A Norton Model of a Distribution Network for Harmonic Evaluation
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Bibliographic record
Abstract
This paper presents a Norton model for modelling distribution networks where the system configuration is not fully known. Traditionally harmonic studies use complex distribution networks modelled by harmonic current sources for specific frequencies. Although this model has been proved to be adequate for some studies, this may not be adequate for other applications. When changing the operating conditions of the supply-side system, the harmonic currents injected by the distribution network might change and to investigate these harmonic currents, the Norton model is used. The change of operating condition is obtained by switching shunt capacitors. The estimated model can be used to analyze, for example, the effect of harmonic filters under different supply system configurations or operating conditions. The method of estimating the Norton models is illustrated on a test system, simulated on the well-known simulation program EMTP-ATPDraw. Key words : Norton model; Distribution network; Operating conditions; Harmonic currents and voltages
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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 it