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Record W4394837327 · doi:10.3390/cleantechnol6020024

Wind–PV–Battery Hybrid Off-Grid System: Control Design and Real-Time Testing

2024· article· en· W4394837327 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClean Technologies · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsÉcole de Technologie SupérieureInnovation, Science and Economic Development Canada
Fundersnot available
KeywordsMaximum power point trackingPhotovoltaic systemController (irrigation)Permanent magnet synchronous generatorEngineeringPower electronicsTurbineComputer scienceInverterControl theory (sociology)VoltageElectrical engineeringControl (management)

Abstract

fetched live from OpenAlex

The paper presents the design and implementation of decentralized control for a PV–wind–battery hybrid off-grid system with limited power electronics devices and sensors. To perform well without using any maximum power point tracking (MPPT) technique from the wind turbine (WT) based on a permanent-magnet brushless DC generator (PMBLDCG) and solar panels (PVs) and balance the power in the system, a cascade control structure strategy based on a linear active disturbance rejection controller (LADRC) is developed for the two-switch DC-DC buck-boost converter. Moreover, to ensure an uninterruptible power supply to the connected loads with a constant voltage and frequency, a cascade d-q control structure based on LADRC is developed for the interfacing single-phase inverter. Furthermore, the modeling and controller parameters design are presented. The performance under all operation conditions of the hybrid off-grid configuration and its decentralized control is validated by simulation using MATLAB/Simulink and in real-time using a small-scale hardware 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.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.830
Threshold uncertainty score0.722

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 head0.008
GPT teacher head0.177
Teacher spread0.169 · 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