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Published November 2019 | Version v1
Journal article

Distributed biomass supply chain cost optimization to evaluate multiple feedstocks for a biorefinery

  • 1. Data and Software Sciences, Idaho National Laboratory, ID (United States)
  • 2. Bioenergy Technologies Department, Idaho National Laboratory, ID (United States)

Description

Highlights: • Developed an optimization method to study optimal use of biomass. • Distributed depot-based supply chain can increase supply chain draw area by 57.3%. • Distributed depot-based supply chain can increase the supply volume by 177.4%. • Showed dynamic blending concept to meet the feedstock quality specifications. -- 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. However, biomass preprocessing operations could be decentralized by moving the preprocessing operations to distributed biomass preprocessing centers, also known as "depots" located near biomass sources. This study presents 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. Results 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 findings 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.

Additional details

Identifiers

DOI
10.1016/j.apenergy.2019.113660;
PII
S0306261919313479;

Publishing Information

Journal Title
Applied Energy
Journal Volume
254
Journal Page Range
vp.
ISSN
0306-2619
CODEN
APENDX

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55008029
Subject category
S09: BIOMASS FUELS;
Descriptors DEI
AGRICULTURAL WASTES; BIOMASS; CARBOHYDRATES; DESIGN; LINEAR PROGRAMMING; OPTIMIZATION; SOLID WASTES; SPECIFICATIONS
Descriptors DEC
CALCULATION METHODS; ENERGY SOURCES; ORGANIC COMPOUNDS; ORGANIC WASTES; RENEWABLE ENERGY SOURCES; WASTES

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.