(300f) Advances in Modeling, Synthesis, and Global Optimization of Hybrid Energy Systems

Significant challenges against a sustainable energy future include energy availability, economics, and the generation of lower carbon energy [1]. To address these challenges, multi-scale modeling and optimization approaches are necessary toward the production of transportation fuels and petrochemicals from alternative feedstocks (e.g., coal, biomass, natural gas, and municipal solid waste - MSW) [1].

At the reactor design level, the effect of key variables are captured through first principles or data analysis while keeping model complexity compatible with large-scale process optimization [2,3]. A first-principles based dynamic optimization framework for the steam cracking of hydrocarbons is highlighted, followed by novel data-driven approaches for microchannel steam reforming and MSW gasification where fundamental models describing these phenomena are too complex. These resulting models are incorporated within a process synthesis superstructure designed to compare novel and competing refinery alternatives for the production of liquid fuels and chemicals from carbonaceous feedstocks [4-7].

A comprehensive process synthesis superstructure is developed to convert alternative feedstocks (e.g., coal, biomass, natural gas, MSW) into liquid transportation fuels, olefins, and aromatics. This superstructure enables the simultaneous evaluation of many competing process alternatives (>1E9) within a single large-scale (>20K variables and constraints) nonconvex mixed-integer nonlinear model (MINLP). A tailored branch-and-bound global optimization algorithm is developed to determine the optimal refinery topology at the highest profit or lowest cost [4-7]. Several case studies are illustrated to demonstrate the capability of the global optimization algorithm and to quantify the economic viability of the optimal topologies. The process synthesis approach is further extended to handle uncertainties and synthesize nationwide energy supply chains.

References:

[1]: Floudas, C. A.; Niziolek, A. M.; Onel, O.; Matthews, L. R. Multi-scale systems engineering for energy and the environment: Challenges and opportunities. AIChE Journal 2016, 62 (3), 602-623.

[2]: Onel, O.; Niziolek, A. M.; Hasan, M.; Floudas, C. A. Municipal solid waste to liquid transportation fuels–Part I: Mathematical modeling of a municipal solid waste gasifier. Computers & Chemical Engineering 2014, 71, 636-647.

[3]: Onel, O.; Niziolek, A. M.; Butcher, H.; Wilhite, B. A.; Floudas, C. A. Multi-scale approaches for gas-to-liquids process intensification: CFD modeling, process synthesis, and global optimization. Computers & Chemical Engineering, 2017, DOI: 10.1016/j.compchemeng.2017.01.016

[4]: Onel, O.; Niziolek, A. M.; Elia, J. A.; Baliban, R. C.; Floudas, C. A. Biomass and natural gas to liquid transportation fuels and olefins (BGTL+C2_C4): Process Synthesis and Global Optimization. Industrial & Engineering Chemistry Research 2014, 54, 359-385.

[5]: Niziolek, A. M.; Onel, O.; Elia, J. A.; Baliban R. C.; Floudas, C. A. Coproduction of Liquid Transportation Fuels and C6_C8 Aromatics from Biomass and Natural Gas. AIChE Journal 2015, 61, 831-856.

[6]: Onel, O.; Niziolek, A. M; Floudas, C. A Optimal Production of Light Olefins from Natural Gas via the Methanol Intermediate. Industrial & Engineering Chemistry Research 2016, 55 (11), 3043-3063.

[7] Niziolek, A. M.; Onel, O.; Floudas, C. A. Production of Benzene, Toluene, and Xylenes from Natural Gas via Methanol: Process Synthesis and Global Optimization. AIChE Journal 2016, 62 (5), 1531 – 1556.