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グリーン水素統合型島嶼ハイブリッドエネルギーシステムネットワークのシナリオベース2段階最適逐次運用

A Scenario-Based Two-Stage Optimal Sequential Operation of Green-Hydrogen-Integrated Island Hybrid Energy System Network (原題)

Boyu Liu, Ahmed S. Musleh, Guo Chen, Daming Zhang, A. Al‐Durra, Z. Dong

IEEE transactions on engineering management📚 査読済 / ジャーナル2026-01-01#水素経営インパクト: コスト削減対象セクター: power
DOI: 10.1109/tem.2026.3709032
原典: https://doi.org/10.1109/tem.2026.3709032

🤖 gxceed AI 要約

日本語

島嶼部の再生可能エネルギー統合と脱炭素化に向け、水素運搬船(HCV)と島嶼ハイブリッドエネルギーシステムの2段階最適化モデルを提案。第1段階でシナリオベースの確率的最適化により発電・貯蔵・水素供給を計画し、第2段階でHCVの配船・ルーティングを最適化する。24時間ケーススタディで、ピーク水素備蓄を11.58%削減しつつ信頼性を確保できることを実証。

English

This paper proposes a two-stage optimization model for scheduling hydrogen carrier vessels (HCV) and island hybrid energy systems, integrating green hydrogen production, storage, and distribution. The first stage uses scenario-based stochastic optimization for energy scheduling, while the second optimizes HCV dispatch and routing. A 24-hour case study shows an 11.58% reduction in peak hydrogen reserves compared to a conservative baseline, while avoiding reliability violations, supporting decarbonization in island and maritime contexts.

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

日本は多数の離島を抱え、再生可能エネルギー導入とエネルギー自給率向上が課題。本モデルは島嶼部の水素サプライチェーン構築に資するもので、日本の離島エネルギー政策や水素社会実現に向けた取り組みに示唆を与える。

In the global GX context

This research contributes to global efforts on hydrogen-based energy systems and island decarbonization, aligning with international goals for maritime transport emission reduction and renewable integration. The optimization framework offers a replicable model for island communities worldwide, supporting the transition to sustainable energy systems.

👥 読者別の含意

🔬研究者:Provides a novel two-stage stochastic optimization framework for hydrogen-integrated island energy systems, offering a methodological reference for similar decarbonization studies.

🏢実務担当者:Offers a practical scheduling model for hydrogen supply chains in island contexts, potentially reducing operational costs and improving reliability for energy providers.

🏛政策担当者:Highlights the feasibility of green hydrogen in island energy systems, informing policies on renewable integration and maritime decarbonization.

📄 Abstract(原文)

Islands, due to their geographical characteristics, face unique challenges in energy production, distribution, and storage, particularly with respect to integrating renewable energy and reducing reliance on fossil fuels. Hydrogen, in this context, is gaining attention as a potential energy carrier capable of facilitating renewable integration, offering energy storage solutions, and aiding in the reduction of emissions in maritime transport. This article proposes a two-stage sequential optimization model for the scheduling of hydrogen carrier vessel (HCV) and Island hybrid energy system network. The objective is to efficiently coordinate energy production, storage, and hydrogen distribution while minimizing operational costs under uncertainty in renewable energy generation and demand. The first stage focuses on scheduling energy systems. A scenario-based stochastic optimization approach is applied to determine optimal schedules of shore-side and island hybrid energy systems. In the second stage, based on the first stage's results, the optimal dispatch and routing of HCV are determined. The HCV scheduling ensures all islands receive hydrogen within their specified time windows while minimizing transportation costs. A 24-h case study demonstrates the effectiveness of the proposed model, the proposed optimization reduced the required peak hydrogen reserves by 11.58% compared with a conservative uncoordinated baseline, while avoiding the reliability violations observed under deterministic scheduling. This research provides a viable framework for incorporating green hydrogen production, storage, and distribution into island energy systems, supporting decarbonization initiatives in maritime transport and island communities.

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