Modeling Sustainable Aviation Fuel Production from Used Cooking Oil Using Aspen Plus: Cluster-Based Feedstock Composition and Technoeconomic Analyses

The hydroprocessing esters and fatty acids (HEFA) pathway currently serves as a main technology for sustainable aviation fuel (SAF) production. However, the commercial and technical efficiency of this pathway is increasingly constrained by the inherent compositional heterogeneity of waste-based feedstock, particularly used cooking oil (UCO). This variability introduces complexities in ensuring process performance and product distribution. This study integrates a validated Aspen Plus simulation of the HEFA process for SAF production with a K-means clustering framework to systematically quantify the impact of UCO compositional variability. By categorizing feedstock heterogeneity into discrete clusters, the study interprets the sensitivity of process outputs and their subsequent technoeconomic implications. K-means clustering categorized the UCO samples into three distinct groups, based on the fatty acid composition, utility demand, and product distribution. For a designated plant capacity of ca. 66 million liters per year, the technoeconomic analysis yielded a minimum fuel selling price (MFSP) of SAF to be in the range of USD 1.44–1.52 L –1, representing a 2.6–2.8 times increase compared to conventional fossil-based jet fuel. This small range of MFSP results reflects the relatively stable SAF yields observed across all clusters. In contrast, feedstock heterogeneity induces more pronounced variations in utility consumption and coproduct distribution, which represent the key operational differences between the identified groups. The integration of feedstock clustering and technoeconomic evaluation provides insight into the robustness of HEFA pathways for SAF production under realistic feedstock uncertainty.