experimentally verify the performance of the SWEC. Wind tunnel tests of the power output, power coefficient, and turbine speed were carried out to ascertain the aerodynamic power conversion and the operation capability at lower wind speeds. The results demonstrated a significant increase in performance compared to a single-rotor system of the same type. Another aspect of development and test is to present a comparative performance evaluation between a standard induction generator and an efficient but with modified design (TRIAS Generator) as a realistic solution of clean power for grid-connected SWECs. The paper also discusses issues related to control and monitoring of SWEC.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".