Dynamic Modeling and Experimental Validation of a PEM-Based System Integrated with Renewable Power sources
再生可能電源と統合したPEMベースシステムの動的モデリングと実験的検証 (AI 翻訳)
Nayrana Daborer-Prado, L. Gaisberger
🤖 gxceed AI 要約
日本語
本研究は、再生可能エネルギーと統合したPEM電解槽システムの動的モデルを開発し、実験データにより検証した。モデルは陽極、陰極、膜、電圧の4つのサブモデルで構成され、MATLAB/Simulinkで実装された。さらに、検証済みモデルを水素貯蔵や多様な需要家を含むエネルギーハブに統合し、グリーン水素の実用化に向けた知見を提供する。
English
This study develops and experimentally validates a dynamic model of a PEM electrolyzer system integrated with renewable energy. The model comprises four submodels (anode, cathode, membrane, voltage) implemented in MATLAB/Simulink. Validated against prototype data, it is then integrated into an energy hub with renewables, hydrogen storage, and various end-users, supporting green hydrogen deployment.
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
日本は水素社会の実現を目指しており、本研究成果は再生可能エネルギー由来のグリーン水素製造システムの設計・運用に直接貢献する。特に、PEM電解槽の動的モデルと実験検証は、日本の水素戦略における技術基盤強化に資する。
In the global GX context
Globally, green hydrogen is critical for decarbonizing hard-to-abate sectors. This paper provides a validated dynamic model of PEM electrolyzers integrated with renewables, offering practical insights for system design and operation, aligning with global hydrogen roadmaps and renewable integration efforts.
👥 読者別の含意
🔬研究者:The detailed PEM electrolyzer model and experimental validation provide a robust foundation for further research on hydrogen production and system integration.
🏢実務担当者:The validated model can be used to design and optimize green hydrogen production systems coupled with renewable sources and storage.
🏛政策担当者:The study supports policy frameworks promoting green hydrogen by demonstrating technical feasibility and integration pathways.
📄 Abstract(原文)
In recent years, hydrogen (H₂) has gained significant attention as a key element in the global energy transition due to its potential to reduce carbon emissions and support sustainable energy systems. Governments and industries have increasingly invested in hydrogen technologies to decarbonize sectors such as transportation, industry, and power generation. Hydrogen can be classified according to its production pathway into gray, blue, brown/black, and green hydrogen, with green hydrogen representing the most environmentally sustainable option and the focus of this study. Green hydrogen is produced via water electrolysis powered by renewable energy sources, using surplus energy from wind, solar, or hydropower to split water into hydrogen and oxygen. This process is carried out by electrolyzers, with the main types being proton exchange membrane (PEM), alkaline, and solid oxide electrolyzers. Among these, PEM electrolyzers offer notable advantages, particularly in renewable energy applications. They respond quickly to power fluctuations, produce high-purity hydrogen suitable for fuel cells, and feature compact designs capable of operating at higher current densities. Owing to these advantages, this study focuses on PEM electrolyzers and their integration with renewable energy sources. The first stage of this study involves the development of a detailed mathematical model of the electrolyzer. To accurately capture the dynamic interactions within the system, the PEM electrolyzer model is structured into four interconnected submodels: the anode, cathode, membrane, and voltage components (Figure (a)). The system is implemented in MATLAB/Simulink®, with current (A), water mass flow rate (kg·s⁻¹), pressure (Pa), and temperature (°C) defined as the primary input variables. In the second stage, the simulation results are validated against experimental data obtained from a prototype operating at the Hydrogen Center laboratory. Finally, the validated electrolyzer model is integrated into an energy-hub framework that incorporates renewable energy sources, hydrogen storage systems, and multiple categories of end users, including industrial and residential consumers as depicted in Figure (b).
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.7250/conect.2026.039first seen 2026-05-15 20:15:55
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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。