(459h) A Risk-Conscious Optimization Model for Sustainable Aviation Fuel Production in the Brazilian Sugarcane Industry

Brazil is a global leader in renewable energy and sustainability efforts. For example, 44.1% of energy in Brazil came from renewable sources compared to only 10.4% in the US [1]. Additionally, Brazil was one of the first countries to start using biomass fuels as a result of multiple incentive programs the Brazilian government has supported since the 1970s [2]. They are currently the second largest producer of the world’s bioethanol from the sugarcane industry which holds the largest share (17%) among all renewables in the national energy mix [3-4]. Biofuels, especially those produced at large scales, have gained increasing interest specifically from the aviation industry which is challenging to decarbonize. Bioethanol from Brazilian sugarcane mills can be upgraded to sustainable aviation fuel (SAF) via the ASTM certified pathway alcohol-to-jet (ATJ) to further sustainability efforts in the aviation industry [5].

SAF is an economic and environmental opportunity for the sugarcane industry; however, challenges exist for commercial implementation. First of all, technologies to produce biojet fuels cost at least 180% more than the conventional fossil-based jet fuel [6]. Second, there is a large uncertainty regarding returns on investment as the sugar, ethanol and electricity markets have been historically volatile [3]. Additionally, with the future of SAF heavily dependent on policy implementation it is hard to predict future market conditions [6]. A framework is needed to rapidly consider SAF production integrated with Brazilian sugarcane mills under market uncertainty.

In this work using historical price data to de-risk decisions, in combination with superstructure process modeling to describe a range of technological options we develop a new optimization model to inform risk-conscious investment decisions on SAF production capacity in sugarcane mills. Specifically, we develop a MILP to model sugarcane processing with the option to invest in SAF production [3], and conversion and economic parameters for SAF production are allowed to vary to simulate different ATJ technologies [7]. Then using historical prices as scenarios, we use stochastic programming to model market uncertainty. Finally using conditional value-at-risk (CVaR) as the risk measure, we solve a multi-objective optimization model that maximizes the expected profit and minimizes risk. Furthermore, with sensitivity studies we quantify multi-objective trade-offs and conclude by discussing how optimization and analysis can guide engineering technology development.

References

[1] IEA (2022), Energy Statistics Data Browser, IEA, Paris https://www.iea.org/data-and-statistics/data-tools/energy-statistics-dat...

[2] Castro REN, Alves RMB, Nascimento CAO, Giudici R. Assessment of sugarcane based ethanol production. In: Basso TP, Basso LC, editors. Fuel ethanol production from sugarcane Rijeka: IntechOpen; 2019. https://doi.org/10.5772/intechopen. 78301. Ch. 1

[3] Mutran, V. M., Ribeiro, C. O., Nascimento, C. A. O., & Chachuat, B. (2020). Risk-conscious optimization model to support bioenergy investments in the Brazilian sugarcane industry. Applied Energy, 258. https://doi.org/10.1016/j.apenergy.2019.113978

[4] López-Ortega, M. G., Guadalajara, Y., Junqueira, T. L., Sampaio, I. L., Bonomi, A., & Sánchez, A. (2021). Sustainability analysis of bioethanol production in Mexico by a retrofitted sugarcane industry based on the Brazilian expertise. Energy, 232, 121056.

[5] Wei, H., Liu, W., Chen, X., Yang, Q., Li, J., & Chen, H. (2019). Renewable bio-jet fuel production for aviation: A review. In Fuel (Vol. 254). Elsevier Ltd. https://doi.org/10.1016/j.fuel.2019.06.007

[6] Watson, M.J., da Silva, A.V., Machado, P.G., Dowling, A.W., Ribeiro, C. O., Nascimento, C. A. O. (2023). Sustainable aviation fuel technologies, costs, emissions, policies, and markets: a critical review. Submitted to Renewable and Sustainable Energy Reviews.

[7] Restrepo-Flórez, J. M., & Maravelias, C. T. (2021). Advanced fuels from ethanol-a superstructure optimization approach. Energy and Environmental Science, 14(1), 493–506. https://doi.org/10.1039/d0ee02447c