Adaptive Protection Coordination Scheme for Distribution Networks with Distributed Generation
Bibliographic record
Abstract
As distributed generation (DG) supported by renew-able energy become more and more prevalent in the distribution network (DN), the coordination of directional overcurrent relays (DOCRs) in their presence needs to be addressed. Numerous meta-heuristic optimization strategies have been used to address this problem in order to determine the optimal relay settings and to achieve the best possible coordination of the protective relays considering coordination constraints. This study presents an adaptive protection coordination strategy for DNs with inter-connected DG units. The scheme utilizes Chicken swarm opti-mization (CSO) to achieve optimal coordination. It dynamically adjusts protective device (DOCR) settings in response to changes in the system, such as fluctuations in DG output or modifications to the network topology. The effectiveness of the proposed adaptive scheme is demonstrated through its application to two benchmark systems: the 9-bus Canadian system and the IEEE 30-bus system. The results are presented and analyzed, showcasing the scheme's capabilities. This approach significantly enhances power system protection and enhances reliability and efficiency of power DNs.
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.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".