Modeling and Analysis of the Logistical Challenge of Supplying Biomass for Biofuel and Biopower
Monday, March 2, 2020
The logistics challenge of using biomass feedstocks is huge with vast quantities of feedstock moved, stored and processed plus the need to accommodate production variation. Logistics costs have been estimated to be large, ranging to over 30% of overall cost of biomass fueled-forms of bioenergy. However, studies have shown that the supply chain cost can be reduced by 40 to 50%. It is imperative to address supply chain design through modeling and analysis.
Hence, Dr. Bruce McCarl, Regents Professor at Texas A&M University (TAMU), College Station, collaborated with Drs. Stephen Searcy (TAMU), Jeffrey Vitale (Oklahoma State University), and Neil Geismar (TAMU) to develop a modeling framework aimed at improving efficiency of biomass supply chains with a long term goal of reducing final product cost by 15%, enhancing market penetration and improving sustainability.
McCarl’s research group developed a comprehensive model for the design of logistical, supply chain systems that exploit regional seasonality of biomass supply and examined whether feedstock diversification lowers storage needs. The team also looked at yield risk management and means for reduction in logistics costs. The project considered perennial grasses, woody biomass, agricultural residues, and logging residues.
“We used a combination of an ArcGIS and Mixed Integer Linear Programming Model (MILP) to generate a feedstock-delivering network that optimizes total cost including the costs of facility construction, storage, transport, feedstock cost, pelleting and processing,” McCarl said.
“We implemented the model in two case studies in Texas High Plains and Eastern Texas, and one in Oklahoma. We used the case study models to study the optimal logistics systems plus the benefits of using or omitting possible logistics components,” McCarl added.
The version of the model used in Texas is already available online.
“We found that the use of pelleting allowed stranded feedstocks to be employed. Our model determined that the use of a feedstock with year round availability reduced costs by more than 25%, and the use of multiple feedstocks resulted in a substantial cost reduction due to lower storage levels,” McCarl said. “We observed that the use of spatial details influences exact supply chain configuration. The model also revealed that either ethanol prices need to go up or processing costs go down, or some other form of revenue must be present in order for cellulosic feedstocks to be cost competitive.
This project was funded by the U.S. Department of Agriculture-National Institute of Food and Agriculture (USDA-NIFA) through the South Central Sun Grant Program.