Prospects of Wind Energy for Power Generation in University of Benin
Bibliographic record
Abstract
Wind is a renewable energy resource by nature. It is clean, abundant, inexhaustible and environmentally friendly. Essentially, this study investigated the prospects of wind energy for power generation in University of Benin. Wind data from Jan 31st – Dec 31st 2013 (at 10m height) was collected from National Centre for Energy and Environment, University of Benin. Accordingly, the annual and monthly wind speed and density are estimated using the 2- parameter Weibull probability density function. From the analysis, results obtained shows that the highest mean wind speed of 1.975m/s occurred in March and the lowest monthly mean speed of 0.977m/s occurred in November. Also, the annual mean wind speed is 1.496m/s while the annual mean power density based on Weibull distribution function is 2.692W/m2 . Further results shows that the mean annual most probable wind speed and wind speed carrying maximum energy are 1.535m/s and 1.761m/s respectively. Thus, it is recommended that the institution can tap on the available wind power potential to augment its power supply.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 0.001 |
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".