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Record W2129129019 · doi:10.1109/tpel.2013.2278716

An Active Damper for Stabilizing Power-Electronics-Based AC Systems

2013· article· en· W2129129019 on OpenAlexaff
Xiongfei Wang, Frede Blaabjerg, Marco Liserre, Zhe Chen, Jinwei He, Yunwei Li

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Alberta
FundersEuropean Commission
KeywordsConvertersPower electronicsDamperElectrical impedanceElectrical engineeringGridEngineeringElectronicsElectronic engineeringPower (physics)Computer scienceControl theory (sociology)Control engineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

The interactions among the parallel grid-connected converters coupled through the grid impedance tend to result in stability and power quality problems. To address them, this paper proposes an active damper based on a high bandwidth power electronics converter. The general idea behind this proposal is to dynamically reshape the grid impedance profile seen from the point of common coupling of the converters, such that the potential oscillations and resonance propagation in the parallel grid-connected converters can be mitigated. To validate the effectiveness of the active damper, simulations and experimental tests on a three-converter-based setup are carried out. The results show that the active damper can become a promising way to stabilize the power-electronics-based ac power systems.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.205
Teacher spread0.200 · 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

Citations359
Published2013
Admission routes1
Has abstractyes

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