Implementing and testing d − q WPT-based digital protection for micro-grid systems
Bibliographic record
Abstract
This paper introduces an implementation procedure and performance testings of a wavelet packet transform (WPT)-based digital protection for micro-grid systems. This digital protection is structured for detecting and classifying faults based on the values of the WPT coefficients of the high frequency sub-bands present in the d - q-axis current components. The WPT coefficients are determined using the Daubechies db4 wavelet basis functions, which are found optimal for analyzing transient disturbances likely to occur in power systems and electric machines. The proposed digital protection is implemented for experimental performance testing on a test micro-grid system that is constructed as a laboratory scale of an actual micro-grid system located in Fermeuse, Newfoundland, Canada. Several transient disturbances occurring in different parts of the test micro-grid system are experimentally investigated. Performance results demonstrate significant capabilities of the d - q WPT-based digital protection for accurate and reliable detection and classification of fault conditions, along with fast response to classified faults.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".