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Stability Analysis of a Remote DC Subgrid/Microgrid Connected to a Very Weak AC Grid

2021· article· en· W3198918630 on OpenAlexafffund
Saeed Rezaee, Amr Radwan, Mehrdad Moallem, Jiacheng Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrogridElectrical impedanceGridVoltage sourceRectificationControl theory (sociology)Topology (electrical circuits)VoltagePhysicsComputer scienceElectrical engineeringEngineeringMathematicsGeometry

Abstract

fetched live from OpenAlex

Instability issues can arise due to the high penetration of remote voltage source converter (VSC)-interfaced DC microgrid (MG) to the ac weak grid (WG), in which the grid impedance is large. This is due to the dynamic interaction between the VSCs and the WG impedance. In this work, a small-signal analysis is conducted to derive the full-order linearized model of the VSC-WG interconnection. Furthermore, a participation factor analysis is presented to identify the effect of varying the grid impedance on the VSC-WG dominant modes in the inversion and rectification modes of operation. It is found that although the system is initially stable in both modes, it tends to move toward the unstable region when the grid impedance increases. In this study, the initial locations of the corresponding dominant eigenvalues are fairly similar for both modes. However, unlike previous works, it is shown that the dominant modes in the rectification mode are much more sensitive to the grid impedance variation than the inversion mode. Time-domain simulations are conducted on a 7.25 MW dc MG which is interfaced to the ac grid via a VSC system to verify the validity of small-signal analysis in both modes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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.

Study designBench or experimental
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
Published2021
Admission routes2
Has abstractyes

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