A Test on Probabilistic Reliability Evaluation of the Korea Power System
Why this work is in the frame
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Bibliographic record
Abstract
The importance and conduct of necessary studies on grid reliability evaluation have become increasingly important in recent years due to the number of blackout events occurring throughout the world. Additionally, quantitative evaluation of transmission system reliability is very important in a competitive electricity environment. The reason is that successful operation of an electric power under a deregulated electricity market depends on transmission system reliability management. This paper suggests that the important input parameters of a probabilistic reliability evaluation tool for the KEPCO-system by sensitivity analysis of high reliability level operation. Simultaneously, it also presents sensitivity analysis probabilistic reliability evaluation of practical KEPCO-system long-term transmission system expansion planning (2006-2010). The tool utilized a Transmission Reliability Evaluation for Large-Scale Systems (TRELSS) which was developed by EPRI and Southern Company Services Inc.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| 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 | 0.001 | 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