A linear programming optimization model of woody biomass logistics integrating infield drying as a cost-saving preprocess in Michigan

Because of the greater demand in using woody biomass for bioenergy and bio-based products, feedstock supply chain optimization becomes more important to decrease supply chain logistics costs. As a primary component in the biomass feedstock supply chain, the storage of harvested woody biomass can directly affect transportation cost, biomass quality, and combustion efficiency. An improved operations system structured with linear programming was developed for minimizing the total cost of woody biomass preprocessing, storage, and transportation. The improved operations system was applied in a simulated case study for a power plant in Michigan. In addition, a simulated second feedstock end user was added to the operations system to further test the model. The results showed that the improved operations system could lower supply chain logistics costs, improve feedstock quality, and simultaneously meet the feedstock end user's demand. The sensitivity analysis indicated that the additional profit from selling higher-quality feedstock could offset the increased transportation cost for up to 171 miles. On average, every 1 percent decrease in biomass moisture content can result in a decrease of $760.68 in total cost and a reduction of 52.1 green tons of delivered biomass to satisfy the end user's demands. The operation details suggested by the improved operations system can be used as a guideline of real operations to achieve the lowest possible operations cost. The additional profit return from selling higher-quality feedstock needs to be quantified for various conversion and upgrading options besides direct combustion in the future.