Multi-interval optimization for real-time power system scheduling in the ontario electricity market
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
The Ontario IMO market operation system software that determines the real-time (5-minute) dispatch instructions has been enhanced to optimize over a number of intervals. Optimizing over a rolling period of up to 1 hour ahead provides more reliable and economic operation by taking into account upcoming demand and system condition changes without need for manual operator intervention. Multi-interval optimization (MIO) makes dispatch advisories available to market participants for future dispatch instructions, which helps them to efficiently manage their units and allows them to be better able to follow their dispatch instructions. Based on the first five months of operation experience, MIO has improved unit scheduling and stability of the IMO network. It also reduces the amount of operator manual intervention and, therefore, leads to more transparent market operation.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 it