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A Multi-Agent Approach for the Optimized Operation of Modular Electrolysis Plants

Author

Listed:
  • Vincent Henkel

    (Institute of Automation Technology, Helmut-Schmidt-University, 22043 Hamburg, Germany)

  • Lukas Peter Wagner

    (Institute of Automation Technology, Helmut-Schmidt-University, 22043 Hamburg, Germany)

  • Maximilian Kilthau

    (Institute of Automation Technology, Helmut-Schmidt-University, 22043 Hamburg, Germany)

  • Felix Gehlhoff

    (Institute of Automation Technology, Helmut-Schmidt-University, 22043 Hamburg, Germany)

  • Alexander Fay

    (Chair of Automation, Ruhr University, 44801 Bochum, Germany)

Abstract

In response to the energy transition to renewable resources, green hydrogen production via electrolysis is gaining momentum. Modular electrolysis plants provide a flexible and scalable solution to meet rising hydrogen demand and adapt to renewable energy fluctuations. However, optimizing their operation poses challenges, especially when dealing with heterogeneous electrolyzer modules. In this work, a combination of decentralized Multi-Agent Systems and the Module Type Package concept is presented that enhances the cost-optimized operation of modular electrolysis plants. This approach synergizes the individual strengths of Multi-Agent Systems in handling complex operational dynamics with the efficiency of the Module Type Package for integration and control capabilities. By integrating these technologies, the approach addresses the heterogeneity of electrolyzer modules and increases the adaptability, scalability, and operational flexibility of electrolysis plants. The approach was validated through a case study, demonstrating its effectiveness in achieving cost-optimized load scheduling, dynamic response to demand–supply fluctuations, and resilience against electrolyzer module malfunctions. In summary, the presented approach offers a comprehensive solution for the effective coordination and optimization of modular electrolysis plants.

Suggested Citation

  • Vincent Henkel & Lukas Peter Wagner & Maximilian Kilthau & Felix Gehlhoff & Alexander Fay, 2024. "A Multi-Agent Approach for the Optimized Operation of Modular Electrolysis Plants," Energies, MDPI, vol. 17(14), pages 1-33, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:14:p:3370-:d:1431875
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    References listed on IDEAS

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    1. Flamm, Benjamin & Peter, Christian & Büchi, Felix N. & Lygeros, John, 2021. "Electrolyzer modeling and real-time control for optimized production of hydrogen gas," Applied Energy, Elsevier, vol. 281(C).
    2. Kasper, Lukas & Schwarzmayr, Paul & Birkelbach, Felix & Javernik, Florian & Schwaiger, Michael & Hofmann, René, 2024. "A digital twin-based adaptive optimization approach applied to waste heat recovery in green steel production: Development and experimental investigation," Applied Energy, Elsevier, vol. 353(PB).
    3. Ma, Tengfei & Pei, Wei & Deng, Wei & Xiao, Hao & Yang, Yanhong & Tang, Chenghong, 2022. "A Nash bargaining-based cooperative planning and operation method for wind-hydrogen-heat multi-agent energy system," Energy, Elsevier, vol. 239(PE).
    4. Buttler, Alexander & Spliethoff, Hartmut, 2018. "Current status of water electrolysis for energy storage, grid balancing and sector coupling via power-to-gas and power-to-liquids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2440-2454.
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    Cited by:

    1. Lukas Peter Wagner & Felix Gehlhoff & Lasse Matthias Reinpold & Georg Frey & Julian Jepsen & Alexander Fay, 2025. "Methodology for the Automatic Generation of Optimization Models of Systems of Flexible Energy Resources," Energies, MDPI, vol. 18(2), pages 1-35, January.

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