Three-Phase and Single-Phase p-q Theories Applied to Three-Phase Shunt Active Power Filter under Different Operating Conditions: A Comparative Evaluation
Bibliographic record
Abstract
This paper deals with a shunt active power filter (APF) realized using three-phase p-q (3-φ p-q) theory and single-phase p-q (1-φ p-q) theory approaches. A comparative evaluation between two p-q theories, applied to three-phase three-wire system, is presented. An in-depth simulation study is carried out for better understanding of the concepts and to explore the factors that affect the performance of both the theories. A shunt APF system is developed and tested using a DSP DS1104 of dSPACE. An extensive experimental investigation is carried out under balanced and/or unbalanced supply voltages, and balanced and/or unbalanced load conditions. It is found that both the p-q theories perform well under balanced supply voltages and balanced non-linear load condition, but, their performance degrades when supply voltages are highly distorted. The 3-φ p-q theory has advantage over 1-φ p-q theory when the load is unbalanced in nature. However, under unbalanced voltages, 3-φ p-q theory fails to demonstrate its ability to compensate the load current harmonics and reactive power, whereas, 1-φ p-q theory gives better performance.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".