A single-ended protection scheme for multi-terminal HVDC grids based on Hilbert-Huang Transform
Bibliographic record
Abstract
Protection is one of the major obstacles in realizing reliable and secure multi-terminal HVDC grids. This paper proposes a single-ended protection scheme that reliably detects internal faults in less than $1 ms$ and distinguishes them from external faults. The proposed algorithm employs the instantaneous features estimated by Hilbert-Huang Transform (HHT) to detect various fault events. First, Empirical Mode Decomposition (EMD) is applied to the local voltage measurements to extract the first intrinsic mode function (IMF), which contains the distinctive features of the fault-initiated traveling waves. Second, the instantaneous frequency and average instantaneous energy, estimated by HHT, are continuously tracked to rapidly detect the fault event. Various simulations applied to a four-terminal meshed HVDC grid are carried out on PSCAD/EMTDC to validate the effectiveness of the proposed algorithm under severe internal and external 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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".