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Record W3117421010 · doi:10.1049/cds2.12001

Performance analysis of high‐power three‐phase current source inverters in photovoltaic applications

2020· article· en· W3117421010 on OpenAlexaff
Payam Alemi, Jiacheng Wang, Jianwen Zhang, Sahar Amini

Bibliographic record

VenueIET Circuits Devices & Systems · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsInsulated-gate bipolar transistorPhotovoltaic systemInverterPower (physics)Power semiconductor deviceElectrical engineeringElectronic engineeringBipolar junction transistorCurrent sourceComputer scienceMaximum power point trackingVoltageTransistorEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract In this study, a design of a medium‐voltage current source inverter (CSI) and a conventional voltage source inverter (VSI) is presented for high‐power (1 MW) photovoltaic (PV) applications. The characteristics of a new 1700 V/1600 A reverse‐blocking insulated‐gate bipolar transistor (IGBT) in the CSI are compared with the same generation of IGBT device in the VSI. The passive components design, including ac‐ and dc‐side filters, are developed based on a given design procedure. Power loss analysis is demonstrated to compare the CSI efficiency with the VSI's in the specified power range. Simulation and experimental results for the operation and control of the CSI in grid‐connected PV application in the central power range show the effectiveness of the proposed CSI and the possibility of applying it as a viable topological candidate.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 head0.012
GPT teacher head0.213
Teacher spread0.201 · 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
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

Citations4
Published2020
Admission routes1
Has abstractyes

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