Optimal Shunt Capacitors’ Placement and Sizing in Radial Distribution Systems Using Multiverse Optimizer
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Bibliographic record
Abstract
This article presents a new approach for solving the radial distribution systems optimal shunt capacitors' placement and sizing problem. The approach modifies and partially uses the conventional loss sensitivity factors (LSFs) and MATLAB's ismember and any commands to reduce the search space of optimal buses that require shunt capacitor placement. Afterward, the multiverse optimizer (MVO) is used to do a concurrent search of the most optimal buses and the corresponding capacitor sizes. To evaluate the effectiveness of the developed approach, simulations have been carried out on the 10-, 33-, and 69-bus radial distribution systems. For all the test systems, the simulation results show that the developed approach gives results as good as those obtained when a search for the most optimal buses is carried out in unreduced search spaces, hence making the approach effective in reducing the computation time and maintaining the much-needed accuracy. Finally, the performance of the MVO has been compared against the other 11 different optimization algorithms, and in all instances, its performance has been outstanding.
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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