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Pyrolysis of biomass – fuzzy modeling

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  • Lerkkasemsan, Nuttapol
  • Achenie, Luke E.K.

Abstract

The depletion of fossil fuel and the environmental impact of using fossil fuel as a main energy source have been subjects of intense research and policy interest in recent years. Pyrolysis of biomass to produce bio-energy is a promising process. However, with the resulting high cost, creating a cost effective chemical plant is very important. A comprehensive process model, which can be used to predict the production from pyrolysis of biomass, is therefore necessary. However, modeling is complex and challenging because of short reaction times, temperatures as high as a thousand degrees Celsius, and biomass of varying or unknown chemical compositions. As such a deterministic model is not capable of representing the pyrolysis reaction system. We propose a new kinetic reaction model, which would account for significant uncertainty. Specifically we have employed fuzzy modeling using the adaptive neuro-fuzzy inference system (ANFIS) in order to describe the pyrolysis of biomass. The resulting model is in better agreement with experimental data than known deterministic models.

Suggested Citation

  • Lerkkasemsan, Nuttapol & Achenie, Luke E.K., 2014. "Pyrolysis of biomass – fuzzy modeling," Renewable Energy, Elsevier, vol. 66(C), pages 747-758.
    • Handle: RePEc:eee:renene:v:66:y:2014:i:c:p:747-758
    DOI: 10.1016/j.renene.2014.01.014
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    References listed on IDEAS

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    1. Andre Faaij, 2006. "Modern Biomass Conversion Technologies," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 11(2), pages 335-367, March.
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    1. Dhyani, Vaibhav & Bhaskar, Thallada, 2018. "A comprehensive review on the pyrolysis of lignocellulosic biomass," Renewable Energy, Elsevier, vol. 129(PB), pages 695-716.
    2. Kasmuri, N.H. & Kamarudin, S.K. & Abdullah, S.R.S. & Hasan, H.A. & Som, A.Md., 2017. "Process system engineering aspect of bio-alcohol fuel production from biomass via pyrolysis: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 914-923.

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