Resonance Damping and Harmonic Suppression for Grid-Connected Current-Source Converter
Bibliographic record
Abstract
Due to the inductor-capacitor (LC) filter, a pulsewidth-modulation (PWM) current-source converter may experience LC resonance. The resonance can be excited by system harmonics either from the PWM process or from the grid voltage distortions and hence results in the line current distorted. In this paper, feedback controls using different variables in the LC filter are first investigated and comprehensively analyzed. It is shown that the inductor-voltage feedback or the capacitor-voltage feedback can damp the current oscillations by increasing the damping ratio, while the inductor-current feedback or the capacitor-current feedback is able to suppress low-order harmonics by raising the resonance frequency. On this basis, a group of combined variable feedback control methods is presented by combining the feedbacks of the inductor/capacitor current and the inductor/capacitor voltage. Thus, not only the current oscillations can be damped, but also the low-order harmonics can be suppressed. Therefore, the line current waveform is improved, and the system performance can be flexibly optimized. A practical design method for feedback gains is also presented in this paper. Finally, the simulation and experimental results verify the feasibility and validity of the proposition.
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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 | 0.000 | 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".