Optimised harmonic elimination modulation extended to four‐leg neutral‐point‐clamped inverter
Bibliographic record
Abstract
Uninterruptible power supply (UPS) is the promising candidate to ensure high quality of delivering power from renewable energy resources to the AC loads especially sensitive and critical ones. In this study, optimised harmonic elimination modulation technique is extended to four‐leg neutral‐point‐clamped (NPC) with neutral point voltage balancing and it has been experimentally validated. It is demonstrated that by controlling the fourth leg to eliminate more harmonics while operating at low switching frequency makes the four‐wire NPC an ideal candidate for an UPS application in energy conversion systems. Non‐triplen, 5th to 23rd harmonics orders from the output voltage waveforms are eliminated by optimally computing the switching angles for phase legs. Moreover, switching angles computed for the fourth leg are also considered to help removing triplen harmonics containing 3rd, 9th, 15th, and 21st orders from phase voltages. It is mathematically proved that the designed selective harmonic elimination technique ensures the neutral point voltage balancing. The obtained experimental results confirm the proper performance of the proposed technique in supplying symmetrical/asymmetrical loads from renewable energy resources while keeping the inverter neutral point voltage balanced.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".