Parallel interfacing converters under unbalanced voltage: Active power oscillation cancellation with peak current sharing
Bibliographic record
Abstract
Unbalanced voltage has adverse effects on power electronic interfacing converters (IFCs) operation such as output power oscillations, DC link voltage oscillations and peak current increase. These adverse effects can be aggregated in parallel IFCs with common DC and AC link, which are commonly used to connect AC and DC subsystems in hybrid AC/DC microgrid or to interface high-power distributed generations/storage elements to AC subsystem. In this paper, two novel control strategies for parallel IFCs operation under unbalanced voltage are proposed, which are focusing on active power oscillation cancellation and sharing of collective peak current of parallel IFCs among IFCs considering their power ratings. In the first proposed control strategy, IFCs' power coefficient factors are controlled for cancellation of active power oscillation and collective peak current sharing of parallel IFCs. In the second proposed control strategy, IFCs' peak currents are controlled for controlling targets. In this paper, individual and parallel IFCs' peak currents are thoroughly studied, and their relationship with active power oscillation cancellation are analyzed. Based on analysis, it is proven that collective peak current of parallel IFCs is constant under zero active power oscillation in the fixed average active powers output. Both proposed control strategies ensure the peak currents of individual IFCs to be approximately in-phase with collective peak current of parallel IFCs, which provide minimum peak currents summation of IFCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 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".