A Critical Review of the Techno-Economic Analysis of the Hydrogen Production from Water Electrolysers Using Multi-Criteria Decision Making (MCDM)
Bibliographic record
Abstract
Hydrogen is a potential energy vector and storage medium for achieving net-zero emissions on a large scale.Among the various methods of producing low-carbon hydrogen, water electrolysis is the most appropriate and promising.Despite the commercial implementation of technical and industrial hydrogen production via electrolysis, conducting a comprehensive economic analysis of its production using grid or micro grid renewable energy systems presents challenges.Accordingly, it's important to review the approaches in the literature on the performance and costs of water electrolysis systems.This critical review aims to identify key performance parameters of the main commercial water electrolysers.In particular, the review will highlight advances in materials and challenges of Alkaline and Polymer Electrolyte Membrane commercial water electrolysis technologies.A techno-economic analysis using Multi-Criteria Decision Making (MCDM) will be performed on these technologies.The review will present various MCDM analysis methods used for these analyses.Results obtained from these methods will be compared and discussed, including their technological issues and the cost of hydrogen prospects, will be shown.Additionally, the potential of using Multi-Criteria Decision Making (MCDM) as a tool for supporting appropriate decision-making in hydrogen production and identifying research and development gaps in water electrolysis will be presented.Also, the limitations and performance of commercial electrolysers while suggesting possible solutions for achieving cost-effective hydrogen production will be described.The goal of this critical review is to propose innovative ideas and solutions for driving cost-effective green hydrogen production for commercial applications.The manuscript clearly states its objective to provide a comprehensive review of the fundamental principles and challenges associated with Proton Exchange Membrane (PEM) and Alkaline Water Electrolysis (AWE).It aims to identify current trends in water electrolysis technology and evaluate the techno-economic feasibility of hydrogen production using Multi-Criteria Decision Making (MCDM) tools.This objective is directly aligned with the need for practical solutions in green hydrogen production, emphasizing the study's contribution towards promoting the adoption of green hydrogen as a critical technology for a low-carbon economy.The introduction discusses the significant challenges in adopting electrolysis technologies, such as high capital costs and the need for innovation in materials and design.It mentions ongoing research to find affordable alternatives to expensive materials like platinum, aiming to reduce the overall cost of electrolysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".