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Title: Impact of the biorefinery size on the logistics of corn stover supply – A scenario analysis

Abstract

In this study, three scenarios are considered to quantify the impact of the biorefinery size on the required biomass logistical resources. The biorefinery scenarios include small scale (175 dt/day)-SS, medium scale (520 dt/day)-MS and large scale (860 dt/day)-LS. These scenarios are compared against the following logistical resources (1) harvest area and contracted fields, (2) logistics equipment fleet and the workforce to run this fleet and (3) intermediate storage sites and their biomass inventory levels. To this end, the IBSAL-MC simulation model is applied to a corn stover logistics system in Southwestern Ontario. The obtained results show (1) the harvest area and the number of contracted fields increase by 65% and 78% from the SS scenario to the MS and LS scenarios, respectively, (2) the average biomass delivered costs are estimated to be $82.09, $87.49 and $93.75/dry tonne in the SS, MS and LS scenarios. The increase in the capital costs to develop a dedicated logistics equipment fleet are estimated to be far greater than the increase in the delivered costs as the size of the biorefinery increases. The upfront capital costs are estimated to be 6.72 dollars, 21.83 and 35.51 million in these scenarios. To run the logistics equipment fleetmore » efficiently, 37, 136 and 235 well-trained operators are required in the SS, MS ad LS scenarios, respectively, and (3) the inventory level and the land requirement for storage in the MS and LS scenarios are estimated to be 225% and 425% greater than those of the SS scenario. The sensitivity analysis indicates that the logistical resources are highly sensitive to corn yield and farm participation rate. Overall, this study shows the importance of considering the size of the required logistical resources and the associated level of logistical complexity in evaluating the economic viability of a biorefinery project.« less

Authors:
 [1];  [1];  [1];  [2];  [3];  [1]
  1. Univ. of British Columbia, Vancouver, BC (Canada)
  2. (ORNL), Oak Ridge, TN (United States)
  3. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1357969
Alternate Identifier(s):
OSTI ID: 1414494
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Applied Energy
Additional Journal Information:
Journal Volume: 198; Journal Issue: C; Journal ID: ISSN 0306-2619
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; logistics; corn stover; biorefinery; simulation; cellulosic sugar; IBSAL-MC

Citation Formats

Wang, Yu, Ebadian, Mahmood, Sokhansanj, Shahab, Oak Ridge National Lab., Webb, Erin, and Lau, Anthony. Impact of the biorefinery size on the logistics of corn stover supply – A scenario analysis. United States: N. p., 2017. Web. doi:10.1016/j.apenergy.2017.03.056.
Wang, Yu, Ebadian, Mahmood, Sokhansanj, Shahab, Oak Ridge National Lab., Webb, Erin, & Lau, Anthony. Impact of the biorefinery size on the logistics of corn stover supply – A scenario analysis. United States. https://doi.org/10.1016/j.apenergy.2017.03.056
Wang, Yu, Ebadian, Mahmood, Sokhansanj, Shahab, Oak Ridge National Lab., Webb, Erin, and Lau, Anthony. Thu . "Impact of the biorefinery size on the logistics of corn stover supply – A scenario analysis". United States. https://doi.org/10.1016/j.apenergy.2017.03.056. https://www.osti.gov/servlets/purl/1357969.
@article{osti_1357969,
title = {Impact of the biorefinery size on the logistics of corn stover supply – A scenario analysis},
author = {Wang, Yu and Ebadian, Mahmood and Sokhansanj, Shahab and Oak Ridge National Lab. and Webb, Erin and Lau, Anthony},
abstractNote = {In this study, three scenarios are considered to quantify the impact of the biorefinery size on the required biomass logistical resources. The biorefinery scenarios include small scale (175 dt/day)-SS, medium scale (520 dt/day)-MS and large scale (860 dt/day)-LS. These scenarios are compared against the following logistical resources (1) harvest area and contracted fields, (2) logistics equipment fleet and the workforce to run this fleet and (3) intermediate storage sites and their biomass inventory levels. To this end, the IBSAL-MC simulation model is applied to a corn stover logistics system in Southwestern Ontario. The obtained results show (1) the harvest area and the number of contracted fields increase by 65% and 78% from the SS scenario to the MS and LS scenarios, respectively, (2) the average biomass delivered costs are estimated to be $82.09, $87.49 and $93.75/dry tonne in the SS, MS and LS scenarios. The increase in the capital costs to develop a dedicated logistics equipment fleet are estimated to be far greater than the increase in the delivered costs as the size of the biorefinery increases. The upfront capital costs are estimated to be 6.72 dollars, 21.83 and 35.51 million in these scenarios. To run the logistics equipment fleet efficiently, 37, 136 and 235 well-trained operators are required in the SS, MS ad LS scenarios, respectively, and (3) the inventory level and the land requirement for storage in the MS and LS scenarios are estimated to be 225% and 425% greater than those of the SS scenario. The sensitivity analysis indicates that the logistical resources are highly sensitive to corn yield and farm participation rate. Overall, this study shows the importance of considering the size of the required logistical resources and the associated level of logistical complexity in evaluating the economic viability of a biorefinery project.},
doi = {10.1016/j.apenergy.2017.03.056},
journal = {Applied Energy},
number = C,
volume = 198,
place = {United States},
year = {Thu Mar 23 00:00:00 EDT 2017},
month = {Thu Mar 23 00:00:00 EDT 2017}
}

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Works referencing / citing this record:

Simulation Modeling for Reliable Biomass Supply Chain Design Under Operational Disruptions
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Plant capacity level and location as a mechanism for sustainability in biomass supply chain
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