A Robust scheduling method of AC / DC Distribution Network Based on Diamond-shaped Cutting Convex Hull Set
Bibliographic record
Abstract
In an effort to enhance the description of the uncertainty inherent in renewable energy production, this paper proposes a robust scheduling method of AC/DC distribution network based on diamond-shaped cutting convex hull set. Initially, an ellipsoidal set accounting for uncertainty was developed using historical renewable energy data, alongside a data-driven convex hull polyhedron formed by interlinking vertices from a high-dimensional ellipse. Building upon this, addressing the substantial conservatism encountered when scaling the convex hull polyhedron, a convex hull set model of diamond-shaped cutting is established. Additionally, a robust scheduling model specifically for AC/DC distribution grids, utilizing the diamond-cut convex hull configuration, is formulated with the assistance of the C&CG algorithm for its resolution. Conclusively, validation through simulations on the enhanced IEEE-33 node system indicates that the proposed method can effectively reduces conservatism while enhancing the robustness of the outcomes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".