Adaptive active filter for interfacing wind-power DGs to distribution systems
Bibliographic record
Abstract
Wind-power distributed generation (DG) converters may inject considerable amount of harmonics into their connected distribution systems that could exceed its connected utility tolerance or IEEE 1547 Std. limits. This paper presents a new adaptive harmonics detection active (AHDA) filter that is designed to suppress harmonics produced by wind DG converters. The AHDA filter consists of an inverter of industrial-proven configurations, controlled using a new adaptive noise cancellation (ANC) algorithm and implemented with state-of-the-art digital signal processing technology. The ANC algorithm is based on a novel noise cancellation theory that was originally created for image signal processing but not for power engineering. This paper presents a practical formulation of the ANC algorithm for harmonics elimination at utility-DG interfaces, with significant simplification of the original complex formulation for noise cancellations. Hardware and software implementations of the AHDA filter are detailed. Simulation and experimental results are provided to demonstrate the effectiveness of the AHDA filter.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".