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Record W7038314479

Green ammonia: optimising production and quantifying its potential as an energy vector

2019· dissertation· en· W7038314479 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueOxford University Research Archive (ORA) (University of Oxford) · 2019
Typedissertation
Languageen
FieldMaterials Science
TopicPhytochemistry and Bioactive Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyEnergy storageFlexibility (engineering)Production (economics)Global warmingEnergy supplyThermal energy storageGreenhouse gasVariable renewable energyEnergy source
DOInot available

Abstract

fetched live from OpenAlex

The environmental imperative to achieve net-zero emissions quickly to minimise the rise in average global temperature rise due to global warming is clear. To achieve this, variable renewable energy (VRE) needs to substitute existing energy sources in the polluting sectors: electricity, heat, transport and industry. The integration of VRE sources to high levels of penetration however, is difficult: unlike most commodities, supply and demand must be in equilibrium at each moment in time, from the sub-second to inter-annual. This study quantifies the flexibility required by a power network to integrate additional VRE sources as a function of the magnitude and duration of the electrical energy storage required. The original energy storage requirement modelling tool (ESRMT) calculates: 1) the storage magnitude index (SMI), 2) the storage duration index (SDI) and 3) the storage size required. This quantifies the impact of VRE penetration, the mix of VRE sources and the application of other flexibility methods on the storage requirements. The ESRMT is used to consider locations in Japan, the UK, Canada and Australia and shows that, while requirements do increase with VRE penetration, the magnitude and type is location specific and highly dependent on the mix of VRE sources. Medium and long-term storage required at high VRE penetration are difficult to mitigate. The chemical storage of electrical energy, using ammonia, is a promising solution due to its favourable chemical and technical properties. The decarbonisation of the ammonia production is itself an environmental imperative as it accounts for 1.3% of global carbon dioxide emissions and supports over 48% of the global population through nitrogen based fertilisers. The developed islanded ammonia production modelling tool (IAPMT) optimises the mix of VRE sources, plant design and operation to minimise the levelised cost of ammonia (LCOA) at any given location. The IAPMT is used to consider ammonia production at 534 locations in 70 countries. It shows that at the best location a LCOA of $473/tonne is currently achievable, but this will decrease to $310/tonne by 2030. Decarbonised production will be highly competitive with conventional production by 2030. Assuming its use for seasonal storage, these LCOA estimates mean that the levelised cost of electricity (LCOE) of power-toammonia-to-power of $252/MWh by 2030.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.415
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.038
GPT teacher head0.283
Teacher spread0.245 · 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