Waste-to-bioethanol supply chain network: A deterministic model

Bioethanol (bio-EtOH) is commonly used as a renewable biofuel additive for gasoline. A novel technology producing bio-EtOH from anaerobic digestion of organic waste (OW) has recently attracted attention. This work presents a deterministic mixed integer linear programming model for the optimal location of OW-based bio-EtOH biorefineries. The proposed model considers OW treatment location, bio-EtOH biorefineries, and truck transport links as a supply chain network (SCN) approach. The objective function of the developed model is to minimize the total bio-EtOH levelized cost (ELC) while satisfying the model constraints consisting of equalities (e.g., mass and energy balances for the bio-EtOH biorefinery) and inequalities (e.g., capacity of the bio-EtOH refinery, truck transport) to meet the regional demands of bio-EtOH. To validate the optimization model, a case study based on a real scenario for South Korea in 2030 was conducted for different bio-EtOH blending rates (E10, E20, E85, E100). The case study results indicate that ELC of E10 containing 10% bio-EtOH from OW products combined with gasoline is USD 3.65/gallon. As the blending rate of bio-EtOH increases, ELC increases to USD 4.36/gallon for E20, USD 8.99/gallon for E85, and USD 10.05/gallon for E100. The optimization results can help determine SCN strategies for an OW-based biofuel economy.

Automated summary

The article introduces a new technology for producing bioethanol from organic waste, and proposes an optimization model to determine the optimal location of bioethanol refineries in order to reduce costs. The validity of the model was demonstrated through a case study on South Korea in 2030.