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Record W4391559661 · doi:10.1109/tia.2024.3362916

Response of MMC-HVDC Systems to Geomagnetic Disturbances

2024· article· en· W4391559661 on OpenAlexafffund
Hamzeh Hosseinpour, Afshin Rezaei‐Zare

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2024
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEarth's magnetic fieldControl theory (sociology)ChemistryComputer sciencePhysicsControl (management)Magnetic field

Abstract

fetched live from OpenAlex

This paper presents a detailed investigation of the performance of MMC-based HVDC systems in the event of a solar Geomagnetic Disturbance (GMD). Detailed models of an MMC and submodules are used to acquire the accurate behavior of the MMC during GMDs. Under such conditions, the current harmonics arising from the DC shift in the transformer flux are distributed between the MMC and grid, distorting the current and voltage waveforms. In this study, a model for the distribution of the current harmonics is developed. It is revealed that the distribution of the second harmonic current is affected not only by the MMC impedance but also by the output current and voltage of the converter. The simulation results in the EMTP show that with the constant power factor control strategy, the MMC does not respond to the increase in reactive power consumption by the transformer. Consequently, a solution approach is proposed to minimize the contribution of the grid to the reactive power demand increase. This control approach provides the saturated transformer with reactive power through the MMC, improving the grid voltage stability. The proficiency of the proposed solution is verified through time-domain simulations.

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: none
Teacher disagreement score0.927
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.244
Teacher spread0.232 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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