4.6 Article

Multiperiod Design and Optimization of Coprocessing of Vacuum Gas Oil and Bio-oil Integrating Supply Fluctuations of Lignocellulosic and Algal Biomass

Journal

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
Volume 60, Issue 20, Pages 7667-7677

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.iecr.1c00181

Keywords

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Funding

  1. Natural Science Foundation of China (NSFC) [21808183]
  2. Natural Science Foundation of Shaanxi Province [2020JQ-577]
  3. Young Talent Fund of University Association for Science and Technology in Shaanxi, China [20190602]
  4. Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China [ICT2021B01]

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Integration of monthly changes in lignocellulosic biomass production and algae growth rate is used in designing and optimizing a coprocessing system to minimize total annual cost. Feed compositions for fast pyrolysis in each period are determined based on the synergistic effect of copyrolysis of the two biomasses, with operational factors near 100% due to large capital investments in fast pyrolysis and algal growth process.
The coprocessing of bio-oil and vacuum gas oil has been demonstrated as a cost-effective way to utilize bioenergy. A multiperiod model is built to design and optimize of the coprocessing system by integrating monthly changes of lignocellulosic biomass production and algae growth rate. The case study showed that the optimal configurations of a coprocessing system with a minimized total annual cost can be attained with the proposed multiperiod model. The feed compositions of lignocellulosic and algal biomass for fast pyrolysis in each period were obtained by integrating the synergistic effect of copyrolysis of the two biomasses. Due to the relatively large capital investments of fast pyrolysis and algal growth process, the operational factors of the two processes were near 100% in all of the periods. A sensitivity analysis was also carried out to discuss the parameter effects. The proposed model not only can be used in the optimization of the coprocessing system but also can be adopted in bioenergy utilization.

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