Development of an Index for Preventive Control Ranking and Selection for Voltage Stability Analysis
Bibliographic record
Abstract
Preventive control selection for voltage stability concerns with determining the preventive controls that have to be activated, and finding a coordination between these preventive controls. This work develops an index, namely correction index CI, that can be used to rank the preventive controls for voltage stability analysis. This ranking helps the operators to select the most effective preventive controls to simultaneously mitigate the impacts of system contingencies on the critical buses. In other words, if such index is used for control selection, the useless (or less effective) controls can be ignored. This index is based on the degree of the effectiveness of the preventive controls to improve the voltage stability margin of power systems. The index can measure the efficiency of each preventive control not only to one bus (i.e. pilot bus), but to multiple critical buses of the system. The cost aspect is also involved in index calculation to distinguish between the cheap and the expensive controls. This means that the correction index helps the operators to select only the cheap and the high-effective controls. The proposed method is tested on the IEEE 39 bus network under a contingency scenario. The results show that the proposed index is accurate and valid for control ranking.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".