QV interaction evaluation and pilot voltage‐reactive power coupling area partitioning in bulk power systems
Bibliographic record
Abstract
This study presents a novel methodology to evaluate the QV interactions among buses and to partition the pilot voltage‐reactive power coupling areas (VRPCAs) using relative gain (RG). According to the concept of a multi‐input multi‐output system, the QV coupling RG is first calculated based on the QV matrix, which is extracted from power flow Jacobian matrix, to evaluate the QV interactions among different buses and then to determine the VRPCAs. The voltage stability critical buses are first identified through a modified loading margin. For each critical bus, the other buses that have strong QV coupling are detected via the cross RG and are clustered into a VRPCA piloted by the corresponding critical bus. New England 39‐bus system and Polish power system are used to test the performance of the proposed approach. Simulation results verify the effectiveness of the proposed approach in evaluating the QV interactions and partitioning the VRPCAs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".