Projecting the Reduction of the Levelized Cost of Green Hydrogen via Stack-Level & System-Level Innovation
スタックレベルおよびシステムレベルの革新によるグリーン水素の均等化コスト削減の予測 (AI 翻訳)
Samuel W. Heath, Vinn Nguyen, Benjamin Zeng, Arisa Kita, A. Winter
🤖 gxceed AI 要約
日本語
この研究は、グリーン水素の均等化コスト(LCOH)を削減するためのスタックおよびバランスオブプラント(BoP)の設計フレームワークを提示する。電力削減と資本コスト削減の2つの戦略を分析し、それらのトレードオフを評価する。学術研究と産業の優先事項のギャップを埋めることで、グリーン水素の競争力向上を目指す。
English
This study presents a design framework for reducing the levelized cost of green hydrogen (LCOH) through stack and balance-of-plant (BoP) innovation. It analyzes two strategies—power reduction and capital cost reduction—and evaluates trade-offs. The framework bridges academic literature and industry priorities to facilitate green hydrogen adoption.
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、グリーン水素のコスト低減は国内の水素サプライチェーン構築に直結する。本研究の設計フレームワークは、日本の水素関連企業や研究機関が重点的に取り組むべき技術開発の方向性を示唆する。
In the global GX context
Global interest in hydrogen as a decarbonization vector makes this cost-reduction analysis critical for energy transition planning. The framework provides actionable guidance for R&D prioritization, complementing policy initiatives like the EU Hydrogen Strategy and US Hydrogen Hub programs.
👥 読者別の含意
🔬研究者:This framework identifies key technical levers for LCOH reduction, offering a systematic approach to prioritize research on stack and BoP innovations.
🏢実務担当者:Corporate teams can use the design framework to evaluate cost-reduction pathways and align R&D investments with industry priorities for green hydrogen competitiveness.
🏛政策担当者:The analysis supports informed policy design by quantifying the impact of different cost reduction strategies, aiding in the allocation of subsidies and R&D funding.
📄 Abstract(原文)
The widespread adoption of green hydrogen as a fuel and chemical feedstock can assist in abating carbon emissions in many hard-to-decarbonize industries, but the current price of green hydrogen is too high for it to be utilized as an alternative fuel and clean chemical feedstock. However, there is an opportunity for green hydrogen to be adopted by lead users if the levelized cost of hydrogen (LCOH) can be reduced by ~$1-4.50 / kg H 2 . Currently, there exist many disjointed recommendations and efforts to reduce the levelized cost of hydrogen (LCOH), including (but not limited to) identifying cheaper sources of electricity, optimizing the balance of plant, and improving the cost and efficiency of electrolyzer stacks. However, a holistic and unified analysis that seeks to understand the impact of different cost reduction strategies relative to one another (and the identification of the best combination of strategies) is lacking. A design framework that elucidates stack and balance of plant (BoP) design decisions that can most effectively lower the cost of green hydrogen production (LCOH) can bring green hydrogen closer to competitiveness with grey hydrogen (and other alternative fuels) and facilitate its adoption by lead users. In this study, we identifyviable pathways for lowering the cost of green hydrogen (LCOH) production through stack and balance of plant technical innovation. This cost reduction analysis is done in three parts. In the first part, we identify the feasible cost reduction potential by improving the efficiency (or lowering the power requirement) for the electrolyzer stack and balance of plant (BoP). In the second part, we identify the feasible cost reduction potential by lowering the capital cost of the stack and BoP. And in the third and final part of the study, we synthesize our findings from the first two cost reduction strategies (power reduction and capital cost reduction) and analyze the trade-offs of different cost reduction pathways. In summary, we present a design framework that bridges the gap between academic literature and industry priorities by highlighting research that should be prioritized to lower the cost of green hydrogen and facilitate its adoption.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1149/ma2026-01361760mtgabsfirst seen 2026-07-20 05:21:01
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