A novel approach for early detection of impending voltage collapse events based on the support vector machine
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Bibliographic record
Abstract
This paper proposes an approach to detect the possibility of long-term voltage instability, based on online measurement of system bus voltages. An optimization framework is proposed to determine the maximum loading points, with different load increase patterns and different levels of reactive power output. The operating conditions so obtained are used as the training database for an artificial intelligence classifier based on the support vector machines. In an online application, the support vector machine classifier helps in detecting the probability of some generators operating at high reactive power output, which is an important indicator of an impending voltage collapse. The proposed framework is tested with the IEEE 39 bus and the Nordic 32 bus systems. The test results demonstrate that the proposed scheme gives reliable prediction of the power system long-term voltage stability.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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