Investigation of Cascaded Commutation Failures in Multiple LCC-HVdc Inverters Caused by Rectifier Side AC Grid Faults
Bibliographic record
Abstract
In earlier work, cascaded commutation failure (CF) in multiple LCC-HVdc inverters of the multi-infeed system has been attributed to inverter side ac grid faults. However, this paper discusses a phenomenon where the cascaded CF is caused by rectifier side ac faults. The risk of this phenomenon is evaluated considering various fault inception instants, types, durations, and severities by electromagnetic transient simulations. The underlying mechanism of the phenomenon is identified by calculating the area under the commutating voltage curve. It is found that the commutating voltage waveform distortion arising from asymmetrical operation of the primary inverter after the fault clearance causes the initial CF. This CF subsequently introduces significant low-order harmonics into common inverter side ac grid, which propagate to the remote inverter ac bus and consequently induce the cascaded CF. It is also shown that if the tie-line impedance between inverter ac buses limits the propagation of low-order harmonics, the cascaded CF can be avoided. The dependency of the phenomenon on ac grid parameters is further quantified using the CF immunity index (CFII). It is inferred that the phenomenon is alleviated with the increased rectifier and inverter side ac grid strength as well as tie-line impedance magnitude at fundamental frequency.
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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 | 0.001 | 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".