Passive Lumped Model With Frequency-Dependent Parameters for Multiconductor DC Cables
Bibliographic record
Abstract
This article introduces a lumped model for multiconductor DC cables, i.e., cables with sheaths and/or armours. The developed model takes into account the frequency-dependency of per-unit-length resistances and inductances and is guaranteed to be passive. Transient analyses of faults in a DC microgrid are conducted where the introduced model is compared with the Frequency-Dependent Phase (FDP) model of PSCAD and the conventional PI model. It is shown that for electrically short DC cable systems with sheaths and/or armours the proposed model is computationally more efficient than the FDP model. The results also highlight the inherent limitation of the PI model in representing the frequency-dependent behavior of DC cables and demonstrate that the proposed model is more accurate than PI models developed at different frequencies. This article also presents a methodology to realize a passive circuit model using the Kron-reduced per-unit-length parameters.
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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".