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Supply chain design under uncertainty for advanced biofuel production based on bio-oil gasification

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  • Li, Qi
  • Hu, Guiping

Abstract

An advanced biofuels supply chain is proposed to reduce biomass transportation costs and take advantage of the economics of scale for a gasification facility. In this supply chain, biomass is converted to bio-oil at widely distributed small-scale fast pyrolysis plants, and after bio-oil gasification, the syngas is upgraded to transportation fuels at a centralized biorefinery. A two-stage stochastic programming is formulated to maximize biofuel producers' annual profit considering uncertainties in the supply chain for this pathway. The first stage makes the capital investment decisions including the locations and capacities of the decentralized fast pyrolysis plants as well as the centralized biorefinery, while the second stage determines the biomass and biofuels flows. A case study based on Iowa in the U.S. illustrates that it is economically feasible to meet desired demand using corn stover as the biomass feedstock. The results show that the locations of fast pyrolysis plants are sensitive to uncertainties while the capacity levels are insensitive. The stochastic model outperforms the deterministic model in the stochastic environment, especially when there is insufficient biomass. Also, farmers' participation can have a significant impact on the profitability and robustness of this supply chain.

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  • Li, Qi & Hu, Guiping, 2014. "Supply chain design under uncertainty for advanced biofuel production based on bio-oil gasification," Energy, Elsevier, vol. 74(C), pages 576-584.
    • Handle: RePEc:eee:energy:v:74:y:2014:i:c:p:576-584
    DOI: 10.1016/j.energy.2014.07.023
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    4. Li, Yuanzhe, 2019. "Modeling Bioenergy Supply Chains: Feedstocks Pretreatment, Integrated System Design Under Uncertainty," Institute of Transportation Studies, Working Paper Series qt1539g5sj, Institute of Transportation Studies, UC Davis.
    5. Debnath, Biswajit & El-Hassani, Rihab & Chattopadhyay, Amit K. & Kumar, T. Krishna & Ghosh, Sadhan K. & Baidya, Rahul, 2022. "Time evolution of a Supply Chain Network: Kinetic modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
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    7. Fattahi, Mohammad & Govindan, Kannan, 2018. "A multi-stage stochastic program for the sustainable design of biofuel supply chain networks under biomass supply uncertainty and disruption risk: A real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 534-567.
    8. Alizadeh, Reza & Lund, Peter D. & Soltanisehat, Leili, 2020. "Outlook on biofuels in future studies: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    9. Zheng, Ji-Lu & Zhu, Ya-Hong & Zhu, Ming-Qiang & Wu, Hai-Tang & Sun, Run-Cang, 2018. "Bio-oil gasification using air - Steam as gasifying agents in an entrained flow gasifier," Energy, Elsevier, vol. 142(C), pages 426-435.
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