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Modelling of sorption-enhanced steam methane reforming in a fixed bed reactor network integrated with fuel cell

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  • Diglio, Giuseppe
  • Hanak, Dawid P.
  • Bareschino, Piero
  • Pepe, Francesco
  • Montagnaro, Fabio
  • Manovic, Vasilije

Abstract

In this study sorption-enhanced steam methane reforming (SE-SMR) in fixed beds is investigated by means of 1D numerical modelling, and the model is validated with the data reported in the literature. Isothermal conditions (973 K) are considered, and the equilibrium between the carbonation and calcination stages is shifted by a pressure swing: 3.5 · 106 Pa and 1013 Pa, respectively. The results showed that under these operating conditions at least 8 reactors in parallel are required to continuously produce a high-purity stream of H2, and a separated stream of concentrated CO2. The average H2 purity is 0.92, whilst the average H2 yield and selectivity are 2.9 molH2 molCH4−1 and 90%, respectively. A thermodynamic analysis was performed, which highlighted that, by using a portion of the produced H2 (about 0.4 molH2 molCH4−1), it is possible to fully cover heat and power demands of the process, making it completely energy self-sufficient. In the case when the proposed SE-SMR is integrated with a solid oxide fuel cell, net power generation at the scale of ∼950 kWel can be achieved with a net efficiency of the entire system of 51%, with the important feature that CO2 is concentrated.

Suggested Citation

  • Diglio, Giuseppe & Hanak, Dawid P. & Bareschino, Piero & Pepe, Francesco & Montagnaro, Fabio & Manovic, Vasilije, 2018. "Modelling of sorption-enhanced steam methane reforming in a fixed bed reactor network integrated with fuel cell," Applied Energy, Elsevier, vol. 210(C), pages 1-15.
    • Handle: RePEc:eee:appene:v:210:y:2018:i:c:p:1-15
    DOI: 10.1016/j.apenergy.2017.10.101
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    3. Vo, Nguyen Dat & Oh, Dong Hoon & Kang, Jun-Ho & Oh, Min & Lee, Chang-Ha, 2020. "Dynamic-model-based artificial neural network for H2 recovery and CO2 capture from hydrogen tail gas," Applied Energy, Elsevier, vol. 273(C).
    4. Gil, María V. & Rout, Kumar R. & Chen, De, 2018. "Production of high pressure pure H2 by pressure swing sorption enhanced steam reforming (PS-SESR) of byproducts in biorefinery," Applied Energy, Elsevier, vol. 222(C), pages 595-607.
    5. Sanusi, Yinka S. & Mokheimer, Esmail M.A., 2019. "Thermo-economic optimization of hydrogen production in a membrane-SMR integrated to ITM-oxy-combustion plant using genetic algorithm," Applied Energy, Elsevier, vol. 235(C), pages 164-176.
    6. Ngo, Son Ich & Lim, Young-Il & Kim, Woohyun & Seo, Dong Joo & Yoon, Wang Lai, 2019. "Computational fluid dynamics and experimental validation of a compact steam methane reformer for hydrogen production from natural gas," Applied Energy, Elsevier, vol. 236(C), pages 340-353.
    7. Lu, Yi Ran & Nikrityuk, Petr, 2018. "A fixed-bed reactor for energy storage in chemicals (E2C): Proof of concept," Applied Energy, Elsevier, vol. 228(C), pages 593-607.
    8. Gu, Rong & Ding, Jing & Wang, Yarong & Yuan, Qinquan & Wang, Weilong & Lu, Jianfeng, 2019. "Heat transfer and storage performance of steam methane reforming in tubular reactor with focused solar simulator," Applied Energy, Elsevier, vol. 233, pages 789-801.
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