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Record W4285558342 · doi:10.18280/psees.040104

Modelling and Analysis of Hybrid PV-PEM Fuel Cell Power System

2020· article· en· W4285558342 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProgress in Solar Energy and Engineering Systems · 2020
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsnot available
FundersDirection Générale de la Recherche Scientifique et du Développement Technologique
KeywordsHybrid systemAutomotive engineeringPhotovoltaic systemRenewable energyProton exchange membrane fuel cellProcess engineeringElectricity generationComputer scienceHybrid powerSizingPhotovoltaicsFossil fuelGreenhouse gasElectric power systemEnvironmental sciencePower (physics)EngineeringElectrical engineeringFuel cellsWaste management

Abstract

fetched live from OpenAlex

Among the renewable energy sources, photovoltaics seems to be the most promising source. It has the advantage of being available everywhere, friend of the environment and easily maintainable. Nevertheless, the major disadvantages are high manufacturing cost, low energy conversion efficiency and non-linear characteristics. On the other hand, the fuel cell is undoubtedly the least polluting means of making electrical energy. Indeed, apart from electricity, the reaction between hydrogen and air produces only water vapour. As such, the process does not reject any greenhouse gases, unlike the combustion of fossil fuels. Whether in a transport-type application (bus or car, or stationary, energy systems including PV or Fuel Cell systems have a in such systems, several levels of control are to be studied, modelled and optimized; this last point, according to one or more criteria of the whole system, can intervene at several levels: optimization of the topology as well as optimization of component sizing. This paper addresses the modelling of hybrid PV-PEM fuel cell power system where the whole system components are implemented using Matlab/Simulink environment. The main parts (PV and PEM fuel cell) are analyzed and investigated alone and in hybrid mode using different scenarios tests. The simulation results show the advantages of using such hybrid system in providing electrical energy in different use cases.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.758

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 science0.0000.000
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 head0.006
GPT teacher head0.164
Teacher spread0.158 · 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