Estimativa de redução de emissão de CO2 pela inserção de UFV para cidades isoladas na Amazônia
Bibliographic record
Abstract
Most of the cities isolated from the national interconnected electrical grid are located in the brazilian Northern Region, and are mainly supplied by thermal power generation, despite representing the main contribution of the electricity sector to greenhouse gas emissions. the isolation occurs mainly because of environmental issues and financial constraints. In Acre, six thermal units supply three isolated cities, with a total installed capacity of 48,34 MW. Due to the potential for renewable energy generation and the high solar irradiance at the sites, the potential for photovoltaic generation in the municipalities of Cruzeiro do Sul, Feijó and Tarauacá was studied considering their respective load curves and solarimetric data of the region, which were provided by stations close to the locations, using the RadiaSol 2 software. Generation systems were proposed for each municipality considering 400W panels, varying the photovoltaic penetration rate with 100%, 75% and 50%. Computer simulations were used to estimate the environmental benefits of the possible replacement of the energy source was estimated based on the reduction of CO2 emissions calculated with the bottom-up method. The quantity and total area of the panels and the cost of implementation were also estimated. The carbon dioxide emissions of the photovoltaic power generation were much lower than those of thermal power generation with diesel fuel. They decreased between 94% and 47% compared to thermal power generation in the three cities. Despite the high costs photovoltaic plants, the investment in hybrid power generation systems is justified by the environmental benefits.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".