Multi-Objective Optimization and K-Means Clustering Analysis of Green Hydrogen Production Routes via Biomass Gasification and Water Electrolysis
バイオマスガス化と水電解によるグリーン水素製造ルートの多目的最適化とK平均クラスタリング解析 (AI 翻訳)
Carlos Antonio Padilla-Esquivel, Thelma Posadas-Paredes, Heriberto Alcocer-García, César Ramírez-Márquez, J. M. Ponce-Ortega
🤖 gxceed AI 要約
日本語
本研究では、バイオマスガス化と水電解によるグリーン水素製造を、DETLアルゴリズムを用いた多目的最適化とK平均クラスタリングで比較評価。結果、ガス化がエネルギー効率とコストで優位であり、最適構成で水素3625.95 kg/h、消費エネルギー39.63 kWh/kg H2、年間コスト2.45 MUSDを達成。水電解は3156.78 kg/h、68.7 kWh/kg H2、3.72 MUSD/yr。ガス化は柔軟でバランスの取れた解を提供し、持続可能な水素製造経路としての可能性を示す。
English
This study compares green hydrogen production via biomass gasification and water electrolysis using multi-objective optimization (DETL algorithm) and K-means clustering. Gasification outperforms electrolysis: optimal configuration yields 3625.95 kg/h H2 at 39.63 kWh/kg H2 and 2.45 MUSD/yr, versus 3156.78 kg/h at 68.7 kWh/kg and 3.72 MUSD/yr. Gasification offers more balanced, flexible solutions, highlighting its potential for sustainable hydrogen production.
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でグリーン水素の普及を掲げており、本論文が示す製造ルートの技術経済比較は、国内での最適な水素供給体制の設計に示唆を与える。特にバイオマスの利用は地域分散型エネルギー源としても注目される。
In the global GX context
This paper provides critical techno-economic benchmarks for green hydrogen production, directly informing global efforts to scale up clean hydrogen under cost and efficiency constraints. The comparative framework helps policymakers and investors assess trade-offs between biomass gasification and electrolysis.
👥 読者別の含意
🔬研究者:The study presents a novel multi-objective optimization framework with clustering for hydrogen production route comparison.
🏢実務担当者:Energy engineers can use the cost and efficiency data to evaluate biomass gasification as a competitive green hydrogen production method.
🏛政策担当者:The comparative cost and performance data support hydrogen strategy development and subsidy allocation for production technologies.
📄 Abstract（原文）
Green hydrogen is a key energy carrier for industrial decarbonization; however, its large-scale deployment requires the optimization of production routes from both energetic and economic perspectives. In this study, green hydrogen production via biomass gasification and water electrolysis is comparatively evaluated using a multi-objective optimization framework based on the Differential Evolution Tabu List (DETL) algorithm. The optimization simultaneously maximizes hydrogen production while minimizing specific energy consumption and total annualized cost, explicitly capturing the trade-offs between competing technologies. Results indicate that biomass gasification outperforms water electrolysis in both energetic and economic terms. The optimal gasification configuration achieves 3625.95 kg/h of H2 with a specific energy consumption of 39.63 kWh/kg H2 and a total annualized cost of 2.45 MUSD/yr, whereas water electrolysis reaches 3156.78 kg/h of H2 with 68.7 kWh/kg H2 and a cost of 3.72 MUSD/yr. To support the interpretation of results, K-means clustering is integrated into the methodological framework, enabling the identification of representative regions within the Pareto fronts. Overall, biomass gasification provides more balanced and flexible solutions, highlighting its potential as a competitive route for sustainable hydrogen production.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/pr14060946first seen 2026-05-15 19:21:46
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