Bulk Electric System Well-Being Analysis Using Sequential Monte Carlo Simulation
Why this work is in the frame
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Bibliographic record
Abstract
There is growing interest in combining deterministic considerations with probabilistic assessment in order to evaluate the "system well-being" of a composite generation and transmission system and to evaluate the likelihood not only of entering a complete failure state but also the likelihood of being very close to trouble. This paper presents bulk electric system well-being analysis using sequential Monte Carlo simulation. This approach provides accurate frequency and duration assessments and the index probability distributions associated with the mean values. The basic N-1 security criterion is used as the deterministic requirement for incorporating a deterministic consideration in a probabilistic assessment to monitor system well-being. The results shown in this paper indicate that the system well-being concept can provide comprehensive knowledge on what the degree of system vulnerability might be under a particular system condition. The basic concepts and their application in composite power system well-being analysis are illustrated by application to a small practical test system.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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