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Record W1996734982 · doi:10.1109/intlec.2014.6972193

Ensuring dynamic stability of constant power loads in DC telecom power systems and data centers using active damping

2014· article· en· W1996734982 on OpenAlexaff
Oleksandr Pizniur, Zhenyu Shan, Juri Jatskevich

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConvertersPower (physics)Electric power systemElectrical impedanceControl theory (sociology)Reliability (semiconductor)VoltageEngineeringElectrical engineeringComputer scienceElectronic engineeringPhysics

Abstract

fetched live from OpenAlex

DC distribution is becoming increasingly important in telecom and buildings' power systems. The main building blocks of DC power systems are switching power converters and rectifiers that have nonlinear characteristics. When the voltages are tightly regulated, the converters will act as constant power loads (CPLs). The CPL is known to exhibit the negative incremental impedance and may cause the dynamic instability of the system. The problem associated with CPLs is traditionally tackled using passive damping which has serious drawbacks such as increased size, decreased reliability and efficiency of the system. This paper introduces an active method to inject damping current into the power bus employing an auxiliary power circuit. The proposed approach ensures that the system operates with sufficient stability margin in a small-signal sense. Comparing with previous works, the advantage of the proposed damping circuit is that the absorbed energy for damping is transferred into a neighboring bus with minimal energenergyy losses.

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: Empirical
Teacher disagreement score0.479
Threshold uncertainty score0.445

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 head0.012
GPT teacher head0.223
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

Citations12
Published2014
Admission routes1
Has abstractyes

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