Analysis and Active Suppression of AC- and DC-Side Instabilities in Grid-Connected Current-Source Converter-Based Photovoltaic System
Bibliographic record
Abstract
Current source converters (CSCs) can be a viable option to interface large photovoltaic (PV) systems to the utility grid. However, interaction dynamics in both the ac- and dc-sides might be yielded and affect the converter stability. 1) On the ac side, interactions of the grid impedance with the LC ac-side filter might cause uncertain resonant frequency modes that should be damped without affecting the converter efficiency. 2) On the dc-side, under uncertain characteristics of the PV source impedance (e.g., number of PV modules connected and/or uncertainty in source circuit parameters), the Nyquist stability criterion might be violated due to equivalent source/load impedance mismatch. Moreover, the real part of the dc impedance of the CSC can be negative which contributes to instabilities of the PV system. In this paper, the ac-side LC filter dynamics are robustly damped by an improved active compensator in the control structure of the CSC. More importantly, the dc-side interactions dynamics are effectively stabilized by proposing active reshaping techniques for the dc impedance of the CSC so that the Nyquist stability criterion is maintained and positive damping is added. Time-domain model is implemented under Matlab/Simulink environment to validate the analytical results.
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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 | 0.001 |
| 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 | 0.000 |
| 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".