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Record W2125538573 · doi:10.1109/ias.2005.1518876

Optimal hydrogen production in a stand-alone renewable energy system

2005· article· en· W2125538573 on OpenAlexaff
Kodjo Agbossou, Mamadou Lamine Doumbia, Aïcha Anouar

Bibliographic record

VenueFourtieth IAS Annual Meeting. Conference Record of the 2005 Industry Applications Conference, 2005. · 2005
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsRenewable energyHydrogen productionWind powerProcess engineeringTurbinePhotovoltaic systemComputer scienceHydrogen fuelAutomotive engineeringEnvironmental scienceBuck converterHydrogenEngineeringElectrical engineeringMechanical engineeringVoltageChemistry

Abstract

fetched live from OpenAlex

A stand-alone renewable wind-photovoltaic energy system can be used to meet the energy requirements of off-grid remote area applications. Such a system has been developed and successfully tested at the Hydrogen Research Institute (HRI). In the HRFs system the excess electrical energy with respect to load demand, is transformed and stored as hydrogen gas via an electrolyzer. The stored hydrogen represents a long-term ecological and transportable form of energy. The renewable energy (RE) system components have substantially different voltage-current characteristics and their operation must be well understood and coordinated to allow an optimal power management in the system. Wind turbine generator, DC-DC buck converter and electrolyzer play key roles in the hydrogen production process. Accurate knowing of operating characteristics of these components is necessary to develop an effective power flow control for the hydrogen production. This paper investigates operational characteristics of the wind turbine, the electrolyzer and the buck converter in order to develop an energy management strategy that will increase the hydrogen production efficiency in the RE system. Wind turbine model is developed and simulation results are compared with experimental measurements. The electrolyzer is characterized and its optimal operating range is defined. The multiphase control principle of the designed buck converter is presented and the efficiency curve is provided. An energy management strategy is proposed to increase the overall efficiency of the hydrogen production process.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.827
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.239
Teacher spread0.220 · 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 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

Citations23
Published2005
Admission routes1
Has abstractyes

Explore more

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