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Modeling and Optimizing Green Hydrogen Integration for Electrical Power Supply: Academic Facility at Al Akhawayn University, Ifrane

グリーン水素統合のモデリングと最適化：アル・アカワイン大学イフラーネキャンパスの電力供給 (AI 翻訳)

Fahd Bouallou

Materials Research Proceedings2026-01-01#水素
DOI: 10.21741/9781644904091-100
原典: https://doi.org/10.21741/9781644904091-100

🤖 gxceed AI 要約

日本語

本研究はモロッコの大学施設におけるグリーン水素システムの実現可能性を検討。太陽光発電と水電解、水素貯蔵、燃料電池を組み合わせたシステムをPythonでシミュレーションし、経済性と信頼性を分析。適切な規模のグリーン水素が炭素排出削減とエネルギー自立に有効であることを示した。高等教育機関の持続可能性戦略への示唆を与える。

English

This study examines green hydrogen integration for an academic building in Morocco. A Python simulation models a system combining PV, electrolyzers, hydrogen storage, and fuel cells. Economic metrics (NPC, LCOE, payback) and technical indicators are analyzed. Results show that appropriately sized green hydrogen systems can reduce emissions and improve energy autonomy, supporting long-term energy transition.

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

日本でもグリーン水素の導入が進む中、本論文は学術施設を対象としたシステム設計・最適化の実証事例を提供。日本の大学や研究機関での水素コミュニティ構築の参考となる可能性がある。

In the global GX context

This paper provides a practical modeling framework for facility-level green hydrogen integration with renewables, relevant for decarbonizing campuses and buildings globally. It contributes to the growing literature on hydrogen system optimization and economic feasibility.

👥 読者別の含意

🔬研究者:Researchers can use the simulation framework to model and optimize similar green hydrogen systems for other facilities or scales.

🏢実務担当者:Practitioners can apply the economic and reliability metrics to assess green hydrogen investments for building energy autonomy.

🏛政策担当者:Policymakers can note the potential of green hydrogen for reducing emissions and enhancing resilience in institutional settings.

📄 Abstract（原文）

Abstract: This study examines the feasibility of green hydrogen as a solution for academic building in Al Akhawayn university in Ifrane, Morocco. To do so, we developed a simulation framework on python to model a system that combines solar photovoltaic (PV) power with electrolyzers to produce hydrogen, hydrogen storage, and proton exchange membrane (PEM) fuel cells to generate electricity. We aim to optimize system configuration by taking into consideration renewable generation profiles, electrolyzer efficiency, storage capacity and fuel cell performance. In this study, we analyzed economic metrics such as net present cost (NPC), levelized cost of electricity (LCOE) and payback period in contrast to technical indicators hydrogen production rate, storage utilization, and system efficiency. And in order to assess the capacity of the model to meet the facility’s energy requirements consistently, a reliability analysis was conducted. The results show that the reduction of carbon emissions, improvement of energy autonomy, and high competitiveness compared to grid-based power supply can be achieved with appropriately sized green hydrogen systems. The findings highlight the potential of green hydrogen to enhance resilience and sustainability in higher education institutions, supporting long term energy transition strategies.

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