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Record W2734401271 · doi:10.15866/irecon.v5i2.11978

Modeling, Simulation and Control Design of a PWM Three-Phase Four-Wire Shunt Active Power Filter for a 60 kW Industrial Load

2017· article· en· W2734401271 on OpenAlexaff
Georges Semaan, Hadi Y. Kanaan, Alferd M. Hayek, Kamal Al‐Haddad

Bibliographic record

VenueInternational Journal on Energy Conversion (IRECON) · 2017
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsHarmonicsTotal harmonic distortionControl theory (sociology)Power factorThree-phasePulse-width modulationAC powerEngineeringActive filterVoltageMATLABElectronic engineeringComputer scienceElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

Electric Power Quality remains a major concern for energy suppliers and consumers. One of the major reasons that contribute to the worsening of power quality is the existence of current harmonics in the power network caused by nonlinear electric loads. A common solution to eliminate such harmonics is the application of Active Power Filters (APF). In this paper, experimental measurements of the current were conducted on a power line that belongs to Electricité du Liban (EDL); feeding a three-phase large industrial load. Two control schemes for a shunt three-phase four-wire APF are developed: one is based on the use of hysteresis current controller to compensate the current distortion and the reactive power, the other consists of multiple loops PI controllers that ensure voltage regulation at the DC side of the filter and current wave shaping at the AC side. The latter control scheme is based on a small–signal averaged model of the converter, computed in the (dq0) synchronous frame. The simulations are performed using Matlab/Simulink tools. Results show an important reduction of the Total Harmonic Distortion (THD) and significant improvement of the power factor for both methods. Also, a comparison between the obtained results shows that the second control scheme is better than the first one on the level of harmonics reduction.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.734
Threshold uncertainty score0.674

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 communication0.0000.001
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 head0.089
GPT teacher head0.308
Teacher spread0.218 · 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.

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

Citations5
Published2017
Admission routes1
Has abstractyes

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