Integration of new generation and load technology in the computation of risk over the operations planning time-horizon
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As new load and generation technologies accompanied by inherent uncertainties are integrated into power systems, utilities should plan to revise their balancing reserves in order to mitigate the consequences of forecast errors. One such technology is wind power generation. To this end, Hydro-Québec has put forward a novel methodology calculating the level of these balancing reserves, over the time horizon of 1-48 hours, based on the risk that the load will exceed the committed generation capacity. The methodology reported in this paper requires as input the statistical characteristics of the load and wind generation forecast errors and of the generation outages, but it is general enough to accommodate other technologies displaying forecast uncertainties The implementation details of this methodology as well a discussion of the nature of the results are given.
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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) | 0.000 | 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 it