Hydrothermal simulations in Brazil using batteries - First Results
Bibliographic record
Abstract
The share of renewable energy sources has increased worldwide, especially those considered unconventional (i.e. without considering hydropower). Besides proved as economically competitive, these sources cause less environmental impacts when compared to other sources of traditional power generation such as coal and oil. However, solar and wind power plants are intermittent, i.e., the generation varies according to the availability of the respective natural resources and therefore are considered non-dispatchable by the System Operator (SO). Because of that, the electrical systems must be able to somehow compensate the variability from the non-dispatchable energy sources to meet the supply-demand equilibrium. Storage technologies such as electrochemical (e.g. batteries) and electromechanical (e.g. flywheel) could be used in that sense. Recent developments of these technologies opened space for several ancillary services and products to be offered by the storage systems to the electrical system. In addition to that, the sustained reduction in operation and maintenance (O&M) costs summed to the payments for providing ancillary services could make some of these technologies economically attractive, under certain conditions. Given this new scenario, the representation of these storage systems in the expansion planning and power systems mathematical models becomes necessary. In this study, we simulated the Brazilian electrical system at 2035, considering batteries (corresponding to 7% of the installed capacity) and a 30% share of unconventional renewable energy in the system generation capacity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".