DSP-based Adaptive Protection for Feeders with Distributed Generations
Bibliographic record
Abstract
Distributed generations (DGs) have been increasingly connected on the distribution feeders that impose challenges on traditional feeder protections. This paper proposes a new adaptive strategy for protection of distribution-system feeders connected with DGs using state-of-the-art digital signal processing (DSP) technology. The proposed strategy overcomes DGs-imposed technical challenges on feeder protection such as increase of fault current, change of prescribed fault flow paths, sympathetic tripping, unintentional islanding operation, continuous non-interruptible fault current, etc., as well as non-DG-caused problems such as undetected high-impedance ground faults. This paper shows the strategy for effective use of state-of-the-art DSP technology for real-time determination of correct protection operations for feeders with dispersed DG-connections against faults and surges resulting from lightning, equipment short-circuit, and switching of capacitors, DGs, large loads, etc.
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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 | 0.000 |
| 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) | 0.002 | 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".