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Record W2773209761 · doi:10.1109/iecon.2017.8217127

Modified droop control to improve performances of two single-phase parallel inverters

2017· article· en· W2773209761 on OpenAlexaff
Ahmed Busbieha, Abdelhamid Hamadi, Auguste Ndtoungou, Alireza Javadi, S. Rahmani, Kamal Al‐Haddad

Bibliographic record

VenueIECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society · 2017
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsVoltage droopInverterControl theory (sociology)AC powerInductorHarmonicsVoltageMaster/slaveEngineeringComputer scienceTotal harmonic distortionElectronic engineeringElectrical engineeringVoltage sourceControl (management)

Abstract

fetched live from OpenAlex

This paper presents an approach for upgrading droop control aimed to improve its performance when used for two parallel inverters. The proposed control ensures equal voltage for the two inverters when different power flowing through them which guarantee zero current circulation. To fulfill the voltage regulation, the second inverter (slave) regulates its voltage to follow the master inverter reference by adding a drop voltage to the reference established by the droop control of the second inverter. The current harmonic compensation is also controlled by the slave inverter using a notch filter for harmonics and reactive current extraction. For the master inverter, a control algorithm is integrated to compensate the reactive power exchanged with the grid side in order to obtain the grid voltage in phase with the grid current. The control approach proposed may be used with equal or different power ratings of any number of parallel inverters, provided that the slave inverters should regulate their voltage according to the master reference inverter. For long distance inverters station, wireless communication may be used to transmit necessary information from the master to other slave inverters. The MSC (Master Slave Control) method is used and the first inverter specified as the master, and the second is the slave. Different tests are undertaken by online variation of the power and the inductor of the second inverter to validate the proposed control approach and robustness.

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: Empirical
Teacher disagreement score0.389
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.264
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 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

Citations3
Published2017
Admission routes1
Has abstractyes

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