Parallel/Series Connected Standardized Active Switching Modules for High Power DCCBs in MVDC Networks
Bibliographic record
Abstract
Solid-state dc circuit breakers (DCCBs) are increasingly employed across all power levels, including MVdc networks. Seamless integration of DCCBs into medium voltage direct current (MVdc) networks is challenging due to the diverse voltage and power levels. Furthermore, the limited current and voltage capability of semiconductor devices limits the full integration of solid-state DCCBs for MVdc applications. Series and parallel-connected insulated-gate bipolar transistor (IGBT) arrays can be employed to match the current and voltage levels required. However, with passive gate drives, devices may fail due to non-homogeneous current and voltage distribution across IGBTs. Closed-loop active gate drives (AGDs) provide a solution to overcome this. In the proposed standardized-active switching module (ASM) scheme, IGBTs are equipped with AGDs with status feedback. This control method enables the IGBTs to follow a defined current/voltage trajectory during the switching rather than being guided by the inherent characteristics of the device. Hence, with the ability to control dynamic current and voltage, an additional degree of freedom is enabled to connect several ASMs in series and parallel. DCCB architecture based on Standardized-ASMs is proposed as a flexible protection solution for MVdc networks. This paper describes the developed AGD scheme and behavioral analysis of the AGD-based ASMs. Experimental results show the dynamic voltage and current slope control capability of the proposed standardized ASMs. Finally, this paper assesses the ASM-based DCCB architecture for MVdc networks. An ASM-based DCCB prototype was developed and tested to verify the voltage and current sharing capability of modular ASMs in the proposed DCCB architecture.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".