Investigation of Fault Ride-Through Capability of Hybrid VSC-LCC Multi-Terminal HVDC Transmission Systems
Bibliographic record
Abstract
In this paper, clearing of DC faults in a hybrid multi-terminal HVDC transmission system consisting of line commutated converters (LCCs) and voltage source converters (VSCs) implemented using half-bridge modular multilevel converter (MMC) technology is investigated. While the hybrid HVDC system has several possible configurations, this paper focuses on two of them: 1) a half-bridge MMC-HVDC link piggy-backing on the transmission line of a LCC-HVDC link and 2) LCC-HVDC link tapped by half-bridge MMC inverters. The proposed dc fault recovery strategy employs a high rating series diode valve placed at each VSC inverter pole to block fault currents; AC circuit breakers to isolate the faulty VSC rectifier pole; and force retardation applied at LCC rectifier to extinguish the arc. Detailed simulations demonstrate fast fault recovery performance with the proposed fault recovery procedure. In the case where a single transmission line is shared by the LCC and VSC links, the VSC rectifier is subjected to considerably high current for a period of few hundreds of milliseconds and the ac side voltage dips momentarily. During a single pole fault, interrupting power flow on the healthy pole of VSC rectifier may be necessary to maintain smooth operation.
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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) | 0.001 | 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".