Comprehensive Evaluation and Testing of Multi-Phase Line-Wise Power Flow Method for Unbalanced AC Power Systems
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Bibliographic record
Abstract
In response to the growing complexity and unbalanced nature of future distribution systems, this paper presents a comprehensive evaluation of the recently proposed multi-phase line-wise power flow (MPLW PF) method across various benchmark systems. The MPLW PF approach effectively models unbalanced power systems with different topologies and phase configurations. This study extends the application of MPLW PF by testing its accuracy, convergence, and computational efficiency on a wide range of AC multi-phase and three-phase systems, including radial and meshed configurations. The MPLW PF method is tested on several benchmark systems, demonstrating its accuracy, scalability, and significant run-time reduction compared to traditional bus-wise (BW) method and OpenDSS as a commercial software.
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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 | 0.001 | 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