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Record W2612088944 · doi:10.1109/icit.2017.7913060

Comparative assessment of three-phase transformerless grid-connected solar inverters

2017· article· en· W2612088944 on OpenAlexaff
Deepak Ronanki, Phuoc Huynh Sang, Vijay K. Sood, Sheldon S. Williamson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsGalvanic isolationPulse-width modulationInverterPhotovoltaic systemElectronic engineeringHarmonicsCommon-mode signalComputer scienceSolar micro-inverterGrid-connected photovoltaic power systemThree-phaseElectrical engineeringMaximum power point trackingVoltageEngineeringTopology (electrical circuits)Transformer

Abstract

fetched live from OpenAlex

Solar energy is a promising alternative energy source for a sustainable pollution-free future. Due to the requirements of high efficiency, reliability, power density and low cost, transformerless PV inverters can be utilized in a grid-connected solar energy system. However, this suffers from no galvanic isolation and leakage currents through the stray capacitances between the PV array and the ground which results in some degradation of the system's performance as well as safety issues. This paper performs a comprehensive review and comparison of the performance of different 3-phase inverter topologies combined with different pulse width modulation (PWM) schemes in transformerless PV systems. Moreover, a modified discontinuous PWM technique was proposed for an H8 inverter to reduce leakage currents in this paper. The analysis was carried out for 50 kW PV inverters. The key performance of each inverter topology such as common mode voltages (CMVs), leakage currents, current harmonics and efficiency are holistically evaluated by using simulation results. Also, the merits and demerits of each system are highlighted.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.025
GPT teacher head0.294
Teacher spread0.269 · 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

Citations14
Published2017
Admission routes1
Has abstractyes

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