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Record W2571072212 · doi:10.1109/iecon.2016.7793465

A multifunctional three-phase grid-connected single-stage SPV system using an intelligent adaptive control technique

2016· article· en· W2571072212 on OpenAlexaff
Rahul Kumar Agarwal, Ikhlaq Hussain, Bhim Singh, Ambrish Chandra, Kamal Al‐Haddad

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsÉcole de Technologie Supérieure
FundersDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsMaximum power point trackingPhotovoltaic systemControl theory (sociology)HarmonicsVoltage sourcePower factorThree-phaseAC powerRippleInductorComputer scienceElectronic engineeringEngineeringVoltageElectrical engineeringInverter

Abstract

fetched live from OpenAlex

In this paper, a multifunctional three-phase grid-connected single-stage solar photovoltaic (SPV) system is presented using an intelligent adaptive control technique. The system configures a SPV array, VSC (Voltage Source Converter), interfacing inductors, ripple filter and three-phase grid connected nonlinear loads. The system is multifunctional as it provides functions of two different modes: 1) It acts as a SPV energy conversion system supplying active power to the loads and grid as well as a DSTATCOM (Distributed Static Compensator), and 2) It acts as a DSTATCOM alone, when SPV generation is unavailable and mitigates several power quality issues such as harmonics attenuation, voltage fluctuations and flickers, reactive power compensation, power factor correction (PFC) and load balancing. It uses a single-stage converter topology with variable step-size least mean fourth (VSS-LMF) derived adaptive control technique for VSC switching incorporating perturb and observe (P&O) method for MPPT (Maximum Power Point Tracking). The performance of the presented system is validated through experimental results obtained on the developed laboratory prototype.

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)0.001
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 score0.940
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.057
GPT teacher head0.282
Teacher spread0.225 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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