IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v268y2023ics0360544223000361.html
   My bibliography  Save this article

A reactor network of biomass gasification process in an updraft gasifier based on the fully kinetic model

Author

Listed:
  • Qi, Jingwei
  • Wang, Yijie
  • Hu, Ming
  • Xu, Pengcheng
  • Yuan, Haoran
  • Chen, Yong

Abstract

Modelling gasification reactors by process simulation is a practical utility to evaluate gasification performance and assist device design. In this study, a fully kinetic model for the biomass gasification process within a pilot-scale updraft gasifier is proposed, which considers the effect of reactor dimensions, residence time, and temperature distribution on the gasification process compared with the thermodynamic equilibrium method and kinetic method modeled by continuous stirring tank reactor blocks. The pyrolysis stage is defined by detailed solid biomass pyrolysis mechanisms and secondary gas reactions kinetic mechanisms. Moreover, the gas evolution effect in the pyrolysis stage is considered by transferring gas to the gasification zone and freeboard zone according to different temperatures. The gasification and combustion processes are modeled utilizing comprehensive homogeneous and heterogeneous rate-controlled reactions and the plug flow reactor is first used in modelling the updraft gasifier with the countercurrent characteristic. This proposed model is validated by several experimental data and the predictive results agree well with experimental data with the maximum root-mean-square deviation of 2.6%. The effect of air or steam as gasification agents on gasification performance is evaluated by the proposed model. This model can provide guidance for industrial equipment design.

Suggested Citation

  • Qi, Jingwei & Wang, Yijie & Hu, Ming & Xu, Pengcheng & Yuan, Haoran & Chen, Yong, 2023. "A reactor network of biomass gasification process in an updraft gasifier based on the fully kinetic model," Energy, Elsevier, vol. 268(C).
    • Handle: RePEc:eee:energy:v:268:y:2023:i:c:s0360544223000361
    DOI: 10.1016/j.energy.2023.126642
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223000361
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.126642?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mutlu, Ali Yener & Yucel, Ozgun, 2018. "An artificial intelligence based approach to predicting syngas composition for downdraft biomass gasification," Energy, Elsevier, vol. 165(PA), pages 895-901.
    2. Nadia Cerone & Francesco Zimbardi, 2018. "Gasification of Agroresidues for Syngas Production," Energies, MDPI, vol. 11(5), pages 1-18, May.
    3. Mohamed, Usama & Zhao, Ying-jie & Yi, Qun & Shi, Li-juan & Wei, Guo-qing & Nimmo, William, 2021. "Evaluation of life cycle energy, economy and CO2 emissions for biomass chemical looping gasification to power generation," Renewable Energy, Elsevier, vol. 176(C), pages 366-387.
    4. Song, Yuhang & Tian, Ye & Zhou, Xiong & Liang, Shimang & Li, Xuanyu & Yang, Yu & Yuan, Liang, 2021. "Simulation of air-steam gasification of pine sawdust in an updraft gasification system for production of hydrogen-rich producer gas," Energy, Elsevier, vol. 226(C).
    5. Safarian, Sahar & Unnþórsson, Rúnar & Richter, Christiaan, 2019. "A review of biomass gasification modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 378-391.
    6. Rosha, Pali & Kumar, Sandeep & Ibrahim, Hussameldin, 2022. "Sensitivity analysis of biomass pyrolysis for renewable fuel production using Aspen Plus," Energy, Elsevier, vol. 247(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Magdalena Skrzyniarz & Marcin Sajdak & Anna Biniek-Poskart & Andrzej Skibiński & Marlena Krakowiak & Andrzej Piotrowski & Patrycja Krasoń & Monika Zajemska, 2024. "Methods and Validation Techniques of Chemical Kinetics Models in Waste Thermal Conversion Processes," Energies, MDPI, vol. 17(13), pages 1-27, June.
    2. Qi, Jingwei & Wang, Yijie & Xu, Pengcheng & Hu, Ming & Huhe, Taoli & Ling, Xiang & Yuan, Haoran & Chen, Yong, 2024. "Study on the Co-gasification characteristics of biomass and municipal solid waste based on machine learning," Energy, Elsevier, vol. 290(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ascher, Simon & Watson, Ian & You, Siming, 2022. "Machine learning methods for modelling the gasification and pyrolysis of biomass and waste," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    2. Kargbo, Hannah O. & Zhang, Jie & Phan, Anh N., 2021. "Optimisation of two-stage biomass gasification for hydrogen production via artificial neural network," Applied Energy, Elsevier, vol. 302(C).
    3. Buentello-Montoya, D.A. & Duarte-Ruiz, C.A. & Maldonado-Escalante, J.F., 2023. "Co-gasification of waste PET, PP and biomass for energy recovery: A thermodynamic model to assess the produced syngas quality," Energy, Elsevier, vol. 266(C).
    4. Ruivo, Luís & Silva, Tiago & Neves, Daniel & Tarelho, Luís & Frade, Jorge, 2023. "Thermodynamic guidelines for improved operation of iron-based catalysts in gasification of biomass," Energy, Elsevier, vol. 268(C).
    5. Salem, Ahmed M. & Abd Elbar, Ayman Refat, 2023. "The feasibility and performance of using producer gas as a gasifying medium," Energy, Elsevier, vol. 283(C).
    6. Luo, Shihua & Hu, Weihao & Liu, Wen & Zhang, Zhenyuan & Bai, Chunguang & Huang, Qi & Chen, Zhe, 2022. "Study on the decarbonization in China's power sector under the background of carbon neutrality by 2060," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    7. Wu, Wei & Taipabu, Muhammad Ikhsan & Chang, Wei-Chen & Viswanathan, Karthickeyan & Xie, Yi-Lin & Kuo, Po-Chih, 2022. "Economic dispatch of torrefied biomass polygeneration systems considering power/SNG grid demands," Renewable Energy, Elsevier, vol. 196(C), pages 707-719.
    8. Nadia Cerone & Francesco Zimbardi, 2021. "Effects of Oxygen and Steam Equivalence Ratios on Updraft Gasification of Biomass," Energies, MDPI, vol. 14(9), pages 1-18, May.
    9. Ayub, Yousaf & Hu, Yusha & Ren, Jingzheng, 2023. "Estimation of syngas yield in hydrothermal gasification process by application of artificial intelligence models," Renewable Energy, Elsevier, vol. 215(C).
    10. 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.
    11. Toledo, Mario & Arriagada, Andrés & Ripoll, Nicolás & Salgansky, Eugene A. & Mujeebu, Muhammad Abdul, 2023. "Hydrogen and syngas production by hybrid filtration combustion: Progress and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 177(C).
    12. Naveed, Muhammad Hamza & Khan, Muhammad Nouman Aslam & Mukarram, Muhammad & Naqvi, Salman Raza & Abdullah, Abdullah & Haq, Zeeshan Ul & Ullah, Hafeez & Mohamadi, Hamad Al, 2024. "Cellulosic biomass fermentation for biofuel production: Review of artificial intelligence approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    13. Ahmed Fathy & Hegazy Rezk & Dalia Yousri & Abdullah G. Alharbi & Sulaiman Alshammari & Yahia B. Hassan, 2023. "Maximizing Bio-Hydrogen Production from an Innovative Microbial Electrolysis Cell Using Artificial Intelligence," Sustainability, MDPI, vol. 15(4), pages 1-13, February.
    14. Mohsen Fallah Vostakola & Babak Salamatinia & Bahman Amini Horri, 2022. "A Review on Recent Progress in the Integrated Green Hydrogen Production Processes," Energies, MDPI, vol. 15(3), pages 1-41, February.
    15. Lv, J. & Li, Y.P. & Huang, G.H. & Ding, Y.K. & Li, X. & Li, Y., 2022. "Planning energy economy and eco-environment nexus system under uncertainty: A copula-based stochastic multi-level programming method," Applied Energy, Elsevier, vol. 312(C).
    16. Smith, William R. & Tahir, Hamdah & Leal, Allan M.M., 2024. "Stoichiometric and non-stoichiometric methods for modeling gasification and other reaction equilibria: A review of their foundations and their interconvertibility," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    17. Vera Marcantonio & Luisa Di Paola & Marcello De Falco & Mauro Capocelli, 2023. "Modeling of Biomass Gasification: From Thermodynamics to Process Simulations," Energies, MDPI, vol. 16(20), pages 1-30, October.
    18. Donghoon Shin & Akhil Francis & Purushothaman Vellayani Aravind & Theo Woudstra & Wiebren de Jong & Dirk Roekaerts, 2022. "Numerical Evaluation of Biochar Production Performance of Downdraft Gasifier by Thermodynamic Model," Energies, MDPI, vol. 15(20), pages 1-18, October.
    19. Elmaz, Furkan & Yücel, Özgün, 2020. "Data-driven identification and model predictive control of biomass gasification process for maximum energy production," Energy, Elsevier, vol. 195(C).
    20. Zhang, Bowei & Guo, Simao & Jin, Hui, 2022. "Production forecast analysis of BP neural network based on Yimin lignite supercritical water gasification experiment results," Energy, Elsevier, vol. 246(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:268:y:2023:i:c:s0360544223000361. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.