Designing a Reliable Power System: Hydro-Quebec's Integrated Approach
Bibliographic record
Abstract
Hydro-Que/spl acute/bec's transmission system is among the most extensive and complex transmission networks in North America. The system's design was improved over the last few years using an optimization process based on acquired experience as well as customers' expectations. Hydro-Que/spl acute/bec's transmission system is currently designed in accordance with four major guiding principles based on a successive line of defense concept designed to counter events that are increasingly more severe but also increasingly more rare. These major guiding principles are a direct reflection of the level of risk that society accepts to tolerate in relation to the costs involved by higher reliability requirements. Que/spl acute/bec's specific context, which is characterized by long transmission lines, harsh weather, and customers' heavy reliance on electricity for their heating needs, means that very high security standards must be used in the system design. To obtain a level of reliability on par with that of our neighbors' systems, however, requires more stringent criteria and standards. This paper will describe the design philosophy of Hydro-Que/spl acute/bec's power system, the underlying major guiding principles, and the defense plans designed to ensure its reliability.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".