HIGH-RESOLUTION NUMERICAL SIMULATION OF WIND ENERGY RESOURCE IN HAINAN PROVINCE AND ITS OFFSHORE WATERS
Bibliographic record
Abstract
With high resolution (1 km), the distribution of wind energy resources in Hainan province and over its offshore waters is numerically simulated by using the Wind Energy Simulation Toolkit (WEST) model developed by Meteorological Research Branch of Environment Canada. Compared with observations from eight coastal anemometric towers and 18 existing stations in the province, the simulations show good reproduction of the real distribution of wind resources in Hainan and over its offshore waters, with the relative error of annual mean wind speed being no more than 9% at the 70-m level. Moreover, based on the simulated results of WEST grids that are closest to where the eight wind towers are located, the annual mean wind speeds are further estimated by using the Danish software WasP (Wind Atlas Analysis and Application Program). The estimated results are then compared with the observations from the towers. It shows that the relative error is also less than 9%. Therefore, WEST and WEST+WAsP will be useful tools for the assessment of wind energy resources in high resolution and selection of wind farm sites in Hainan province and over its offshore waters.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".