ANÁLISIS PRELIMINAR DE LA VARIABILIDAD DE CORTO PLAZO DEL RECURSO SOLAR EN ARGENTINA UTILIZANDO LOS DATOS DE LA RED SAVER-NET
Bibliographic record
Abstract
La variabilidad de la irradiancia solar introduce limitaciones a la producción de energía solar fotovoltaica(PV) ya que dificulta su despacho. Por lo tanto, su cuantificación es importante para el desarrollo en gran escala desistemas PV y su contribución relativa a la matriz eléctrica. Argentina posee un gran potencial para la generación solar,con un extenso territorio que recibe una irradiación promedio anual de 5 kWh/m2/día. Además, cuenta con el respaldode políticas públicas y regulaciones que fomentan la transición hacia fuentes de energía renovable. En este trabajo secuantificó la variabilidad de corto plazo (minutal, 10-minutal y horaria) mediante la desviación estándar de los cambiosen el índice de cielo claro (kc). Se analizaron las series temporales de los años 2019 y 2020 en 6 estaciones de la redArgentina de radiación solar Saver-Net. Se encontró un promedio de variabilidad nominal en los sitios de 0,09, 0,13 y0,15 para 1 minuto, 10 minutos y 1 hora, respectivamente. Estos valores sugieren una variabilidad intermedia del recursosolar a lo largo del territorio.Palabras clave: Fluctuaciones, GHI, Energía solar
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".