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A Complete Internal Voltage-Based RMS Model of Grid-Connected VSC for Weak Grid Instability Studies

2024· article· en· W4404295544 on OpenAlexaff
Tao Xue, Mingxuan Zhao, Zahid Javid, Xinquan Chen, Ilhan Koçar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsGridInstabilityComputer scienceControl theory (sociology)VoltagePower gridElectrical engineeringMechanicsPhysicsEngineeringMathematicsPower (physics)GeometryArtificial intelligence

Abstract

fetched live from OpenAlex

Root mean square (RMS) simulation is resource- efficient compared to electromagnetic transient (EMT) simulation, so it is widely used in transient stability studies of large-scale power systems. However, its applicability in studying weak grid instability under the influence of renewables requires further research while improving the mapping of models in different solvers. This paper aims to bridge this gap. A complete internal voltage-based RMS model of voltage source converter (VSC) is proposed with consideration of the outer and inner loop controls, phase locked loop and the DC-side dynamics to improve the existing RMS models. Then the performance of the proposed model is compared against EMT simulations in a test system subject to weak grid instability. The simulation results show that the proposed RMS model of VSC can regenerate the weak grid instability phenomenon with accurate resonance frequency with more conservative stability boundaries.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.053
GPT teacher head0.280
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), 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
Published2024
Admission routes1
Has abstractyes

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