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Title: Integrated framework for designing spatially explicit biofuel supply chains

Abstract

We present a framework that allows us to utilize high-resolution spatial data to design biomass-to-fuel supply chains. Specifically, we first present how to extract crop data from the Agricultural Model Intercomparison and Improvement Project packages, and then develop a method to combine these data with a historical cropland data layer, to generate spatial data with user-specified resolution. Next, we develop a general approach to determine the potential depot and biorefinery locations, and calculate the actual fiow path distance between facilities using Geographic Information Systems methods. Since spatially explicit data lead to large-scale supply chain networks, we develop preprocessing algorithms that allow us to remove arcs that will never be used in an optimal solution, thereby reducing the size of the network under consideration. We then present a multi-period mixed-integer linear programming model that accounts for the selection of depot and biorefinery locations and their capacities, shipping and inventory planning, as well as the selection of pretreatment and conversion technologies, and transportation modes. Finally, we demonstrate the application of our framework using a case study of corn stover-to-ethanol supply chain in Wisconsin.

Authors:
 [1]; ORCiD logo [1]; ORCiD logo [1];  [1];  [1];  [1]
  1. Univ. of Wisconsin, Madison, WI (United States)
Publication Date:
Research Org.:
Univ. of Wisconsin, Madison, WI (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1501833
Grant/Contract Number:  
FC02-07ER64494
Resource Type:
Accepted Manuscript
Journal Name:
Applied Energy
Additional Journal Information:
Journal Volume: 216; Journal Issue: C; Journal ID: ISSN 0306-2619
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS

Citation Formats

Ng, Rex T. L., Kurniawan, Daniel, Wang, Hua, Mariska, Brian, Wu, Wenzhao, and Maravelias, Christos T. Integrated framework for designing spatially explicit biofuel supply chains. United States: N. p., 2018. Web. doi:10.1016/j.apenergy.2018.02.077.
Ng, Rex T. L., Kurniawan, Daniel, Wang, Hua, Mariska, Brian, Wu, Wenzhao, & Maravelias, Christos T. Integrated framework for designing spatially explicit biofuel supply chains. United States. doi:10.1016/j.apenergy.2018.02.077.
Ng, Rex T. L., Kurniawan, Daniel, Wang, Hua, Mariska, Brian, Wu, Wenzhao, and Maravelias, Christos T. Fri . "Integrated framework for designing spatially explicit biofuel supply chains". United States. doi:10.1016/j.apenergy.2018.02.077. https://www.osti.gov/servlets/purl/1501833.
@article{osti_1501833,
title = {Integrated framework for designing spatially explicit biofuel supply chains},
author = {Ng, Rex T. L. and Kurniawan, Daniel and Wang, Hua and Mariska, Brian and Wu, Wenzhao and Maravelias, Christos T.},
abstractNote = {We present a framework that allows us to utilize high-resolution spatial data to design biomass-to-fuel supply chains. Specifically, we first present how to extract crop data from the Agricultural Model Intercomparison and Improvement Project packages, and then develop a method to combine these data with a historical cropland data layer, to generate spatial data with user-specified resolution. Next, we develop a general approach to determine the potential depot and biorefinery locations, and calculate the actual fiow path distance between facilities using Geographic Information Systems methods. Since spatially explicit data lead to large-scale supply chain networks, we develop preprocessing algorithms that allow us to remove arcs that will never be used in an optimal solution, thereby reducing the size of the network under consideration. We then present a multi-period mixed-integer linear programming model that accounts for the selection of depot and biorefinery locations and their capacities, shipping and inventory planning, as well as the selection of pretreatment and conversion technologies, and transportation modes. Finally, we demonstrate the application of our framework using a case study of corn stover-to-ethanol supply chain in Wisconsin.},
doi = {10.1016/j.apenergy.2018.02.077},
journal = {Applied Energy},
number = C,
volume = 216,
place = {United States},
year = {2018},
month = {2}
}

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Cited by: 11 works
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