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Record W1577827995 · doi:10.1109/ias.2002.1042800

A modular photo-voltaic grid-connected inverter based on phase-shifted-carrier technique

2003· article· en· W1577827995 on OpenAlexaff
Xuanyuan Wang, Mehrdad Kazerani

Bibliographic record

VenueConference Record of the 2002 IEEE Industry Applications Conference. 37th IAS Annual Meeting (Cat. No.02CH37344) · 2003
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhotovoltaic systemWaveformInverterModular designElectronic engineeringMaximum power point trackingComputer scienceTopology (electrical circuits)Power (physics)GridGrid-connected photovoltaic power systemElectrical engineeringThree-phaseEngineeringVoltagePhysicsMathematics

Abstract

fetched live from OpenAlex

Residential photovoltaic grid-connected inverters are modular distributed power generation devices that convert the DC power from the roof-top solar panels to high-quality AC power at the utility grid interface. In this paper, the phase-shifted-carrier technique, which is normally used in high power multi-converter schemes, is applied to a modular grid-connected inverter to improve the output current waveform. First, it is shown, through analysis and simulation, that in the commonly-used photovoltaic grid-connected inverter topology, based on the phase-shift modulated full-bridge converter, the well-known rule of the phase-shift between the carrier signals of the adjacent modules is not valid for both odd and even number of modules. Then, a new general rule for the phase-shift is proposed, and finally, the validity of the proposed rule and its effect on the improvement of the quality of the output current waveform are verified through simulation.

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 score0.002
Threshold uncertainty score0.005

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 communication0.0000.000
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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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

Citations7
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueConference Record of the 2002 IEEE Industry Applications Conference. 37th IAS Annual Meeting (Cat. No.02CH37344)Same topicMicrogrid Control and OptimizationFrench-language works237,207