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Simulation methodology for an off-grid solar–battery–water electrolyzer plant: Simultaneous optimization of component capacities and system control

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  • Ibáñez-Rioja, Alejandro
  • Puranen, Pietari
  • Järvinen, Lauri
  • Kosonen, Antti
  • Ruuskanen, Vesa
  • Ahola, Jero
  • Koponen, Joonas

Abstract

The capacity of each component in an off-grid water electrolyzer hydrogen production plant integrated with solar photovoltaics and a battery energy storage system represents a significant factor affecting the viability and reliability of the system. This paper describes a novel method that optimizes simultaneously the component capacities and finite-state machine based control of the system to minimize the cost of green hydrogen production. The components and control in the system are referenced to a proton exchange membrane water electrolyzer stack with a fixed nominal power of 4.5kW. The end results are thus scalable by changing the nominal power of the electrolyzer. Simulations are carried out based on data collected from a residential solar photovoltaic installation with 300s time resolution. Optimization of the system is performed with particle swarm optimization algorithm. A sensitivity analysis performed over the prices of the different components reveals that the price of the water electrolyzer has the greatest impact on the green hydrogen production cost. It is found that the price of the battery has to be below 0.3 €/Wh to become a feasible solution as overnight energy storage.

Suggested Citation

  • Ibáñez-Rioja, Alejandro & Puranen, Pietari & Järvinen, Lauri & Kosonen, Antti & Ruuskanen, Vesa & Ahola, Jero & Koponen, Joonas, 2022. "Simulation methodology for an off-grid solar–battery–water electrolyzer plant: Simultaneous optimization of component capacities and system control," Applied Energy, Elsevier, vol. 307(C).
  • Handle: RePEc:eee:appene:v:307:y:2022:i:c:s0306261921014306
    DOI: 10.1016/j.apenergy.2021.118157
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    References listed on IDEAS

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    1. Wang, Ningbo & Guo, Yanhua & Liu, Lu & Shao, Shuangquan, 2024. "Numerical assessment and optimization of photovoltaic-based hydrogen-oxygen Co-production energy system: A machine learning and multi-objective strategy," Renewable Energy, Elsevier, vol. 227(C).

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