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Green hydrogen production plants: A techno-economic review

2024· review· en· W4401688018 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy Conversion and Management · 2024
Typereview
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsYork UniversityMcMaster University
Fundersnot available
KeywordsProduction (economics)Hydrogen productionEnvironmental scienceHydrogenBiochemical engineeringNatural resource economicsWaste managementEngineeringEconomicsChemistryMacroeconomics

Abstract

fetched live from OpenAlex

• Reviewing different configurations of green hydrogen production from technical and economic perspectives. • Six renewable sources, three types of electrolyzers, and five hydrogen storage methods are reviewed. • Power plant configurations are assessed based on economic viability, efficiency, and technological maturity. • This review offers stakeholders informed decision-making tools. • The most cost-effective configurations involve solar photovoltaics or wind turbines, alkaline electrolyzers, and compressed hydrogen storage. • Geothermal or biomass paired with solid oxide electrolyzer cells utilizing waste heat show significant system efficiency. Green hydrogen stands as a promising clean energy carrier with potential net-zero greenhouse gas emissions. However, different system-level configurations for green hydrogen production yield different levels of efficiency, cost, and maturity, necessitating a comprehensive assessment. This review evaluates the components of hydrogen production plants from technical and economic perspectives. The study examines six renewable energy sources—solar photovoltaics, solar thermal, wind, biomass, hydro, and geothermal—alongside three types of electrolyzers (alkaline, proton exchange membrane, and solid oxide electrolyzer cells) and five hydrogen storage methods (compressed hydrogen, liquid hydrogen, metal hydrides, ammonia, and liquid organic hydrogen carriers). A comprehensive assessment of 90 potential system configurations is conducted across five key performance indicators: the overall system cost, efficiency, emissions, production scale and technological maturity. The most cost-effective configurations involve solar photovoltaics or wind turbines combined with alkaline electrolyzers and compressed hydrogen storage. For enhanced system efficiency, geothermal sources or biomass paired with solid oxide electrolyzer cells utilizing waste heat show significant promise. The top technologically mature systems feature combinations of solar photovoltaics, wind turbines, geothermal, or hydroelectric power with alkaline electrolyzers using compressed hydrogen or ammonia storage. The highest hydrogen production scales are observed in systems with solar PV, wind, or hydro power, paired with alkaline or PEM electrolyzers and ammonia storage. Configurations using hydro, geothermal, wind, or solar thermal energy sources paired with alkaline electrolyzers, and compressed hydrogen or liquid organic hydrogen carriers yield the lowest life cycle GHG emissions. These insights provide valuable decision-making tools for researchers, business developers, and policymakers, guiding the optimization of system efficiency and the reduction of system costs.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.879
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.020
GPT teacher head0.256
Teacher spread0.236 · 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