Distributed biomass supply chain cost optimization to evaluate multiple feedstocks for a biorefinery
Abstract
Conventional practices of siting all biomass preprocessing operations at the biorefinery is widely believed to be the most cost-effective solution for feedstock supply because of economies of scale. Yet, biomass preprocessing operations could be decentralized by moving the preprocessing operations to distributed biomass preprocessing centers, also known as “depots” located near biomass sources. We present a comparative case study with multiple biomass resources to analyze biorefinery feedstock supply logistics designs having distributed depots and a primary depot co-located with the biorefinery. A mixed-integer linear programming model was developed to simultaneously optimize feedstock sourcing decisions, and optimal preprocessing depot locations and size, utilizing biomass resources from agricultural residue, energy and municipal solid waste to meet carbohydrate specifications and feedstock demand for a biochemical conversion process. Findings from a case study in the US showed that a biorefinery could increase its feedstock supply draw area and supply volume by 57.3%, 177.4% respectively without increasing the feedstock delivered cost by adopting distributed depot-in the feedstock supply chain design. A distributed-depot-based supply chain can be more economical by selecting optimal mix of biomass resource, optimal siting and depot scales during feedstock supply chain design. The results from this study indicate that a biorefinery canmore »
- Publication Date:
- Research Org.:
- Idaho National Lab. (INL), Idaho Falls, ID (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Sustainable Transportation Office. Bioenergy Technologies Office
- OSTI Identifier:
- 1557240
- Alternate Identifier(s):
- OSTI ID: 1779322
- Report Number(s):
- INL/JOU-18-52059-Rev000
Journal ID: ISSN 0306-2619
- Grant/Contract Number:
- AC07-05ID14517
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Applied Energy
- Additional Journal Information:
- Journal Volume: 254; Journal Issue: C; Journal ID: ISSN 0306-2619
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 09 - BIOMASS FUELS; 97 - MATHEMATICS AND COMPUTING; Feedstock supply chain; mixed-integer linear programming; supply radius; depot; biomass; dynamic blending
Citation Formats
Roni, Mohammad S., Thompson, David N., and Hartley, Damon S. Distributed biomass supply chain cost optimization to evaluate multiple feedstocks for a biorefinery. United States: N. p., 2019.
Web. doi:10.1016/j.apenergy.2019.113660.
Roni, Mohammad S., Thompson, David N., & Hartley, Damon S. Distributed biomass supply chain cost optimization to evaluate multiple feedstocks for a biorefinery. United States. https://doi.org/10.1016/j.apenergy.2019.113660
Roni, Mohammad S., Thompson, David N., and Hartley, Damon S. Wed .
"Distributed biomass supply chain cost optimization to evaluate multiple feedstocks for a biorefinery". United States. https://doi.org/10.1016/j.apenergy.2019.113660. https://www.osti.gov/servlets/purl/1557240.
@article{osti_1557240,
title = {Distributed biomass supply chain cost optimization to evaluate multiple feedstocks for a biorefinery},
author = {Roni, Mohammad S. and Thompson, David N. and Hartley, Damon S.},
abstractNote = {Conventional practices of siting all biomass preprocessing operations at the biorefinery is widely believed to be the most cost-effective solution for feedstock supply because of economies of scale. Yet, biomass preprocessing operations could be decentralized by moving the preprocessing operations to distributed biomass preprocessing centers, also known as “depots” located near biomass sources. We present a comparative case study with multiple biomass resources to analyze biorefinery feedstock supply logistics designs having distributed depots and a primary depot co-located with the biorefinery. A mixed-integer linear programming model was developed to simultaneously optimize feedstock sourcing decisions, and optimal preprocessing depot locations and size, utilizing biomass resources from agricultural residue, energy and municipal solid waste to meet carbohydrate specifications and feedstock demand for a biochemical conversion process. Findings from a case study in the US showed that a biorefinery could increase its feedstock supply draw area and supply volume by 57.3%, 177.4% respectively without increasing the feedstock delivered cost by adopting distributed depot-in the feedstock supply chain design. A distributed-depot-based supply chain can be more economical by selecting optimal mix of biomass resource, optimal siting and depot scales during feedstock supply chain design. The results from this study indicate that a biorefinery can utilize dynamic blending to meet the feedstock quality specifications as well as larger supply radius in the distributed depot-based supply chain design to access more available biomass to handle potential feedstock supply uncertainty.},
doi = {10.1016/j.apenergy.2019.113660},
journal = {Applied Energy},
number = C,
volume = 254,
place = {United States},
year = {Wed Aug 07 00:00:00 EDT 2019},
month = {Wed Aug 07 00:00:00 EDT 2019}
}
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Figures / Tables:
Figure 1: Feedstock supply chain design of a biorefinery sourcing multiple biomass resources with distributed depots. This supply chain design incorporates both bale and pellet transportation. 3-P CS=three pass corn stover, 2-P CS= two pass corn stover, SG=switchgrass
Figures / Tables found in this record: