MétaCan
Menu
Back to cohort
Record W2900370871

Allocation of Hydrogen Produced via Power-to-Gas Technology to Various Power-to-Gas Pathways

2018· dissertation· en· W2900370871 on OpenAlexaboutno aff
Suaad Al-Zakwani

Bibliographic record

VenueUWSpace (University of Waterloo) · 2018
Typedissertation
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsnot available
Fundersnot available
KeywordsPower to gasPower (physics)HydrogenChemistryPhysicsThermodynamicsOrganic chemistryPhysical chemistry
DOInot available

Abstract

fetched live from OpenAlex

Demand for renewable energy systems is accelerating and will account for a significant share of future power systems aimed to enhance and decarbonize the world’s energy system. Unlike conventional power plants, electricity output from renewable sources cannot be adjusted easily to match consumer power demand because renewable resources are intermittent short-term seasonal power sources. Accordingly, a rapid increase in surplus power is expected in the future. The Canadian Province of Ontario, in line with global efforts, has targeted 80 % reduction of greenhouse gas emission levels by 2050 compared to 1990 levels. One key step to accomplish this goal is to harness more renewable energies for power generation. Instead of losing the surplus power or exporting it for low returns, storage and utilization in other sectors urgently need to be explored.
\n
\nPower-to-Gas technology offers a possible solution for optimal use of energy surplus. It is efficient at the huge — national— consumption scale and global acceptance of Power-to-Gas as energy storage and transportation technology is growing noticeably. In short, Power-to-Gas is a potential means to manage intermittent and weather-dependent renewable energies like wind, solar, or hydro in a storable chemical energy form. The main concept behind Power-to-Gas technology is to make use of surplus electricity to decompose water molecules into their primary components: hydrogen and oxygen. Power-to-Gas is not only a storage technology; its role can be extended to other energy streams including transportation, industrial use, injection into the natural gas grid as pure hydrogen, and renewable natural gas. 
\n
\nThe current study investigated four specific Power-to-Gas pathways: Power-to-Gas to mobility fuel, Power-to-Gas to industry, Power-to-Gas to natural gas pipeline for use as hydrogen-enriched natural gas, and Power-to-Gas to Renewable Natural Gas (i.e., Methanation). 
\nThis study quantifies the hydrogen volumes at three production capacity factors (67%, 80%, and 96%) upon utilizing Ontario’s surplus electricity baseload. Five allocation scenarios (A-E) of the hydrogen produced to the four Power-to-Gas pathways are investigated and their economic and environmental aspects considered. Allocation scenario A in which hydrogen assigned to each pathway is constrained by a specific demand, is based on Ontario’s energy plans for pollution management in line with international efforts to reduce global warming impacts. Scenarios B-E are about utilization of the produced hydrogen entirely for one of mobility fuel, industrial feedstock, injection into the natural gas grid, or renewable natural gas synthesis, respectively. The study also examines the economic feasibility and carbon offset of the PtG pathways in each scenario.
\n
\nThe research sets the assumption that hydrogen is produced at three capacity production factors: 67% (16 h/day), 80% (19 h/day), and 96% (23 h/day). The amount of surplus baseload electricity for 2017 of each capacity factor is converted to hydrogen via water electrolysis. Accordingly, the total hydrogen produced is approximately 170 kilo-tonnes (kt), 193 kt, and 227 kt, respectively. 
\nResults indicate that the Power-to-Gas to mobility fuel pathway in scenarios A and B has the potential to be implemented. Utilization of hydrogen produced via Power-to-Gas technology for refueling light-duty vehicles is a profitable business case with an average positive net present value of $4.5 billions, five years payback time, and 20% internal rate of return. Moreover, this PtG pathway promises a potential 2,215,916 tonnes of CO2 reduction from road travel. In the scenario to utilize Ontario’s surplus electricity to produce hydrogen via the PtG technology for industrial demand, results indicate that supply could achieve 82%, 93%, and 110% of the industrial demand for hydrogen at the three capacity factors, respectively. Nevertheless, hydrogen production through PtG is still costly compared to other available cheaper alternatives, namely hydrogen produced via steam methane reforming. Power-to-Gas for industry projects should, however, be part of government incentives to encourage clean energy utilization. In addition, although using hydrogen-enriched natural gas or renewable natural gas instead of the conventional natural gas could offset huge amounts of carbon, their capital and operational costs are extremely high, resulting in negative net present values and very long payback time.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.198
Teacher spread0.191 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueUWSpace (University of Waterloo)Same topicHybrid Renewable Energy SystemsFrench-language works237,207