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Record W2120093255 · doi:10.1109/tia.2015.2455025

Real-Time Testing of a Fuzzy-Logic-Controller-Based Grid-Connected Photovoltaic Inverter System

2015· article· en· W2120093255 on OpenAlexaff
M. A. Hannan, Z. A. Ghani, M. Nasir Uddin

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2015
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsLakehead University
FundersKementerian Sains, Teknologi dan Inovasi
KeywordsPhotovoltaic systemInverterFuzzy logicGridComputer scienceGrid-connected photovoltaic power systemProgrammable logic controllerController (irrigation)Control engineeringMaximum power point trackingControl theory (sociology)EngineeringElectrical engineeringControl (management)VoltageArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

This paper presents a novel fuzzy-logic-based high-performance control of a three-phase photovoltaic grid-connected inverter. With the aid of the inverter model and fuzzy-logic-based voltage and current-control schemes, a digital signal processor controller board DS1104 generates the sinusoidal pulsewidth modulated signals for the inverter operation in both stand-alone and grid-connected modes. An inverter prototype was built to verify the effectiveness of the control algorithm. The system demonstrates stable ac output voltage satisfactorily during both transient and steady state with grid and load disturbances. The control system generates 2.48% and 4.64% voltage and current total harmonic distortions, respectively. The output waveforms such as output voltage, injected current, and the system power flow are presented to validate the effectiveness of the control strategy.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.039
GPT teacher head0.260
Teacher spread0.221 · 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
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

Citations124
Published2015
Admission routes1
Has abstractyes

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