Modeling and Design of Parallel LCC-VSC Interlinking Converters’ Unified Controller in AC/DC Network
Bibliographic record
Abstract
While both line-commutated converters (LCCs) and voltage-source converters (VSCs) have been adopted in ac/dc grids, they are mostly used individually despite some point-to-point dc transmission. The combination of both technologies as a single interlinking converter (IC) unit in an ac/dc grid can bring advantages, such as capacity expansion, bidirectional power flow, reactive power support, and harmonics compensation. For such a parallel LCC-VSC unit, a suitable control scheme and careful control parameters’ design are important to ensure that the system can maintain the above advantages in different operation modes. In this article, the control scheme and parameter design for a parallel LCC-VSC unit for use in an ac/dc grid are conducted with a focus on capacity expansion scenario, where a unified control scheme that reserves most of the original LCC terminal’s control while also smoothly incorporates the VSC operation is considered. The operation states of a hybrid ac/dc network are modeled. The proposed unified control scheme is considered for each state for the stability study. Then, a set of control parameters for the unified control scheme suitable for all operation states with good dynamics and stability is designed. Real-time simulations and experiments are conducted to verify the design and study.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".