Optimal design of inductor and DC bus voltage for shunt active filter
Bibliographic record
Abstract
This paper proposes two methods for optimal design of DC bus reference voltage (V <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dcref</inf> ) and an optimal selection of the shunt active filter (SAF) inductor. The proposed methods help to reduce the filter rating, devices stress and increase the performance of the SAF. An optimal choice of the inductor of the SAF is presented based on the slope calculation of the SAF current which was demonstrated to be greater than the slope of the nonlinear load current. Moreover, the adaptation of the DC reference voltage which is a function of the amplitude of total load current harmonics and load reactive current is developed and the latter offer important advantage in terms of losses reduction in the converter switches leading to a more accurate design of the SAF. To achieve these goals, the first developed method is based on the direct calculation of the maximum SAF voltage to determine the minimum DC bus voltage reference; while the second method is based on the estimation of the maximum voltage of the SAF through a control technique developed and applied to the model of the SAF. For validation purposes, the proposed methods were simulated. The simulation results validate the approach in terms of source current compensation, THD reduction, as well as the correction of power factor.
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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 | 0.001 | 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 | 0.001 |
| 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".