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Record W3023806259 · doi:10.1109/tpel.2020.2992779

An Adaptive Sensorless Control Technique for a Flyback-Type Solar Tile Microinverter

2020· article· en· W3023806259 on OpenAlexaff
Nicholas Falconar, Dawood Shekari Beyragh, Majid Pahlevani

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2020
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSolar micro-inverterFlyback transformerPhotovoltaic systemInductorElectronic engineeringEngineeringInductanceControl systemControl theory (sociology)Computer scienceMaximum power point trackingElectrical engineeringVoltageControl (management)TransformerInverter

Abstract

fetched live from OpenAlex

This article presents a novel sensorless control system for a solar tile microinverter employing the flyback topology. The elimination of current sensors from the circuit lowers the overall cost and reduces measurement noise introduced into the control system. The proposed control system eliminates both the high frequency inductor current measurement as well as the photovoltaic (PV) module current measurement. Additionally, an inductance observer is combined with the proposed technique to increase the accuracy of the high frequency inductor current estimation. A stability analysis proves the system to be stable. The proposed control system is experimentally validated on a microinverter prototype. Simulation and experimental results affirm the feasibility and performance of the control system. The experimental setup includes a grid simulator and a PV module simulator to test the system at varying irradiance levels. The proposed control system is also compared to methods presented in previous literature to demonstrate its superior characteristics.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.988
Threshold uncertainty score1.000

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 head0.014
GPT teacher head0.244
Teacher spread0.230 · 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.

Study designBench or experimental
Domainnot available
GenreMethods

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

Citations21
Published2020
Admission routes1
Has abstractyes

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