The development and testing of a coordinated anti-islanding protection for collector systems with multiple distributed generation units
Bibliographic record
Abstract
This paper presents a coordinated anti-islanding protection for collector systems with multiple distributed generation units (DGUs). The presented anti-islanding protection is established based on processing the d-q-axis components of the instantaneous three phase apparent powers (sd and sq), determined at the point-of-common-coupling, using the wavelet packet transform (WPT). Processing sd and sq by using WPT allows the extraction of low and high frequency sub-band contents. The contents of the high frequency sub-band are used to detect and distinguish islanding events, and contents of the low and high frequency sub-bands are employed to define a coordination index, which is used to identify the islanded DGU(s). The presented anti-islanding protection is implemented for off-line testing using data obtained from a laboratory collector with four different DGUs. Off-line test results demonstrate accurate, fast, and reliable responses to islanding and non-islanding event(s), accurate identification of islanded DGUs, along with negligible sensitivity to levels of power delivery to the collector system.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".