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:
- Publication Date:
- Research Org.:
- Univ. of Wisconsin, Madison, WI (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1769496
- Alternate Identifier(s):
- OSTI ID: 1501833
- Grant/Contract Number:
- FC02-07ER64494
- Resource Type:
- Published Article
- Journal Name:
- Applied Energy
- Additional Journal Information:
- Journal Name: Applied Energy Journal Volume: 216 Journal Issue: C; Journal ID: ISSN 0306-2619
- Publisher:
- Elsevier
- Country of Publication:
- United Kingdom
- 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 Kingdom: 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 Kingdom. https://doi.org/10.1016/j.apenergy.2018.02.077
Ng, Rex T. L., Kurniawan, Daniel, Wang, Hua, Mariska, Brian, Wu, Wenzhao, and Maravelias, Christos T. Sun .
"Integrated framework for designing spatially explicit biofuel supply chains". United Kingdom. https://doi.org/10.1016/j.apenergy.2018.02.077.
@article{osti_1769496,
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 Kingdom},
year = {Sun Apr 01 00:00:00 EDT 2018},
month = {Sun Apr 01 00:00:00 EDT 2018}
}
https://doi.org/10.1016/j.apenergy.2018.02.077
Web of Science
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