Modeling of thermochemically liquefied biomass products and heat of formation for process energy assessment

E.M. Lozano, T.H. Pedersen and L.A. Rosendahl

Applied Energy, 2019, vol. 254, issue C

Abstract: A generic approach is proposed for the estimation of advanced biocrudes properties from liquefied biomass and the enthalpy of formation of biomass feedstocks applicable to the modeling of biomass conversion processes where the exact stoichiometry and kinetics are unknown, such as pyrolysis, solvolysis and hydrothermal liquefaction. The enthalpy of formation of the biomass is estimated through a direct correlation based on ultimate and proximate analysis, whose parameters can easily be fitted with experimental data available from sources such as the Phillys database for different biomass types and implemented in process simulators such as Aspen Plus®. For the biocrude modeling, a multi-objective optimization model is proposed that refines the selection of model compounds to match measured bulk thermochemical and physical properties. Parameter fitting and multi-objective optimization were both performed in Matlab® and the codes are available in the supplementary material. As a case study, the optimization model was applied to two different oils obtained via hydrothermal liquefaction and pyrolysis of woody biomass. The first case was further studied in order to estimate the impact of the proposed models in the energy requirements. The process was implemented in Aspen Plus® but the methodology is applicable to other simulation tools. The results show that the methods for estimating enthalpies of formation have a high impact on the energy balance and consequently the models developed allow a more accurate estimation of the energy requirement in the reactor. This is a key element in making accurate heat integration and techno-economic analyses of thermochemical conversion processes.

Keywords: Modeling; Biomass; HTL; Pyrolysis; Heat of formation; Energy balance (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.apenergy.2019.113654

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