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Record W2748676169 · doi:10.11159/ehst17.1

Power-to-Gas Pathways to a Fossil Free Energy System

2017· article· en· W2748676169 on OpenAlexaffabout
Michael Fowler

Bibliographic record

VenueProceedings of the International Conference of Energy Harvesting, Storage, and Transfer · 2017
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFossil fuelEnergy (signal processing)Power (physics)Power to gasComputer scienceEnvironmental scienceChemistryEngineeringPhysicsWaste managementThermodynamicsElectrode

Abstract

fetched live from OpenAlex

Power-to-gas is a novel energy storage concept that can help in providing energy storage and offer a sustainable and efficient alternative ways utilize the surplus electricity generated by the provincial grid of Ontario, Canada. The ability of the power to gas energy hubs to utilize the existing natural gas distribution and storage network (within the province) to distribute and store the electrolytic hydrogen produced is one of its major advantages. There a number of different 'pathway' for using the hydrogen generated via the Power-to-Gas concept, and this presentation will outline the pathways for use of the hydrogen and for the provision of energy storage. Also an optimization model of a power to gas energy hub having a hydrogen production module capacity of 2 MW has been developed and will be presented. The goal of this optimization study was to carry out an economic feasibility of the energy hub under existing pricing mechanisms for the three primary services that it provides, namely: 1) Offsetting CO2 emissions at natural gas end users by providing hydrogen enriched natural gas; 2) Providing demand response when directed by the Independent Electricity System Operator of the province, and 3) Providing pure hydrogen to a fuel cell vehicle refueling station.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.027
GPT teacher head0.226
Teacher spread0.199 · 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 designBench or experimental
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

Citations0
Published2017
Admission routes2
Has abstractyes

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