Control of Reactive Power and Connection Voltage in Grid Connected Wind Turbine
Bibliographic record
Abstract
Due to the development and progress of countries, with the passage of time, our need for electrical energy also increases, but electricity production relies on fossil energy sources, which are both running out and cause the production of greenhouse gases, but on the other hand, because energy is cheap. Wind this renewable energy has been developed rapidly on a global scale. However, due to the fact that in wind power plants, wind speed will not always be constant and it is changing, this problem disturbs the balance of the power system and causes the voltage to always change, for this reason, the grids in which there is a wind turbine are different from each other. grids are different and many researches and studies have been done to solve this problem, and due to its many advantages, the Doubly Fed Induction Generator (DFIG) is considered to compensate for these problems, by using it, we will not need to compensate for additional reactive devices We had and can control the speed, active and reactive power.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".