Active Damping Control of a High-Power PWM Current-Source Rectifier for Line-Current THD Reduction
Bibliographic record
Abstract
The use of active damping to reduce the total harmonic distortion (THD) of the line current for medium-voltage (2.3-7.2 kV) high-power pulsewidth-modulation (PWM) current-source rectifiers is investigated. The rectifier requires an LC filter connected at its input terminals, which constitutes an LC resonant mode. The lightly damped LC filter is prone to series and parallel resonances when tuned to a system harmonic either from the utility or from the PWM rectifier. These issues are traditionally addressed at the design stage by properly choosing the filter resonant frequency. This approach may result in a limited performance since the LC resonant frequency is a function of the power system impedance, which usually varies with power system operating conditions. In this paper, an active damping control method is proposed for the reduction in line current THD of high-power current-source rectifiers operating at a switching frequency of only 540 Hz. Two types of LC resonances are investigated: the parallel resonance excited by harmonic currents drawn by the rectifier and the series resonance caused by harmonic pollution in the source voltage. It is demonstrated through simulation and experiments that the proposed active damping control can effectively reduce the line-current THD caused by both parallel and series resonances.
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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".