An Optimal Composition and Placement of Automatic Switches in DAS
Why this work is in the frame
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Bibliographic record
Abstract
This paper proposes an algorithm for determining the optimal composition which means number of links and section switches in a feeder and placement of automatic switches in a distribution automation system (DAS). A DAS is configured by automatic switches and reclosers on a power distribution line. The composition and placement of switches affect the operational applications of a DAS. More switches lead to better DAS operation but also to increased cost and maintenance. Thus, this paper proposes an approach to determining the optimal composition and placement of automatic switches. Additionally, the proposed algorithm is developed considering various system topologies in a real field. The algorithm was tested on an example power distribution system with eight-feeders and on a real power distribution system operated by KEPCO in Young-Deung-Po and Jeju, South Korea.
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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