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Record W1997175287 · doi:10.1109/iecon.2013.6699111

Crossover Switches Cell (CSC): A new multilevel inverter topology with maximum voltage levels and minimum DC sources

2013· article· en· W1997175287 on OpenAlexaff
Hani Vahedi, Kamal Al‐Haddad, Youssef Ounejjar, Khaled E. Addoweesh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsPhotovoltaic systemVoltageSwitched capacitorCapacitorTopology (electrical circuits)Voltage regulationElectrical engineeringRenewable energyComputer scienceCrossoverElectronic engineeringEngineering

Abstract

fetched live from OpenAlex

Renewable energy resources are widely used because of providing green and economic energy for the consumers. Multilevel inverters generates low harmonic waveforms at the output, therefore they are most suitable for energy conversion to deliver efficient power to the loads from renewable energy sources like photovoltaic systems. In this paper a new dc source less topology has been introduced for multilevel inverters. It uses crossover switches to generate the maximum output voltage levels. The Crossover Switches Cell (CSC) multilevel inverter can generate all possible voltage level among the DC supply and regulated DC voltage capacitor. A voltage controller has been proposed to keep the DC capacitor voltage regulated in case of load changes. The simulation results prove the capability of CSC in producing maximum voltage levels as well as the controller ability in balancing the capacitor voltage even if the DC supply voltage changes.

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)0.000
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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.192
Teacher spread0.178 · 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
GenreMethods

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

Citations84
Published2013
Admission routes1
Has abstractyes

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