Photovoltaic energy production systems and the carbon market in Maranhao: a case study
Bibliographic record
Abstract
The dissertation deals with a research carried out with data from a 168.4kWcc/120kWca photovoltaic solar plant installed in Itapecuru Mirim, in the state of Maranhão, with the objective of modeling a system for parameterization and possible calculation of the effect of the solar photovoltaic system on the market of carbon credit. Throughout the introduction and the theoretical framework, advances in photovoltaic solar technology in the world and in Brazil are presented. The project aims to carry out data collection such as power, voltage, current, yield and performance in a solar farm already obtained in the system and analyze the impact of the efficient use of solar energy. The system used as a base has the following characteristics: plant for distributed generation, in remote self-consumption mode, use of Canadian modules, kUmax line, CS3U-380|385|390|395|400MS, 1000V/1500V, number of boards: 440 units, 22 units of strings of 20 modules. and 2 units of Sungrow SG 60KTL inverters, total area: 0.31h, rated power: 1.36kWp, inverter power: 120Kw. The methodology consists of the following steps: First, discussing the role of the solar photovoltaic system in carbon crediting models, starting with a discussion of this type of system in the global scenario, the role in the global and regional scenario. Then, the impact of solar photovoltaic projects on the avoidance of atmospheric carbon emissions will be evaluated, and based on data obtained from the photovoltaic solar plant in Itapecuru Mirim - MA, a model and visualization of the impact result for the state will be carried out.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".