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Influence of shunt currents in industrial-scale alkaline water electrolyzer plants

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Listed:
  • Sakas, Georgios
  • Ibáñez-Rioja, Alejandro
  • Pöyhönen, Santeri
  • Kosonen, Antti
  • Ruuskanen, Vesa
  • Kauranen, Pertti
  • Ahola, Jero

Abstract

The aim of this paper is to analyze through simulation how the energy efficiency of a single electrolysis stack at various loads is affected by shunt currents and to determine the energy-optimal load distribution between lines in a multiline electrolysis system under various magnitudes of shunt current losses. A dynamic energy and mass balance model of an industrial 3MW, 16bar alkaline water electrolyzer (AWE) process was developed using MATLAB. The optimization goal is to determine the power supply for each AWE line so that it can meet any hydrogen demand while minimizing the global specific energy consumption (SEC). The Particle Swarm Optimization (PSO) algorithm is used to minimize the objective function. According to the results of the single stack investigation, shunt current reduction could significantly improve the energy efficiency of partial-load operation. In addition, the optimization study revealed that whenever two or more lines are required to run in order to satisfy the hydrogen demand, the global SEC is minimized when the lines operate at equal loads.

Suggested Citation

  • Sakas, Georgios & Ibáñez-Rioja, Alejandro & Pöyhönen, Santeri & Kosonen, Antti & Ruuskanen, Vesa & Kauranen, Pertti & Ahola, Jero, 2024. "Influence of shunt currents in industrial-scale alkaline water electrolyzer plants," Renewable Energy, Elsevier, vol. 225(C).
    • Handle: RePEc:eee:renene:v:225:y:2024:i:c:s0960148124003318
    DOI: 10.1016/j.renene.2024.120266
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    References listed on IDEAS

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    1. De Silva, Y. Sanath K. & Middleton, Peter Hugh & Kolhe, Mohan Lal, 2020. "Performance comparison of mono-polar and bi-polar configurations of alkaline electrolysis stack through 3-D modelling and experimental fabrication," Renewable Energy, Elsevier, vol. 149(C), pages 760-772.
    2. Hu, Song & Guo, Bin & Ding, Shunliang & Yang, Fuyuan & Dang, Jian & Liu, Biao & Gu, Junjie & Ma, Jugang & Ouyang, Minggao, 2022. "A comprehensive review of alkaline water electrolysis mathematical modeling," Applied Energy, Elsevier, vol. 327(C).
    3. Ibáñez-Rioja, Alejandro & Järvinen, Lauri & Puranen, Pietari & Kosonen, Antti & Ruuskanen, Vesa & Hynynen, Katja & Ahola, Jero & Kauranen, Pertti, 2023. "Off-grid solar PV–wind power–battery–water electrolyzer plant: Simultaneous optimization of component capacities and system control," Applied Energy, Elsevier, vol. 345(C).
    4. Mohammad Ostadi & Kristofer Gunnar Paso & Sandra Rodriguez-Fabia & Lars Erik Øi & Flavio Manenti & Magne Hillestad, 2020. "Process Integration of Green Hydrogen: Decarbonization of Chemical Industries," Energies, MDPI, vol. 13(18), pages 1-16, September.
    5. Sakas, Georgios & Ibáñez-Rioja, Alejandro & Pöyhönen, Santeri & Järvinen, Lauri & Kosonen, Antti & Ruuskanen, Vesa & Kauranen, Pertti & Ahola, Jero, 2024. "Sensitivity analysis of the process conditions affecting the shunt currents and the SEC in an industrial-scale alkaline water electrolyzer plant," Applied Energy, Elsevier, vol. 359(C).
    6. Gallo, María Angélica & García Clúa, José Gabriel, 2023. "Sizing and analytical optimization of an alkaline water electrolyzer powered by a grid-assisted wind turbine to minimize grid power exchange," Renewable Energy, Elsevier, vol. 216(C).
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