Techno-Economic Assessment of a 1 MW Solar PV Rooftop System at Thaksin University (Phatthalung Campus), Thailand
Bibliographic record
Abstract
This study presents a techno-economic assessment of a 1 MW solar photovoltaic (PV) rooftop system at Thaksin University (Phatthalung Campus) in Thailand. A detailed analysis of the solar PV rooftop system is performed with particular attention to the performance of different PV technologies and the effects of different tilt angles and orientations of the PV panels on the annual energy production, the specific production, and the performance ratio. The economic analysis was performed for four scenarios: (1) self-investment and self-consumption scheme, (2) bankable and self-consumption scheme, (3) bankable and feed-in tariff (FiT) scheme, and (4) energy service company (ESCO) scheme. The results show that the amorphous silicon/micro-crystalline silicon (a-Si/µc-Si) technology shows the lowest annual energy production and performance ratio (PR), while the copper indium disulfide (CIS) technology records the largest annual energy production and PR. The largest annual energy production and specific production were obtained with the PV panels installed at a 10° tilt angle and with the PV modules facing South (S), while the lowest annual energy production and specific production were observed with the PV panels installed at a 45° tilt angle and the PV modules facing North (N). The economic analysis results show that the best scenarios are Scenario 3 (bankable and FiT scheme) and Scenario 1 (self-investment and self-consumption scheme). The findings of this research provide valuable information for regional stakeholders and policymakers regarding investments in solar PV rooftop systems.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".