Green Hydrogen in Integrated Multi-Energy Systems: Technological Pathways, Policy and Market Perspectives, and the Role of Artificial Intelligence
統合マルチエネルギーシステムにおけるグリーン水素：技術経路、政策と市場の展望、および人工知能の役割 (AI 翻訳)
H. Niazi, Kamran Taghizad-Tavana, A. Esmaeel Nezhad, Afshin Canani, Mehrdad Tarafdar Hagh, Pouya Paidar
🤖 gxceed AI 要約
日本語
本レビューは、グリーン水素のサプライチェーン、統合マルチエネルギーシステム、主要経済国の政策比較、市場構造、大規模プロジェクト、そしてAIの役割を包括的に議論する。AIの応用は、再生可能エネルギー予測、電解槽の設計・運用、貯蔵・輸送の最適化、システムレベルの技術経済評価の4段階に分類される。全体として、AIがマルチエネルギーシステムにおけるグリーン水素統合を促進する可能性を強調する。
English
This review provides a structured discussion on green hydrogen supply chain, integrated multi-energy systems, policy comparison across EU, US, China, Japan, and India, market structure, large-scale projects, and the role of AI. AI applications are grouped into four stages: forecasting renewable generation, improving electrolyzer design/operation, optimizing storage/distribution, and supporting techno-economic assessment. The review highlights AI's potential to enable green hydrogen integration in multi-energy systems.
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
日本は水素基本戦略を掲げ、グリーン水素の導入を推進している。本レビューは日本の政策を国際比較の中で位置づけ、AI活用による水素システム最適化の可能性を示す。日本のエネルギー政策や水素サプライチェーン構築に示唆を与える。
In the global GX context
This review is valuable globally as it integrates technological, policy, and AI perspectives on green hydrogen, a key decarbonization vector. It compares policies across major economies and highlights AI's role in system integration, offering insights for policymakers and researchers advancing hydrogen deployment.
👥 読者別の含意
🔬研究者:Provides a comprehensive review of AI applications in hydrogen systems, useful for identifying research gaps.
🏢実務担当者:Offers an overview of policy and market conditions affecting hydrogen project viability.
🏛政策担当者:Compares hydrogen policies across major economies, informing policy design.
📄 Abstract（原文）
Green hydrogen is increasingly discussed as an energy carrier that can link electricity, gas, heat, and transport sectors. However, many existing reviews address this topic from separate viewpoints, such as hydrogen production technologies, Artificial Intelligence (AI) applications, or system integration, with less attention to how policy and market conditions affect deployment. This review brings these related aspects together in one structured discussion. The paper first reviews the hydrogen supply chain, including production, storage, transport, and utilization. It then discusses an integrated multi-energy architecture in which hydrogen interacts with electricity, natural gas, heat, and cooling networks. Policy instruments in five major economies, including the European Union, the United States, China, Japan, and India, are compared. The review also summarizes the main barriers to large-scale deployment, including high production costs, limited infrastructure, technological challenges, regulatory uncertainty, and supply-chain constraints. In addition, the current market structure and selected large-scale hydrogen projects planned in the United States are reviewed. The paper also examines the role of artificial intelligence in green hydrogen systems. AI applications are grouped into four main stages of the hydrogen value chain: forecasting renewable energy generation, improving electrolyzer design and operation, optimizing storage and distribution, and supporting system-level techno-economic assessment. Recent Machine Learning (ML) studies are compared based on their methods and their contributions to operation and planning. Overall, this review highlights the role of AI in enabling green hydrogen integration within multi-energy systems.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/fuels7020037first seen 2026-06-19 05:27:47
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