Optimization of an integrated grain-biomass-ethanol supply chain with event-based decision-making
type: CreativeWork
description: There is an increasing demand for renewable energy in the US, but high investment costs and low energy yield often slow the adoption of renewable technologies. When considering biomass for fuel production, farm and distribution management become key in turning such renewable alternatives into successful large-scale systems. This research effort proposes an integrated approach to a grain-biomass-ethanol supply chain, with the purpose of reducing costs by adapting and expanding the current US corn system. Two modeling tools were applied to assess supply chain performance. First, BioGrain is a mixed-integer linear program that optimizes machinery selection and grain harvesting schedule for different farm sizes. Second, BioGen is a multi-objective model that optimizes biomass distribution by minimizing system costs and GHG emissions. The models were applied to a case study in Illinois. A three-stage supply chain was considered: farms, centralized storage and pre-processing (CSP) facilities and dry-grind ethanol plants. Champaign county farms were chosen as the suppliers for both corn and biomass, and existing Illinois ethanol plants were considered as potential facilities to adopt the co-fermentation process. BioGrain results show that, by optimizing harvesting schedule and equipment selection, the overall grain system efficiency can be enhanced, and grain losses can be reduced for individual farms. BioGen results show that the integrated grain and biomass conversion to ethanol through co-fermentation can significantly reduce biomass-related costs when compared to stover-only biorefineries, and that GHG emissions aren’t significantly different when comparing co-fermentation and stover-only biorefineries. The optimization also shows that, in order to reduce costs and GHG emissions, the biomass should be sent to a CSP facility also located in Champaign county, and that the dry grind plant in Ford county would be the optimal destination for co-fermentation. This research c…
abstract: There is an increasing demand for renewable energy in the US, but high investment costs and low energy yield often slow the adoption of renewable technologies. When considering biomass for fuel production, farm and distribution management become key in turning such renewable alternatives into successful large-scale systems. This research effort proposes an integrated approach to a grain-biomass-ethanol supply chain, with the purpose of reducing costs by adapting and expanding the current US corn system. Two modeling tools were applied to assess supply chain performance. First, BioGrain is a mixed-integer linear program that optimizes machinery selection and grain harvesting schedule for different farm sizes. Second, BioGen is a multi-objective model that optimizes biomass distribution by minimizing system costs and GHG emissions. The models were applied to a case study in Illinois. A three-stage supply chain was considered: farms, centralized storage and pre-processing (CSP) facilities and dry-grind ethanol plants. Champaign county farms were chosen as the suppliers for both corn and biomass, and existing Illinois ethanol plants were considered as potential facilities to adopt the co-fermentation process. BioGrain results show that, by optimizing harvesting schedule and equipment selection, the overall grain system efficiency can be enhanced, and grain losses can be reduced for individual farms. BioGen results show that the integrated grain and biomass conversion to ethanol through co-fermentation can significantly reduce biomass-related costs when compared to stover-only biorefineries, and that GHG emissions aren’t significantly different when comparing co-fermentation and stover-only biorefineries. The optimization also shows that, in order to reduce costs and GHG emissions, the biomass should be sent to a CSP facility also located in Champaign county, and that the dry grind plant in Ford county would be the optimal destination for co-fermentation. This research c…
author: Spranger Correia de Oliveira, Ana Paula
language: en
keywords: biomass logistics, supply chain, co-fermentation, optimization, mixed integer linear program
date published: 2021-09-17T04:04:25Z
date modified: 2026-07-22T22:24:52Z
provider: University of Illinois - Urbana-Champaign
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Illinois at Urbana-Champaign

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2142/110812