Investment Incentive of Grid Connected Solar Photovoltaic Power Plant under Proposed Feed-in Tariffs Framework in Thailand
Bibliographic record
Abstract
This study aims to present the proposed feed-in tariffs in grid connected photovoltaic power plants in Thailand. Under the Renewable and Alternative Energy Development Plan for 25 percent of final energy consumption in 10 years (AEDP 2012-2021), The government of Thailand has planed that the electricity generated by solar power will be 2,000 MW or 2,484 GWh. Thailand has moderate solar potential with average annual global radiation of 17-18 MJ/m 2 .day. Until recently, the incentive of investment to produce electricity from solar power is under government subsidization scheme, or Adder. However, the Adder itself has many constraints such as the limitation of the period of subsidization within 10 years for solar power. This paper investigates the proposed feed-in tariffs in solar photovoltaic through the whole lifetime of the projects by an energy model (RETscreen model) in three categories; (1) residential rooftop, (2) integrated ground mounted and rooftop solar photovoltaic, and (3) utility scale with the installed capacity larger than 1 MW. The result of this study found that the proposed feed-in tariffs with after tax return to equity of 11.0% are: $0.48/kWh for residential rooftop, $0.31/kWh for the integrated ground mounted and rooftop solar photovoltaic, and $0.28/kWh for the utility scale.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".