An Online Algorithm for Linear Optimal Power Flow Computations
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Bibliographic record
Abstract
The conventional optimal power flow (OPF) formulation falls short when dealing with incomplete information in real-time operations. Recent studies propose OPF reformulations using online algorithms to cope with this limitation. However, existing implementations oversimplify grid models, resulting in noticeably unrealistic scenarios. This study employs a linear approximation of the power flow balance equation that convexifies the problem while preserving reactive power flows and voltage variables within the analysis. Thus, the OPF is formulated as an online convex optimization problem and solved using primaldual updates. This study presents the update equations using the Lagrangian function that minimizes the dynamic regret. The proposed algorithm is tested on the IEEE 33-bus test system to validate its convergence and analyze application opportunities. The results demonstrate that the algorithm converges with sublinear regret and fulfills the OPF security constraints.
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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) | 0.000 | 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