Evaluation of biorefinery configurations through a dynamic model-based platform: Integrated operation for bioethanol and xylitol co-production from lignocellulose


An extended DLB 1.0 modelling platform version (towards a biorefinery) was done.

Downstream processes for bioethanol were added to previous modelling platform.

The addition of xylitol production was included in four process configurations.

Energy production from solid remains combustion was evaluated to use in the process.

Results showed a feasible biorefinery configuration for biofuels and bioproducts


This study presents a feasibility analysis of simultaneous bioethanol and xylitol production from lignocellulosic materials. In addition with the in situ power generation analysis employing the residual solids not converted in the process. This work is an extension of the Dynamic Lignocellulosic Bioethanol 1.0 modelling platform (Morales-Rodriguez et al., Bioresour Technol 2011; 102: 1174–84) in four process configurations that included operation in both continuous and continuous with recycling of unconverted materials. The benchmarking criteria employed was the potential profit of combined bioethanol and xylitol products. The best process configuration was simultaneous saccharification and co-fermentation in continuous with recycling and continuous production of xylitol with 11.4% higher for combined production of bioethanol and xylitol compared with the selected base case (simultaneous saccharification and continuous co-fermentation). Besides, integrating the energy generation using the remaining solid materials and energy balance, allowed to determine that the energy necessary for the production process configurations could be generated with the residues from each configuration. The energy produced from solid material combustion was in the range of 1.9 and 2.2 times higher than the energy needed for each configuration. The potential depleted carbon dioxide from crude oil for energy production was up to 32,194 kg/h.


  • Biorefinery;
  • Xylitol;
  • Bioethanol;
  • Model-based evaluation;
  • Process configurations

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