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Surrogate-assisted robust design optimization and global sensitivity analysis of a directly coupled photovoltaic-electrolyzer system under techno-economic uncertainty

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  • Coppitters, Diederik
  • De Paepe, Ward
  • Contino, Francesco

Abstract

To match intermittent solar energy supply with energy demand, power-to-hydrogen is a viable solution. In this framework, designing a directly coupled photovoltaic-electrolyzer system assuming deterministic parameters (i.e.perfectly known and fixed parameters) is widely studied. However, considering deterministic model parameters in optimization disregards the inherent uncertainty of the system performance during real-life operation (e.g.due to unexpected costs or ineffective maintenance), leading to a fragile, suboptimal direct coupling of the photovoltaic array with the electrolyzer stack. To avoid a suboptimal coupling, we performed a design optimization under parameter uncertainties (i.e.robust design optimization). This paper provides the deterministic designs, robust designs and a global sensitivity analysis on the hydrogen production and levelized cost of hydrogen. The technical robust design provides a 43% reduction in hydrogen production standard deviation compared to the deterministic design, while the robust, cost-efficient design achieves a mean levelized cost of hydrogen of 6.4€/kg and standard deviation of 0.74€/kg. The discount rate and capital expenditure parameters dominate the standard deviation by 52% and 39% respectively. Therefore, bulk manufacturing of these technologies and more demonstration projects are the main actions to improve the robustness. Future works will focus on including accurate probability distributions, a demand load, the grid and batteries to the system.

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  • Coppitters, Diederik & De Paepe, Ward & Contino, Francesco, 2019. "Surrogate-assisted robust design optimization and global sensitivity analysis of a directly coupled photovoltaic-electrolyzer system under techno-economic uncertainty," Applied Energy, Elsevier, vol. 248(C), pages 310-320.
  • Handle: RePEc:eee:appene:v:248:y:2019:i:c:p:310-320
    DOI: 10.1016/j.apenergy.2019.04.101
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    3. Arsalis, Alexandros & Papanastasiou, Panos & Georghiou, George E., 2022. "A comparative review of lithium-ion battery and regenerative hydrogen fuel cell technologies for integration with photovoltaic applications," Renewable Energy, Elsevier, vol. 191(C), pages 943-960.
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    5. Wang, Jing & Kang, Lixia & Huang, Xiankun & Liu, Yongzhong, 2021. "An analysis framework for quantitative evaluation of parametric uncertainty in a cooperated energy storage system with multiple energy carriers," Energy, Elsevier, vol. 226(C).
    6. Xavier Rixhon & Gauthier Limpens & Diederik Coppitters & Hervé Jeanmart & Francesco Contino, 2021. "The Role of Electrofuels under Uncertainties for the Belgian Energy Transition," Energies, MDPI, vol. 14(13), pages 1-23, July.
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    8. Zahir Barahmand & Marianne S. Eikeland, 2022. "Techno-Economic and Life Cycle Cost Analysis through the Lens of Uncertainty: A Scoping Review," Sustainability, MDPI, vol. 14(19), pages 1-22, September.
    9. Slavin, Brittney & Wang, Ruiqi & Roy, Dibyendu & Ling-Chin, Janie & Roskilly, Anthony Paul, 2024. "Techno-economic analysis of direct air carbon capture and hydrogen production integrated with a small modular reactor," Applied Energy, Elsevier, vol. 356(C).
    10. Coppitters, Diederik & De Paepe, Ward & Contino, Francesco, 2020. "Robust design optimization and stochastic performance analysis of a grid-connected photovoltaic system with battery storage and hydrogen storage," Energy, Elsevier, vol. 213(C).
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