Where in the World Should We Produce Green Hydrogen? An Objective First-Pass Site Selection
グリーン水素は世界のどこで生産すべきか：客観的な一次選定手法 (AI 翻訳)
Moe Thiri Zun, Benjamin Craig Mclellan
🤖 gxceed AI 要約
日本語
本研究は、太陽光・風力によるグリーン水素生産の最適地点を客観的に選定するための意思決定支援システム（DSS）を開発した。経済・環境・技術・社会・リスク・安全の各要因を多基準意思決定（MCDM）手法で統合し、3種類の重み付けシナリオを比較。特にPageRankベースの重み付けがインフラや社会的指標の重要性を再配分し、資源効率的なサイト選定に有効であることを示した。
English
This study develops a decision support system (DSS) for objectively identifying optimal green hydrogen production sites using solar and wind resources. It integrates economic, environmental, technical, social, and risk factors via multi-criteria decision making (MCDM), comparing three weighting scenarios. The PageRank-based approach redistributes importance toward infrastructure and social indicators, offering a balanced and resource-efficient site selection method.
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
日本の水素基本戦略やグリーンイノベーション基金事業において、国内・海外の水素サプライチェーン構築が加速する中、客観的な立地選定手法は投資判断や政策支援に有用。本手法は特に初期段階のスクリーニングに適しており、日本企業の海外水素プロジェクト参画の意思決定を支援する。
In the global GX context
As global hydrogen investments surge, objective site selection methods like this DSS reduce upfront costs and biases in identifying viable production locations. The PageRank-based weighting offers a novel approach to capture indicator interdependencies, relevant for ISSB-aligned climate transition plans and TCFD scenario analysis. The framework is adaptable to various regional contexts, supporting efficient capital allocation in the hydrogen economy.
👥 読者別の含意
🔬研究者:Provides a transparent, bias-minimized MCDM framework for hydrogen site selection, comparing weighting methods and offering insights on indicator interdependencies.
🏢実務担当者:Useful for energy companies and project developers seeking a low-cost, initial screening tool to prioritize green hydrogen production sites globally.
🏛政策担当者:Offers a data-driven approach to inform national hydrogen strategy and support public funding decisions for infrastructure development.
📄 Abstract（原文）
Many nations have been investing in hydrogen energy in the most recent wave of development and numerous projects have been proposed, yet a substantial share of these projects remain at the conceptual or feasibility stage and have not progressed to final investment decision or operation. There is a need to identify initial potential sites for green hydrogen production from renewable energy on an objective basis with minimal upfront cost to the investor. This study develops a decision support system (DSS) for identifying optimal locations for green hydrogen production using solar and wind resources that integrate economic, environmental, technical, social, and risk and safety factors through advanced Multi-Criteria Decision Making (MCDM) techniques. The study evaluates alternative weighting scenarios using (a) occurrence-based, (b) PageRank-based, and (c) equal weighting approaches to minimize human bias and enhance decision transparency. In the occurrence-based approach (a), renewable resource potential receives the highest weighting (≈34% total weighting). By comparison, approach (b) redistributes importance toward infrastructure and social indicators, yielding a more balanced representation of technical and economic priorities and highlighting the practical value of capturing interdependencies among indicators for resource-efficient site selection. The research also contrasts the empirical and operational efficiencies of various weighting methods and processing stages, highlighting strengths and weaknesses in supporting sustainable and economically viable site selection. Ultimately, this research contributes significantly to both academic and practical implementations in the green hydrogen sector, providing a strategic, data-driven approach to support sustainable energy transitions.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/hydrogen7010011first seen 2026-05-15 19:28:54
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。