Wind resource assessment and wind power potential for the city of Ardabil, Iran
Bibliographic record
Abstract
The results of an investigation of the potential of wind energy as a power source are reported for an Iranian north-western city, Ardabil. The Weibull probability distribution function using a long-term data source, consisting of 6 years (2005–2010) of 3-h period measured mean wind data, is adopted and analyzed. The data have been measured at a height of 10 m above the ground level. Also, monthly and annual wind speed variations are analyzed. The monthly mean wind speed is between 2.09 and 6.58 m/s, while the annual mean wind speed is in the range of 3.28–4.08 m/s. The Ardabil site is found to have good characteristics from the perspective of mean wind speed. The numerical values of the shape and scale parameters for Ardabil are seen to vary over a wide range. The monthly mean value of shape parameter ( k ) is between 2.62 and 3.17, while the monthly mean value of the Weibull scale parameter ( c ) is between 3.36 and 5.43 m/s. The results show that the months of October and September have higher mean power densities and that July has a lower mean power density than other months. Also, the wind potential of the studied region is determined to be very suitable for the off-grid connections and could be acceptable for connecting to power grids.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".