(49c) Multi-Objective Optimization of Sustainable Middle Distillates from Renewable Feedstocks

Fossil fuels dominate the transportation sector, making it the largest contributor to greenhouse gas emissions in the United States. Particularly, hard-to-decarbonize sectors such as aviation, shipping, and heavy hauling transport are challenging to transition away from fossil fuels since they cannot be easily electrified. Biofuels can be a sustainable substitute for fossil fuels in these sectors. Renewable feedstocks like lignocellulosic biomass can be transformed into low-carbon fuels to partially meet the existing demands of fuels for hard-to-decarbonize sectors. In the last 30 years, a plethora of conversion pathways and catalytic upgrading alternatives for lignocellulosic materials have been discovered. However, identifying optimal routes for transforming lignocellulosic residues into fuels in a cost-effective and environmentally sustainable manner become arduous due to the huge design space.

In this research, we developed a novel superstructure framework to study diverse pathways for biofuels production, specifically middle distillates. Notably, our superstructure systematically allows three decisions levels: the choice of catalysts, biomass upgrading chemistries, and fuel blend composition of middle distillates. The model presents a comprehensive map of current technological alternatives and contains 500 catalytic options, 165 upgrading chemistries, and 320 candidate molecules that can be used to engineer new biofuel blends. Since many of the molecules evaluated have not been used as fuels and have unknown physical properties, we use graph based neural networks to fill this gap.

We formulate the problem of finding the optimal pathway to produce fuel with tailored properties as a multi-objective mixed integer non-linear programming problem. Importantly, since the model is constrained to satisfy a set of desired fuel properties, then, it is possible to identify via optimization, novel fuel products, such as diesel and jet fuels, which match or outperform existing fossil fuel alternatives.

The proposed framework is equipped to identify fuel production pathways based on minimum selling price and greenhouse gas emissions, and we use it to explore the tradeoffs between the cost and environmental sustainability of our biofuel designs.