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Record W3040491283 · doi:10.1109/jestpe.2020.3007556

A Novel Transformerless Single-Stage Grid-Connected Solar Inverter

2020· article· en· W3040491283 on OpenAlexafffund
Sivanagaraju Gangavarapu, Manish Verma, Akshay Kumar Rathore

Bibliographic record

VenueIEEE Journal of Emerging and Selected Topics in Power Electronics · 2020
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInverterPhotovoltaic systemInductorGrid-tie inverterFlyback transformerSolar micro-inverterControl theory (sociology)Maximum power point trackingElectronic engineeringVoltageComputer scienceEngineeringElectrical engineeringTransformer

Abstract

fetched live from OpenAlex

A novel tranformerless single-stage grid-connected solar inverter with a combination of a bidirectional dc/dc boost converter followed by a flyback inductor inverter is proposed. The inverter shares a common ground with the photovoltaic (PV) panel and the grid, which realizes a zero leakage current and it is the most desired feature in transformerless inverters. Further, the proposed inverter provides the boost voltage operation, hence it does not require a second stage which decreases the system cost and increases the system reliability. The other advantage of the proposed inverter is that it provides both the symmetrical positive voltage gain and negative voltage gain, which allows to use simple sinusoidal pulsewidth modulation technique for realizing the ac sinusoidal output voltage. The proposed inverter steady-state operation and the design equations are presented in detail. The converter dynamic model is developed using state-space averaging approach, and a proportional resonant current controller is designed for inverter closed-loop operation with the grid. The presented analysis and the design are verified with both the simulation and experimental results.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.243
Teacher spread0.223 · 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 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

Citations37
Published2020
Admission routes2
Has abstractyes

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