Power flow methods for improving convergence
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Bibliographic record
Abstract
Power flows are widely used by engineers and remain essential for steady state analysis, short circuit and transient studies on power systems. Robustness of power flow methods is important for facilitating engineering studies on difficult network configurations. This paper presents a review of different techniques for improving the convergence of power flows. The methods under investigation consist essentially in adjusting the Jacobian and the incremental voltage. These adjustments incorporated within the Newton Raphson method are used to obtain a faster rate of convergence, to provide a larger region of convergence or both. Different techniques are first presented from an investigation of various schemes available in the literature. A power flow method consisting of a scaled Levenberg-Marquardt scheme is introduced and its property is compared along with other traditional methods. Comparisons of the region of convergence on a power system consisting of a 3000-bus model are presented.
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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) | 0.001 | 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 it