A new fuzzy-based representative quality power factor for unbalanced three-phase systems with nonsinusoidal situations
Bibliographic record
Abstract
The summary form only given. Under ideal sinusoidal operating conditions, the definition of power factor for single-phase and balanced three-phase systems is unique and meaningful. However in non-sinusoidal situations and/or unbalanced three-phase system operation, different power factors have been proposed to deal with these situations. In this paper a new fuzzy based representative quality power factor (RQPF) is introduced to represent three recommended power factors, fundamental positive sequence power factor (FPSPF), transmission efficiency power factor (TEPF) and oscillation power factor (OSCPF). In addition, the problem of defining power factor for three-phase system is formulated and the RQPF module is explained. In order to test the validity of the proposed fuzzy based module, the RQPF is applied to different cases, balanced, unbalanced, linear, nonlinear, sinusoidal and non-sinusoidal. The obtained results reveal that the new RQPF is meaningful and accurately represents the existing power factors in all cases and in all situations. Taking into consideration the advantages of fuzzy systems, this factor is useful for power quality evaluation, cost-effective analysis of PQ mitigation techniques and as well billing purposes in these situations.
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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".