A Computer-aided Operations System to Optimize Woody Biomass Feedstock Storage and Transportation

Abstract. Due to the greater demand in bioenergy and bio-based products, feedstock supply chain optimization is critical to decrease the logistics costs. As a primary phase in the biomass feedstock supply logistics, the storage of harvested biomass can directly affect transportation cost, biomass quality and its combustion efficiency. A model structured with linear programming was developed to determine an optimized biomass pre-processing, storage, and transportation strategy. The optimization model was applied in a simulated case study for an energy plant in Michigan. The results indicated that lower supply chain logistics costs and higher feedstock quality could be achieved by applying an optimized supply chain strategy while simultaneously meeting the feedstock user’s demand. The sensitivity analysis indicated that transportation distance had no impact on the supply chain logistics strategy. The additional profit brought by higher quality biomass can offset the increased transportation cost for up to 151 miles. Through biomass MC increases, logging residue pile is always the preferred storage method. The impact of biomass moisture content (MC) is concluded to be more significant when it is higher. Through the increase of biomass MC, more biomass is required to satisfy the same energy demand. In average, every 1% increase in biomass MC can result in $760.68 increase in total cost and 52.1 more green tons biomass to satisfy the four-month energy demands.