Line-Wise Optimal Power Flow Using Successive Linear Optimization Technique
Why this work is in the frame
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Bibliographic record
Abstract
Optimal power flow (OPF) is an important power systems optimization tool. However, due to the inherent nonlinearity of the solution space, OPF methods may yield a local optimal solution, leading to economic loss. For this reason, an OPF remains a major research topic. Changing power balance equations can change the solution space, alter solution time, and create a chance of reaching a better solution. In this paper, a new simple line-wise optimal power flow (LWOPF) formulation is proposed using line-wise power balance equations and solved using the successive linear programming (SLP) technique. The study results on nine different test systems, up to a 9 241-bus real power system, show that the proposed method is accurate, provides monotonic convergence, scales well for large systems and is consistently faster, up to twice the speed of MATPOWER and other proven bus-wise SLP approaches to solve the OPF.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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