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Record W2102224555 · doi:10.1109/epec.2009.5420881

Energy storage for renewable energy combined heat, power and hydrogen fuel (CHPH<inf>2</inf>) infrastructure

2009· article· en· W2102224555 on OpenAlexaff
K.A. Nigim, H. Reiser

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsLambton College
Fundersnot available
KeywordsHydrogen storageEnergy storageRenewable energyThermal energy storageController (irrigation)ElectricityHydrogen fuelAutomotive engineeringProcess engineeringEnvironmental scienceEngineeringWaste managementFuel cellsComputer scienceElectrical engineeringPower (physics)ChemistryHydrogenChemical engineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

The article discusses the use of storage systems that address electricity supply intermittency. It also introduces a conceptional intermittency controller which is coupled to the storage units; the controller is used as an energy management system. The combined system is capable of mitigating energy source fluctuation as well as supplying heat and hydrogen fuel. The storage units are selected for insertion in combined heat, power and hydrogen fuel (CHPH2) production and storage facility. Rechargeable batteries and hydrogen storage batteries are selected to supply energy as managed by the controller. Produced hydrogen is used either as fuel for transportation vehicles or to produce electricity using fuel cells. Heat released by the fuel cells is used to supply the demand for thermal energy. Therefore, a combined heat, power and fuel source CHPH2 system is managed and controlled.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.002

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 head0.002
GPT teacher head0.162
Teacher spread0.159 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations12
Published2009
Admission routes1
Has abstractyes

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