Optimal Design of Sugar-Cane-Based Biorefinery Networks in Argentina

Abstract

Sugar cane, an extremely abundant agricultural resource, is a key feedstock for the sustainable production of biofuels and bioproducts. Although it is mainly grown for the production of sugar and first-generation ethanol, this grass is a privileged candidate to be processed in biorefineries. This study focuses on the use of mathematical programming to make strategic decisions in the sugar cane value chain. The design task is formulated as a mixed-integer linear model (MILP) that seeks to minimize the total cost of a network of processing, transportation, and storage instances, which include many different technologies and bioproducts. The capabilities of the proposed framework are illustrated through a case study based on four real-scaled scenarios in Argentina. The results show not only the optimal supply chain configuration for different demand patterns but also the technologies operating inside the biorefineries and the possibility of recycling resources. Given a set of specific real parameters, such as biomass availability, product demand, and unit costs, the model is a useful tool for establishing strategic policies in the fields of agribusiness and bioenergy.