Systematical Investigation of Transient Response and Fault Clearing Angle Estimation for Delay-Based PLL Inverters During Grid Fault
Bibliographic record
Abstract
For grid-following inverters, the phase-locked loop (PLL) plays a critical role in ensuring transient stability. From the perspective of safe and robust operation, the inverter must remain stable throughout the entire transient process, including during and after grid fault. However, previous research has not provided a systematic and comprehensive analysis of the entire transient response during fault events. This article offers a detailed study of the transient stability of grid-following inverters, combining the equal area criterion with the phase portraits method that accounts for the frequency-dependent impedance. The analysis classifies the system's dynamic behavior into five distinct cases, revealing new phenomena not previously explored, including the identification of an unstable region that emerges after fault recovery, which can lead to system instability. To mitigate this issue, an advanced method for estimating the fault clearing angle is proposed, extending the traditional single-interval approach to multiple intervals, thereby enhancing transient stability during fault recovery. The proposed method and findings are validated through experimental tests on a single-phase grid-connected inverter, confirming their effectiveness and relevance during fault processes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".