Grid Synchronization PLL Based on Cascaded Delayed Signal Cancellation
Bibliographic record
Abstract
During the grid synchronization of distributed generation (DG) units, phase-locked loop (PLL) is well accepted as an efficient approach to detect grid phase angle. Conventional PLL schemes used in DG controller have to compromise between steady-state accuracy and transient dynamics when grid voltage is polluted by unbalance and harmonics. To simultaneously realize good steady-state and transient performances, this paper proposes a general delayed signal cancellation (DSC) operator, which can be tailored to eliminate any specified harmonic. The proposed DSC operator can be further cascaded to stepwise reject all undesired harmonics. Then the conditioned voltage signal can be used in PLL loop to achieve fast transient response at high control bandwidth without suffering from the steady-state error caused by harmonics. Based on differently configured DSC operators, two PLL designs are then developed, namely CDSC-PLL1 and CDSC-PLL2. Specifically, CDSC-PLL1 is aimed for grid voltage with unbalance and odd/even harmonics, while CDSC-PLL2 further addresses asymmetrical harmonics, i.e., harmonics arising from asymmetrically distorted three-phase voltages. By introducing a frequency feedback loop, the proposed PLL can operate properly during considerable frequency variations, even when a phase jump or severe harmonics are also present. All proposed PLL designs have very simple structure and can be easily implemented. The superior performance is confirmed by experimental 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 | 0.000 |
| 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".