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Feasibility assessment of power-to-methanol through solar thermochemical hydrogen production plant: A case study

2025· article· en· W4409317969 on OpenAlexaff
Shahin Akbari, Ali Hakkaki-Fard, Mohammad Behshad Shafii

Bibliographic record

VenueEnergy Conversion and Management · 2025
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHydrogen productionMethanolProduction (economics)Environmental scienceWaste managementConcentrated solar powerProcess engineeringHydrogenPower stationNuclear engineeringSolar energyChemistryEngineeringElectrical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

• A novel solar-based methanol production system is presented. • It integrates a thermochemical water-splitting cycle with an oxy-fuel power plant. • Hourly simulations are analyzed using meteorological data. • The cost of green hydrogen and e-methanol is about $5.5/kg and $1,531/tonne. • The proposed system utilizes 32 % of the annually captured CO 2 . Power-to-X technologies are pivotal in the future energy landscape, converting renewable electricity into valuable chemicals and fuels. This study proposes a novel solar-based methanol production system to decarbonize an existing power plant through a case study. The system integrates a copper-chlorine (Cu-Cl) thermochemical water-splitting cycle as a promising technology for sustainable hydrogen production with an oxy-fuel combined cycle power plant to determine if it can create e-methanol at a lower cost than alternative methanol production technologies. The power-to-methanol (PtM) system is modeled to establish its technical framework. Subsequently, hourly dynamic simulations are performed, and the effect of real-world solar conditions on the annual system performance is investigated, considering meteorological data. It is demonstrated that the system can produce hydrogen and methanol at competitive production costs while featuring lower operating expenses (OPEX) due to lower electricity consumption than conventional electrolysis methods. Moreover, the surplus electricity produced from the integrated gas turbine and steam Rankine cycles can be sold to the grid and increase the economic performance of the proposed PtM system. The considered system operates optimally at the design direct normal irradiance (DNI) of 881 W/m 2 . Under these conditions, the cost of hydrogen and e-methanol is about $5.5/kg and $1,531/tonne. The CO 2 emissions analysis also reveals that the proposed system utilizes 32 % of the annually captured CO 2 (1.3 kgCO 2 /kgMeOH). With analysts projecting the carbon price to increase to around $186/tCO 2 by 2035, the levelized cost of methanol (LCOM) would decrease to $1,291/tonne, enhancing the cost-competitiveness of e-methanol production.

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 categoriesnone
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 score0.440
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.282
Teacher spread0.266 · 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.

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

Citations27
Published2025
Admission routes1
Has abstractyes

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