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An overview of renewable hydrogen generation methods and optimisation strategies

再生可能水素生成方法と最適化戦略の概要 (AI 翻訳)

Siddique Mni

Currents in Research📚 査読済 / ジャーナル2026-05-19#水素
DOI: 10.54026/esecr/10129
原典: https://doi.org/10.54026/esecr/10129

🤖 gxceed AI 要約

日本語

本論文はグリーン水素の製造方法（電解、バイオマス、ハイブリッド再生可能エネルギー）と、AIを用いた最適化戦略（予測、故障診断）を概説する。実世界のケーススタディを通じて、運輸・発電・産業での実現可能性を示す。

English

This review covers green hydrogen production methods including electrolysis, biomass, and hybrid renewable energy systems, and AI-driven optimization strategies such as forecasting and fault diagnostics. Real-world case studies demonstrate viability in transport, power generation, and industry.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本政府は水素基本戦略を掲げ、水素供給網の整備を進めている。本レビューは技術オプションとAI活用を整理しており、水素バリューチェーン構築の参考になる。

In the global GX context

This overview integrates AI optimization with hydrogen production, reflecting global trends toward efficient, smart renewable energy systems. It supports hydrogen's role in decarbonization, relevant to ISSB and transition finance discussions.

👥 読者別の含意

🔬研究者:Provides a structured overview of hydrogen production and AI optimization strategies, useful for identifying research gaps.

🏢実務担当者:Offers insights into cost-effective hydrogen production and AI-driven system management for energy companies.

🏛政策担当者:Highlights technological viability and case studies supporting hydrogen policy and investment decisions.

📄 Abstract（原文）

Green hydrogen provides a viable alternative to conventional energy, providing a sustainable technique to lower carbon emissions and strengthening electricity protection. This overview explores key production pathways, specializing in electrolysis and biomass-based strategies and hybrid renewable energy and cogeneration systems to improve efficiency and grid stability. In addition, it explores the feature of synthetic intelligence (AI) in H2 production, especially in renewable energy forecasting, system optimization, and fault diagnostics. The optimization guarantees value-effectiveness and system reliability, and enhances hydrogen production efficiency with the aid of identifying premier operational parameters and minimizing system inefficiencies. The newness of this examines lies in integrating hybrid renewable power and hydrogen manufacturing optimization, an attitude not substantially covered in previous research. Furthermore, it provides a comprehensive analysis of optimized applications, consisting of predictive upkeep and fault detection, to enhance hydrogen device reliability. A distinguished contribution of this study is its attention to real-global case research of hydrogen production and application, demonstrating its viability across transportation, strength generation, and industrial sectors. Via addressing key technical and financial challenges, this evaluation outlines a scalable method for lower-priced and sustainable H2 manufacturing, encouraging a greater resilient and sustainable energy future.

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