Robust Vector Control of a Very Weak-Grid-Connected Voltage-Source Converter Considering the Phase-Locked Loop Dynamics
Bibliographic record
Abstract
Conventional vector-controlled voltage-source converters (VSC) suffer from stability and performance problems when integrated into very weak ac grids (high-impedance grids). This is attributed to the increased coupling between the converter and grid dynamics, via the phase-locked loop (PLL), at the very weak-grid condition. In the current literature, the impact of the PLL is usually ignored when the converter controllers are designed. While this approach can be accepted under stiff grid conditions, it yields unmodeled dynamics that destabilize the converter under weak-grid conditions and high-power injection levels. To overcome this limitation, this paper presents a robust vector-controlled VSC that facilitates full converter power injection at weak and very weak-grid conditions (i.e., when the short-circuit capacity ratio is one). To realize the controller, first, a detailed dynamic model for the ac-bus voltage dynamics, including the PLL dynamics, is developed and validated in this paper. Second, the model is used to optimally design a robust ac-bus voltage controller to stabilize the dynamics under operating point variation and grid impedance uncertainty. Because the developed model includes the PLL dynamics, the developed controller inherently stabilizes the negative impact of the PLL on the converter stability. A theoretical analysis and comparative simulation and experimental results are provided to show the effectiveness of the proposed controller.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".