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Numerical Simulation of an Improved Updraft Biomass Gasifier Based on Aspen Plus

Author

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  • Fugang Zhu

    (Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University, Nanjing 210096, China
    Everbright Greentech Technology Service (Jiangsu) Co., Ltd., Nanjing 211100, China)

  • Laihong Shen

    (Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education, Southeast University, Nanjing 210096, China)

  • Pengcheng Xu

    (Everbright Environmental Research Institute (Shenzhen) Co., Ltd., Shenzhen 518000, China)

  • Haoran Yuan

    (Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China)

  • Ming Hu

    (Everbright Environmental Research Institute (Shenzhen) Co., Ltd., Shenzhen 518000, China)

  • Jingwei Qi

    (Everbright Environmental Research Institute (Shenzhen) Co., Ltd., Shenzhen 518000, China)

  • Yong Chen

    (Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China)

Abstract

In this paper, numerical investigation and optimization is conducted upon an improved updraft gasifier which is expected to overcome the weakness of conventional updraft gasifier. The comprehensive Aspen Plus model of the improved updraft gasifier is based on the RYield and RCSTR reactor. The tar prediction model is constructed, and the yield of tar is determined by the volatile of biomass and gasification temperature. The Aspen Plus simulation results agree very well with experiment results for the product yields and gasification efficiency, which shows the accuracy of the Aspen Plus model. The tar content in syngas of the improved gasifier is proved to be much lower than that of the conventional one by this model. The inflection point of the gasification efficiency occurs when air ratio is 0.25, and the optimum steam proportion in the air is 7.5%. Such a comprehensive investigation could provide necessary information for the optimal design and operation of the improved updraft gasifier.

Suggested Citation

  • Fugang Zhu & Laihong Shen & Pengcheng Xu & Haoran Yuan & Ming Hu & Jingwei Qi & Yong Chen, 2022. "Numerical Simulation of an Improved Updraft Biomass Gasifier Based on Aspen Plus," IJERPH, MDPI, vol. 19(24), pages 1-11, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:17089-:d:1008406
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    References listed on IDEAS

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    1. Samiran, Nor Afzanizam & Jaafar, Mohammad Nazri Mohd & Ng, Jo-Han & Lam, Su Shiung & Chong, Cheng Tung, 2016. "Progress in biomass gasification technique – With focus on Malaysian palm biomass for syngas production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 1047-1062.
    2. Umeki, Kentaro & Namioka, Tomoaki & Yoshikawa, Kunio, 2012. "Analysis of an updraft biomass gasifier with high temperature steam using a numerical model," Applied Energy, Elsevier, vol. 90(1), pages 38-45.
    3. Parthasarathy, Prakash & Narayanan, K. Sheeba, 2014. "Hydrogen production from steam gasification of biomass: Influence of process parameters on hydrogen yield – A review," Renewable Energy, Elsevier, vol. 66(C), pages 570-579.
    4. Zhang, Kai & Chang, Jian & Guan, Yanjun & Chen, Honggang & Yang, Yongping & Jiang, Jianchun, 2013. "Lignocellulosic biomass gasification technology in China," Renewable Energy, Elsevier, vol. 49(C), pages 175-184.
    5. Gabbrielli, Roberto & Barontini, Federica & Frigo, Stefano & Bressan, Luigi, 2022. "Numerical analysis of bio-methane production from biomass-sewage sludge oxy-steam gasification and methanation process," Applied Energy, Elsevier, vol. 307(C).
    6. Fazil, A. & Kumar, Sandeep & Mahajani, Sanjay M., 2022. "Downdraft co-gasification of high ash biomass and plastics," Energy, Elsevier, vol. 243(C).
    7. Ismail, T.M. & El-Salam, M. Abd, 2015. "Numerical and experimental studies on updraft gasifier HTAG," Renewable Energy, Elsevier, vol. 78(C), pages 484-497.
    8. Ghorbani, Saba & Atashkari, Kazem & Borji, Mehdi, 2022. "Three-stage model-based evaluation of a downdraft biomass gasifier," Renewable Energy, Elsevier, vol. 194(C), pages 734-745.
    9. Saxena, R.C. & Seal, Diptendu & Kumar, Satinder & Goyal, H.B., 2008. "Thermo-chemical routes for hydrogen rich gas from biomass: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(7), pages 1909-1927, September.
    10. Rosha, Pali & Kumar, Sandeep & Ibrahim, Hussameldin, 2022. "Sensitivity analysis of biomass pyrolysis for renewable fuel production using Aspen Plus," Energy, Elsevier, vol. 247(C).
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    Cited by:

    1. Marco Mancini & Andreas Schwabauer, 2023. "On the Thermal Stability of a Counter-Current Fixed-Bed Gasifier," Energies, MDPI, vol. 16(9), pages 1-36, April.

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