A Coherency-Based Equivalence Method for MMC Inverters Using Virtual Synchronous Generator Control
Bibliographic record
Abstract
This paper extends the previous virtual synchronous generator (VSG) control for voltage-source converters to modular multilevel converters (MMCs). Compared with the ac synchronous generator (SG), the VSG-based MMC is embedded with a power-angle characteristic. Starting from this feature and with reference to the existing ac system coherency-based equivalence methods, this paper proposes a novel coherency equivalence method for MMC used in large-scale renewable energy systems connected to the ac grid. This novel method mainly focuses on the coherency criterion and parameter aggregation methods which have significant differences compared with the ac system methods. The proposed equivalence method is validated on PSCAD/EMTDC and the study results indicate that: 1) the VSG-based MMC model does show the power-angle characteristic similar to the SG model; 2) the proposed coherency criterion can accurately and efficiently classify the paralleled MMC into coherent groups; and 3) the dynamic behaviors of the external systems are preserved after the aggregations of all previous coherency MMC groups.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".