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Lab VIEW modelling and simulation of a hydrogen based photovoltaic/wind energy system

2009· article· en· W2042293622 on OpenAlexaff
Mamadou Lamine Doumbia, Kodjo Agbossou, C.-L. Proulx

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPhotovoltaic systemDimensioningTest benchState of chargeComputer scienceRenewable energyMATLABWind powerTurbineSimulation softwareSoftwareAutomotive engineeringSimulationControl engineeringPower (physics)EngineeringElectrical engineeringMechanical engineeringAerospace engineeringEmbedded system

Abstract

fetched live from OpenAlex

This paper presents a dynamic simulation model using LabVIEW software to study the behavior of renewable energy systems with hydrogen storage (RESHS). The complete system model is developed by integrating individual sub-units of the photovoltaic arrays, wind turbine, batteries, electrolyzer, fuel cell and power conditioning units. The Labview sub-models are compared with Matlab/Simulink models developed in the previous work Such a global model is useful for optimal dimensioning and effective control design of the RESHSs. The state of charge control method was chosen to validate the developed simulation models. The results confirmed previous modelling and experimental measurements on the test bench.

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 score0.939
Threshold uncertainty score0.275

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 head0.007
GPT teacher head0.176
Teacher spread0.170 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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