Utilization of the Area Risk Concept for Operational Reliability Evaluation of a Wind-Integrated Power System
Bibliographic record
Abstract
Wind power generation is significantly different from conventional thermal and hydro power generation in the sense that the wind power is governed by the atmosphere and cannot be dispatched like the conventional units in order to respond to the system requirements. The operational reliability of a conventional system depends on the failures of the committed units and the lead time of the next available unit. The reliability contribution of a wind turbine generator is mainly governed by the variability of wind speed at the wind site. A short-term wind model developed for the specific lead time should be suitably combined with the other committed units to evaluate the operational reliability of a power system with significant wind penetration. The area risk concept, previously developed to evaluate the reliability contribution of rapid start units and hot reserve units that are committed later in the lead time, is extended in this paper to incorporate wind power in evaluating the system reliability. The developed method is applied to the IEEE-RTS to evaluate the operational system well-being indices.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".