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A Dynamic Series Voltage Regulator for Load Protection in Bipolar DC Power System

2022· article· en· W4313562830 on OpenAlexaff
Ramin Babazadeh‐Dizaji, Mohammad Hassan Ghaderi, Mohsen Ghafouri, Mohsen Hamzeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsConcordia University
Fundersnot available
KeywordsConvertersVoltageElectromagnetic coilVoltage regulatorElectric power systemVoltage regulationElectrical engineeringEngineeringAC powerLow-dropout regulatorElectronic engineeringComputer sciencePower (physics)Dropout voltagePhysics

Abstract

fetched live from OpenAlex

The low-voltage DC distribution systems are comprised of various components with a wide range of power ratings. In such systems, compared with unipolar configurations, bipolar structures bring considerable superiority in terms of efficiency, safety, and compatibility. However, the scarcity of protection methods has restricted the expansion of bipolar DC grids. In line with this trend, this paper presents a dynamic series regulator (DSVR) for the protection of sensitive loads in bipolar DC distribution systems. The proposed DSVR injects dynamic voltage for a set of selected sensitive loads to suppress the probable voltage abnormalities in the system. Therefore, it provides desirable satisfaction of voltage quality metrics in bipolar DC power systems. The proposed DSVR is composed of a multi-active bridge converter with one primary and two secondary windings followed by two full-bridge DC-DC converters. To evaluate the feasibility and effectiveness of the proposed concept, various simulations of several case studies are carried out in the PLECS (Plexim) software.

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: none
Teacher disagreement score0.802
Threshold uncertainty score0.320

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 head0.003
GPT teacher head0.161
Teacher spread0.158 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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