Optimal coordination of directional overcurrent relays using hybrid BBO/DE algorithm and considering double primary relays strategy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Finding optimal settings of directional overcurrent relays (DOCRs) has been extensively solved by many scenarios with adopting different traditional and modern optimization algorithms. For the sack of simplicity, all the conducted studies in the literature are restricted on a condition that all DOCRs are numerical, static, or electromechanical. There is a fact that when jumping from electromechanical or static relays to numerical relays the former devices could be used as a second wall of protection instead of just throwing them. With a very extreme condition, which may not happen in the real-world applications, all buses will have double primary DOCRs, which where act as backup DOCRs for other buses. That is, the dimension of any given problem is duplicated and becomes very hard to be feasibly and optimally solved. This paper covers this uncommon scenario, and a new hybrid algorithm with some additional sub-algorithms is developed to solve the IEEE 6-bus test system. Moreover, both numerical with electromechanical DOCRs and numerical with static DOCRs are considered in this study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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