Frequency adaptive pre filtering stage for differentiation based control of shunt active filter under polluted grid conditions
Bibliographic record
Abstract
A differentiation based control method for a shunt active power filter is used in this paper for functioning in the presence of grid voltage distortion and imbalance. To enable the fast and accurate estimation of the variables in the presence of unbalancing or distortion in the grid voltages, a pre-filtering scheme is considered based on the dual second order generalized integrator (DSOGI) approach. The signal recomposition performed by the pre-filter isolates the harmonics from the voltage and current waveforms, and the differentiation FLL (dFLL) is able to estimate the frequency of the waveforms which is used as a feedback for the pre-filter, thus making the system frequency adaptive. The control algorithm is validated with both simulation studies and a hardware prototype of a active power filter carrying out current compensation robustly, demonstrating the speed and accuracy of the system under grid voltage distortions and maintaining less than 5% supply current total harmonic distortion THD as dictated by IEEE Std. 519-2014.
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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 | 0.001 |
| 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".