粒子群最適化を用いたパイプライン輸送を伴う統合グリーン水素エネルギーシステムの需要駆動型技術経済最適化:モロッコ・ワルザザートの病院ケーススタディ
Demand-Driven Techno-Economic Optimization of an Integrated Green Hydrogen Energy System with Pipeline Transport Using Particle Swarm Optimization: A Hospital Case Study in Ouarzazate, Morocco (原題)
Hajar Bouayad, J. Sabor
🤖 gxceed AI 要約
日本語
モロッコ・ワルザザートの病院向けに、太陽光発電・PEM電解・パイプライン貯蔵・燃料電池を統合したグリーン水素システムを設計。粒子群最適化で機器容量を算出し、1日159kgの水素需要を満たす構成を提示した。設置費は約821万ユーロ、水素平準化コストは約13.67ユーロ/kgで、太陽照射変動への感度は限定的だった。
English
A green hydrogen system combining PV, PEM electrolysis, pipeline storage, and fuel cells was designed for a hospital in Ouarzazate, Morocco. Particle swarm optimization sized components to meet 159 kg/day hydrogen demand, with an installation cost of ~EUR 8.21M and LCOH of ~EUR 13.67/kg. Monte Carlo analysis shows reliability is not robust to combined ±20% uncertainty in electrolyzer efficiency and unit costs.
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
日本では水素社会実装や脱炭素電源として水素が政策課題だが、本論文は遠隔地・水ストレス地域の重要負荷(病院)向け独立系水素システムの設計手法を提示。日本企業の海外展開や離島・災害拠点のレジリエンス電源検討に参考となる。
In the global GX context
While global disclosure frameworks (TCFD/ISSB) focus on corporate climate risk, this study offers a techno-economic template for hard-to-abate critical loads like hospitals. It contributes to the growing literature on green hydrogen microgrids and pipeline storage, relevant to transition finance and energy access in high-solar regions.
👥 読者別の含意
🔬研究者:統合水素システムの最適化手法と不確実性評価の実証例として参考になる。
🏢実務担当者:病院等の重要施設における水素導入のコスト・信頼性検討に活用可能。
🏛政策担当者:離島・遠隔地の脱炭素電源政策や水素インフラ補助の設計に示唆を与える。
📄 Abstract(原文)
The decarbonization of hospitals located in remote regions with water stress requires a power source that is both reliable and cost-effective. The use of a green hydrogen energy system is proposed for use as the power source for the medical sector located in Ouarzazate, Morocco. The system utilizes photovoltaic panels to power proton exchange membrane (PEM) electrolyzers, which generate hydrogen fuel that is stored in a pipeline to the hospital site where it can be utilized in a fuel cell. A model was created in MATLAB/Simulink R2023a that considered the backward-propagation algorithm to size each of the components of the hydrogen energy system, which was optimized using the particle swarm optimization algorithm. The sizing results of the model indicated that a 924 kW electrolyzer, a 217 kW fuel cell, a 21.5 kW compressor, a 30 mm diameter pipeline, and a 7400 m2 area for the photovoltaic panels are required to supply 161 kg of hydrogen per day to the hospital. The hydrogen fuel system will meet the demand of the hospital for 159 kg of hydrogen per day with a zero loss of load at the deterministic design point, in both the representative day and five-day cloudy-period stress test horizons; a full-physics Monte Carlo uncertainty analysis (N = 10,000 draws) further shows that this reliability outcome is not robust to combined ±20% uncertainty in electrolyzer efficiency and component unit costs, with zero loss of load maintained in 62.8% of draws. The installation cost of the hydrogen fuel system is approximately 8.21 M EUR. Furthermore, because the hydrogen fuel is stored upstream from the hospital, the flow rate of hydrogen fuel that passes through the pipeline is less than if it were stored downstream from the hospital. Finally, the levelized cost of hydrogen fuel of the system is approximately 13.67 EUR/kg, which shows limited sensitivity to the considered variations in solar irradiance. Thus, this hydrogen fuel system methodology can be applied to other types of critical loads, especially those critical loads within hospitals, in regions with high solar potential.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/hydrogen7040138first seen 2026-09-26 05:12:01 · last seen 2026-09-29 05:20:27
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