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Record W4413279862 · doi:10.3390/en18164400

Numerically Enhanced Interfacings for Average-Value Models of Voltage-Source Converters in Nodal-Based EMT Simulators

2025· article· en· W4413279862 on OpenAlexaff
Seyyedmilad Ebrahimi, Juri Jatskevich

Bibliographic record

VenueEnergies · 2025
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConvertersNODALVoltageValue (mathematics)Electrical engineeringComputer scienceElectronic engineeringMathematicsEngineeringStatisticsMedicineInternal medicine

Abstract

fetched live from OpenAlex

Efficient simulations of converter-dominated power systems and microgrids significantly rely on average-value models (AVMs) of the converters. The conventional AVMs of voltage-source converters (VSCs) typically require a time-step delay for interfacing with the external circuits in non-iterative nodal-based electromagnetic transient (EMT) programs. This time-step relaxation may lead to numerical inaccuracy and/or instability for simulations with large time-step sizes. This paper presents several alternative formulations and interfacing techniques for AVMs of VSCs, which eliminate undesirable time-step delays and result in robust and reliable interfaces that allow simulations at large time steps without significant compromise in numerical accuracy. This is achieved by formulating the VSCs as conductance matrices (and history terms), which are computed simultaneously with the solution of the external network. The advantages of the proposed techniques over the conventional methods are demonstrated in simulations of a VSC-dominated power system using the EMT program PSCAD.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.620
Threshold uncertainty score0.673

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 head0.005
GPT teacher head0.216
Teacher spread0.211 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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