Adaptive protection coordination in microgrid based on nature inspired meta-heuristic optimization algorithm
Bibliographic record
Abstract
Abstract Ensuring a robust protection system is crucial for safeguarding the integrity of the overall system against abnormalities. Incorporating distributed generation (DG) into the distribution network can introduce fluctuations in fault current levels and directions, potentially causing mismatches in the response of the existing coordination system. This study proposes an adaptive protection coordination scheme designed to accommodate both grid-connected and standalone modes, addressing various fault scenarios. Utilizing a hybrid WCMFO algorithm, optimal relay settings are determined to facilitate effective coordination within a microgrid setup. The proposed method has been analyzed on 9 bus Canadian benchmark system integrated with four DGs. The performance of the proposed method is compared to other optimization techniques to demonstrate its effectiveness. System modelling is conducted using MATLAB/Simulink, and validation is further carried out using industrial ETAP software on a test microgrid system. The analysis extends to evaluating the enhancement in overall system reliability, quantified in terms of energy not supplied (ENS).
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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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".