A multiport power-flow controller for DC transmission grids
Bibliographic record
Abstract
This paper proposes an m-port converter structure for high-voltage dc (HVDC) applications to facilitate power-flow routing between k controlled dc buses and m-k independent dc networks. Power-flow control is achieved via the injection of incremental dc voltages between the networks; thus, the converter structure is only rated for a fraction of the rated power and voltage of the connecting dc networks. Unlike previously proposed dc power-flow devices, these incremental dc voltages are generated without requiring power exchange with an external ac network. There are four variants of the structure, each offering unique advantages for deployment. These variants, and the modules that comprise them, are presented. A sample simulation case study is performed to demonstrate three-port bidirectional power-flow control between networks of similar voltage (495/500/505 kV). The proposed converter structure is shown to route power between the networks using modules with megavolt-ampere ratings of approximately 2% of the transmitted power. Thus, the proposed converter structure offers a highly cost-effective means of routing and controlling dc power flows within emerging HVDC grids.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".