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Record W4382568064 · doi:10.1109/tpwrd.2023.3290928

Passive Lumped Model With Frequency-Dependent Parameters for Multiconductor DC Cables

2023· article· en· W4382568064 on OpenAlexafffund
Milad Ghazizadeh, Anestis Dounavis, Firouz Badrkhani Ajaei

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrogridTransient (computer programming)Dependency (UML)EngineeringEquivalent circuitElectronic engineeringFrequency responseControl theory (sociology)Transient responseVoltageComputer scienceElectrical engineering

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.227
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2023
Admission routes2
Has abstractyes

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