Design and scheduling of agricultural biomass supply chain for a cellulosic ethanol plant

• Main Author: Ebadian, Mahmood
• Language: English
• Published: University of British Columbia 2013
• Online Access: http://hdl.handle.net/2429/44439

The overall objective of this dissertation is to design and schedule a highly constrained agricultural biomass supply chain to meet the daily biomass demand of a commercial-sized cellulosic ethanol plant at the minimum delivery cost possible. To this end, an integrated simulation/optimization model is developed. The developed simulation model plans and schedules a flow of multi-biomass in the supply chain to meet the daily demand subject to the dynamics and stochasticity of the supply chain. The developed optimization model is used to meet the annual demand at the minimum delivery cost by prescribing the design of the supply chain. The design includes the selection of farms, the location of storage sites, and the assignment of the farms to the storage sites. It also determines the flow of biomass between farms, storage sites and the plant. The integration of the models is made via an iterative procedure. In this procedure, the design is used in the simulation model to manage the flow of biomass in the supply chain. On the other hand, the outputs of the simulation model are used as the inputs of the optimization model to adjust the design. The iterative procedure continues until no improvement can be made in the design. The integrated model is applied to a proposed ethanol plant in Prince Albert, Saskatchewan. The numbers of selected farms and the established storage sites in the integrated model are reduced by 6% and 10%, respectively, compared to the optimization model. Compared to the simulation model, the integrated model leads to the reduction in number of farms (15%), number of storage sites (57%), amount of purchased biomass from farmers (7%), harvested area (13%), supply radius (13%), number of maximum trucks (2 trucks), supply costs (6-12%), energy input (19%), and emitted CO₂ (12%). The results of the sensitivity analysis reveal that the most influential parameter on the design is biomass yield. In addition, bale bulk density and in-field and road transportation operations have the highest impacts on the total supply cost compared to other input parameters.