Offshore wind power assessment on the western coast of Thailand
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Bibliographic record
Abstract
This paper presents an offshore wind resource assessment and offshore wind power feasibility analysis on the western coast of Thailand using coupled mesoscale atmospheric and microscale Computational Fluid Dynamics wind flow modeling, along with a climatic database. Offshore wind maps at elevations of 80 m, 90 m and 120 m above mean sea level (amsl) are presented and validated with measured wind datasets gathered from nine met masts installed along the coast of the Andaman Sea and the Strait of Malacca on the western part of Thailand. Results show that, at an elevation of 120 m amsl, the northern region near Myanmar is characterized by wind speeds in the range of 5.5 to 6.0 m/s, while the area around Phuket Island has wind speeds in the range of 4.6 to 5.3 m/s. In line with the Thai energy policies for wind power plant development, the annual energy production, the capacity factors, the levelized cost of energy (LCOE), the CO2eq emission avoidance, and the required Feed-in-Tariff (FiT) are analyzed for wind power plants integrating 3.3 MW, 8.0 MW and 9.5 MW offshore wind turbine generators. Results show that offshore wind power plants with 3.3 MW wind turbine generators could produce over 13 GWh of electricity per year under the Very Small Power Producer (VSPP) scenario for 10 MW wind power plants. For its part, 50 MW wind power plants under the Small Power Producer (SPP) scenario could produce 68 GWh/yr, and nearly 123 GWh/yr for SPP wind power plants with 90 MW of installed capacities. With capacity factors in the order of 16%, the lowest LCOE is 0.188 USD/kWh and the CO2eq emission avoidances reach 774 tonnes CO2eq per year. Finally, the required FiT to sustain the development of VSPP offshore wind power plants in the vicinity of Phuket Island is in the range of 0.314 to 0.688 USD/kWh.
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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 it