Abstract
The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Defining the future location and supply logistics of conversion plants is imperative to ultimately transform the nation's renewable biomass resources into cost-competitive, high-performance feedstock for production of biofuels and bioproducts. Since the US has put restrictions on production levels of conventional biofuels from edible resources, the nation needs to plan for the widespread accessibility and development of the cellulosic biofuel scenario. Conventional feedstock supply systems will be unable to handle cellulosic biomass nationwide, making it essential to expand the industry with an advanced feedstock supply system incorporating a distributed network of preprocessing depots and conversion plants, or biorefineries. Current studies are mostly limited to designing supply systems for specific regions of the country. We developed a national database with potential locations for depots and biorefineries to meet the nation's target demand of cellulosic biofuel. Blended feedstock with switchgrass and corn stover (harvested by either a two- or three-pass method) are considered in a Mixed Integer Linear Programming model to deliver on-spec biomass that considers both, a desired quantity and quality at the biorefinery. The model solves for a network of varying size depots that supply to biorefineries of 725,000 dry tons/year. A total delivered feedstock cost that is less than $79.07/dry tons (2016$) is evaluated for years 2022, 2030, and 2040. In 2022, 124 depots and 59 biorefineries could be supplied with 42.8 million dt of corn stover and switchgrass. In 2030 and 2040, the total accessible biomass could increase to 215% and 393% respectively when compared to 2022. However, an $8/dry tons reduction in targeted delivery cost could reduce total accessible biomass by 67%. Kansas, Nebraska, South Dakota and Texas were identified as potential states with a strong biofuel economy given that they had six or more biorefineries located in all scenarios. In some scenarios, Colorado, Alabama, Georgia, Minnesota, Mississippi and South Carolina would greatly benefit from a depot network as these could only deliver to a biorefinery in a nearby state. To elaborate the impact of a nationwide consideration, the findings were compared with existing literature for different US regions. We also present results for biorefinery capacities that are double, triple and quadruple in size.
| Original language | English |
|---|---|
| Article number | 116946 |
| Journal | Applied Energy |
| Volume | 294 |
| DOIs | |
| State | Published - Jul 15 2021 |
Funding
This work was funded by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) Bioenergy Technology Office under DOE Idaho Operations Office Contract DEAC07-05ID14517 with Battelle Energy Alliance, LLC, contract DE-AC05-00OR22725 with UT-Battelle, LLC, and USDA Hatch Project funds. The views expressed in this publication do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. We acknowledge help from people from SAS Inc. for their valuable insights and helpful comments towards developing the MILP code: Lincoln Groves, Mark Hartmann, Tom Grant, Imre Pólik, and Rob Pratt. We are also grateful to Mohammad S. Roni from Idaho National Laboratory for his excellent suggestions that helped greatly in the analysis and presentation of this work. The input dataset for the supply curve of this study can be found using the County Download Tool at the Bioenergy Knowledge Discovery Framework open-source database [1]. The published dataset from the results of this study are attached with the manuscript. This work was funded by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) Bioenergy Technology Office under DOE Idaho Operations Office Contract DEAC07-05ID14517 with Battelle Energy Alliance, LLC, contract DE-AC05-00OR22725 with UT-Battelle, LLC, and USDA Hatch Project funds. The views expressed in this publication do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. We acknowledge help from people from SAS Inc. for their valuable insights and helpful comments towards developing the MILP code: Lincoln Groves, Mark Hartmann, Tom Grant, Imre Pólik, and Rob Pratt. We are also grateful to Mohammad S. Roni from Idaho National Laboratory for his excellent suggestions that helped greatly in the analysis and presentation of this work.
Keywords
- Biofuel
- Biomass supply chain
- Corn stover
- Feedstock quality
- Mixed-integer linear programming
- Switchgrass