GIS based discrete event modeling and simulation of biomass supply chain

A consistent, reliable and low cost biomass supply chain is crucial for a sustainable biorefinery. Spatial and temporal variations in biomass yield, weather risk, transport network, machine capacity significantly impacts logistics cost and supply chain performances. The objectives of the study are to develop a sustainable biomass supply chain modeling framework coupled with GIS (Geographic Information System) to estimate feedstock flow rate and delivered cost. The supply chain model was developed and implemented in discrete event simulation platform and tested with Miscanthus crop (biomass) supply chain for 10 years from strip-mined lands in Ohio. The overall cost of biomass delivered to a biorefinery was estimated to 84 $/dry Mg with an average annual plant demand of 200,000 dry Mg. The developed model will be further improved to include energy consumption and environmental impacts of entire biofuels supply chain.