Application of new directional logic to improve DC side fault discrimination for high resistance faults in HVDC grids
Bibliographic record
Abstract
This paper proposes a simple and fast way to determine the direction of a fault in a multi-terminal high voltage direct current (HVDC) grid by comparing the rate of change of voltage (ROCOV) values at either side of the d i /d t limiting inductors at the line terminals. A local measurement based secure and fast protection method is implemented by supervising a basic ROCOV relay with a directional element. This directional information is also used to develop a slower communication based DC line protection scheme for detecting high resistance faults. The proposed protection scheme is applied to a multi-level modular converter based three-terminal HVDC grid and its security and sensitivity are evaluated through electromagnetic transient simulations. A methodology to set the protection thresholds considering the constraints imposed by the breaker technology and communication delays is also presented. With properly designed d i /d t limiting inductors, the ability of clearing any DC transmission system fault before fault currents exceeds a given breaker capacity is demonstrated.
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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 | 0.001 | 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".