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Record W4378187409 · doi:10.14447/jnmes.v26i1.a02

Implementation of an Asymmetric Multilevel Inverter for Solar Photovoltaic Applications Using N-R Approach

2023· article· en· W4378187409 on OpenAlexvenueno aff
Devineni Gireesh Kumar, Neerudi Bhoopal, Aman Ganesh, Nagineni Venkata Sireesha, DSNM Rao

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2023
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemInverterComputer scienceMaterials scienceEngineering physicsEnvironmental sciencePhysicsEngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

Two-level inverters are the most basic kind of multi-level inverter (MLIs).Total harmonic distortion diminishes as the number of output levels is increased.In classic MLI topologies, more electronic components are utilized to get higher-level outputs, which raises the cost, complexity, and volume of typical MLI installations.By reducing the use of power components, overall costs can be reduced.Further, the two and three-level inverters produce constant dv/dt output, which increases the stress on the power switches.This research proposed an asymmetric MLI topology that is suitable for PV applications and utilizes a minimum number of components.A selective harmonic elimination-based pulse width modulation (SHEPWM) is implemented for the proposed inverter to eliminate the lower-order dominant harmonics.The non-linear transcendental equations produced by the SHEPWM are solved for the switching angles of the proposed inverter using the Newton-Raphson approach.The performance of the inverter is analyzed based on the THD of output for different operating levels of the inverter.In this research, the NR method yielded a THD of 7.3% at a 0.9 modulation index.Also, the proposed inverter is applied to grid-connected solar PV systems for the analysis of THD.T The THD of the grid voltage is measured as 0.06% and the THD of the grid current is 4.8% with the proposed inverter which is acceptable as per the IEEE519 standards.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.542
Threshold uncertainty score0.620

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 head0.038
GPT teacher head0.300
Teacher spread0.261 · 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 designBench or experimental
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

Citations6
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of New Materials for Electrochemical SystemsSame topicMultilevel Inverters and ConvertersFrench-language works237,207