Turbine performance and wind energy potential using probability distribution in Africa
Bibliographic record
Abstract
The energy requirement in the world is increasing day by day. The non-renewable energy production is one of the reasons for climate change. The present study explores the selection of possible locations to establish a wind power plant in Ethiopia. The possible locations in Ethiopia that were considered in this study are Weraelu, Enewari and Mekdela. The wind speed characterisation, wind direction and wind power densities were analysed at Weraelu, Enewari and Mekdela. The results of this study reveal that Enewari is the best suitable place to establish the wind power plants among Weraelu, Enewari and Mekdela. In Enewari site, the maximum wind speed at 10 m height is 6.11 m/s. Seventy-five per cent of wind direction at Enewari site is from north to northwest and north to northeast. The Weibull distribution analysis was incorporated to find average wind speed and probability density among 5 years of wind speed data. The average wind speed and probability density over 5 years of Enewari site is 5 m/s and 18.5%. The wind power densities were determined by the Weibull method and the maximum wind power obtained from Enewari site is 495.33 W/m2.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".