Offshore wind resource assessment of the Gulf of Thailand
Bibliographic record
Abstract
The Royal Thai Government recently launched its latest policy regarding the installation of 1,800 MW wind power capacity by 2025. While onshore wind power has significant limitations due notably to land use constraints and public acceptance, offshore wind energy offers good opportunities of development and is thus an interesting alternative. The main objective of this paper is to present the offshore wind resource assessment of the Gulf of Thailand, which covers an area of 320,000 km2. A coupled mesoscale-microscale model is used, along with R1 NCEP/NCAR global reanalysis database, to generate a high resolution wind resource map. Results show that interesting potential areas for offshore wind farm development have wind speeds of up to 6.5 m/s, especially in the upper part of the Gulf of Thailand, covering a surface of 2,112 km2. With a total potential installed capacity of 5,000 MW, the annual energy production is estimated at 9.64 TWh/year.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".