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Record W1967881232 · doi:10.1109/ccece.2008.4564895

Modelling and analysis of parallel operated inverters

2008· article· en· W1967881232 on OpenAlexaffvenue
Nacer Benaifa, Hussain Bierk, Babatunde Adedotun Ajayi, E.P. Nowicki

Bibliographic record

VenueConference proceedings - Canadian Conference on Electrical and Computer Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsInterfacingTotal harmonic distortionPulse-width modulationElectronic engineeringComputer scienceHarmonicHarmonic analysisMATLABInverterReduction (mathematics)Modulation (music)Equivalent circuitThree-phaseTopology (electrical circuits)Electrical engineeringEngineeringVoltageMathematicsPhysicsAcousticsComputer hardware

Abstract

fetched live from OpenAlex

Renewable energy sources are quickly becoming incorporated into increasingly distributed electrical utility grids. An ever present issue when interfacing these sources is that of harmonic distortion reduction at the inter-tie point. Presented in this paper is the modeling and analysis of a rarely employed technique for harmonic reduction using synchronized phase shifted parallel PWM inverters with current-sharing reactors [1-4]. A main contribution of this paper is the introduction of parallel inverters equivalent circuit model that permits any number of inverters operated in parallel to be analyzed with accuracy, simplicity and ease. The validity of the results obtained using this equivalent is investigated analytically and simulated using MATLAB/Simulink and PSpice for one, two and three parallel phase-shifted inverters using double-edge asymmetrical RSPWM modulation with various modulation indices and carrier to reference frequency ratios.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.026
GPT teacher head0.182
Teacher spread0.157 · 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

Citations1
Published2008
Admission routes2
Has abstractyes

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