Bibliographic record
Abstract
Voltage stability continues to be a limiting phenomenon in many power systems world-wide. When combined with a continual growth in load, the lack of sufficient and optimally located generation together with the failure to build new transmission facilities has lead many systems to be vulnerable to situations of uncontrollable system voltages. In its most severe form, voltage instability can result in localized or even cascading system blackouts. To deal with this serious issue, many utilities have mandated the study of voltage stability as a normal component in system planning and operation. While acceptable methods of voltage stability analysis have emerged in recent years, and comprehensive tools have been developed, the issue of load modeling remains a challenge. It can be argued that the details of load modeling are, because of the nature of the phenomena, more critical for voltage stability than for other forms of stability, and this has perhaps been partially responsible for the lack of widely acceptable load modeling practices. This paper discusses some of the factors that make load modeling for voltage stability a challenge and provides insight into key issues which must be considered when performing practical studies
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".