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Techno-Economic Analysis of decentralized preprocessing systems for fast pyrolysis biorefineries with blended feedstocks in the southeastern United States

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  • Lan, Kai
  • Ou, Longwen
  • Park, Sunkyu
  • Kelley, Stephen S.
  • English, Burton C.
  • Yu, T. Edward
  • Larson, James
  • Yao, Yuan

Abstract

This study evaluated the economic feasibility of fast pyrolysis biorefineries fed with blended pine residues and switchgrass in the Southeastern U.S. with different supply chain design. Previous techno-economic analyses (TEA) have focused on either blended biomass or decentralized preprocessing without investigating the impacts of varied process parameters, technology options, and real-world biomass distribution. This study fills the literature gap by modeling scenarios for different biomass blending ratios, biorefinery and preprocessing site (so-called depot) capacities, and alternative preprocessing technologies. High-resolution, real-world geospatial data were analyzed using Geographic Information Systems to facilitate supply chain design and TEA. For a decentralized system, the minimum fuel selling price (MFSP) of biofuel was $3.92–$4.33 per gallon gasoline equivalent (GGE), while the MFSP for the centralized biorefinery at the same capacities ranged between $3.75–$4.02/GGE. Implementing a high moisture pelleting process depot rather than a conventional pelleting process lowered the MFSP by $0.03–$0.17/GGE. Scenario analysis indicated decreased MFSP with increasing biorefinery capacities but not necessarily with increasing depot size. Medium-size depots (500 OMDT/day) achieved the lowest MFSP. This analysis identified the optimal blending ratios for two preprocessing technologies at varied depot sizes. Counterintuitively, increasing the proportion of higher cost switchgrass reduced the MFSP for large biorefineries (>5000 ODMT/day), but increased the MFSP for small biorefineries (1000–2500 ODMT/day). Although the decentralized systems have a higher MFSP based on current analysis, it has other potential benefits such as mitigated supply chain risks and improved feedstock quality that are difficult to be quantified in this TEA.

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  • Lan, Kai & Ou, Longwen & Park, Sunkyu & Kelley, Stephen S. & English, Burton C. & Yu, T. Edward & Larson, James & Yao, Yuan, 2021. "Techno-Economic Analysis of decentralized preprocessing systems for fast pyrolysis biorefineries with blended feedstocks in the southeastern United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
  • Handle: RePEc:eee:rensus:v:143:y:2021:i:c:s1364032121001751
    DOI: 10.1016/j.rser.2021.110881
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    2. Bidhan Bhuson Roy & Qingshi Tu, 2022. "A review of system dynamics modeling for the sustainability assessment of biorefineries," Journal of Industrial Ecology, Yale University, vol. 26(4), pages 1450-1459, August.
    3. Hossain, Tasmin & Jones, Daniela S. & Hartley, Damon S. & Thompson, David N. & Langholtz, Matthew & Davis, Maggie, 2022. "Nth-plant scenario for forest resources and short rotation woody crops: Biorefineries and depots in the contiguous US," Applied Energy, Elsevier, vol. 325(C).
    4. Conteratto, Caroline & Artuzo, Felipe Dalzotto & Benedetti Santos, Omar Inácio & Talamini, Edson, 2021. "Biorefinery: A comprehensive concept for the sociotechnical transition toward bioeconomy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
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