(459a) Simultaneous Product and Process Design for Tailor-Made Biofuels

König, A., RWTH Aachen University
Mitsos, A., RWTH Aachen University
Viell, J., RWTH Aachen
Neidhardt, L., RWTH Aachen University
Dahmen, M., FZ Jülich
By consuming roughly half of global oil produced [1], road transport contributes significantly to climate change. Internal combustion engines (ICEs) are currently the main propulsion system in road transport and are expected to stay important at least until 2050 [2]. Renewable fuels that are tailored for high-efficiency and low-emissions combustion pose a promising option for future ICEs. These fuels, which typically consist of multiple components, must be produced by economic and sustainable processes. In case the fuel components can be derived from the same feedstock in a single process, integrated design of process and product is needed to find the overall optimal process-product combination [3].

While many methods for process design and product design exist, few have dealt with simultaneous process and product design. Marvin et al. [4] propose a method for simultaneous fuel and reaction pathway design that is based on automatically constructed reaction networks. Following a similar approach, Dahmen and Marquardt [5] design tailor-made biofuels and their optimal production pathways using relatively detailed fuel property models that take into account non-ideal thermodynamics. The pathway models used by Marvin et al. [4] and Dahmen and Marquardt [5], however, neglect separations and their energy demands, thus hindering direct optimization of two key process performance measures, i.e., fuel production cost and global warming impact (GWI). By contrast, the optimization-based pathway screening method Process Network Flux Analysis (PNFA) proposed by Ulonska et al. [6] also evaluates downstream processing alternatives and their minimum energy demand based on reduced-order separation models [7]. PNFA requires a priori specification of a target product and therefore does not facilitate integrated product and process design; however, its more detailed mass- and energy-based pathway evaluation allows optimizing for fuel production cost and GWI.

We present a new method for integrated fuel and production process design that combines two of our aforementioned approaches, i.e., [5] and [6]. The new method is capable of performing simultaneous fuel and production process design with cost and GWI as objectives. To enhance computational tractability of the optimization problem, the new approach contains several model simplifications, e.g., an algebraic fuel distillation curve model based on the concept of the true boiling point curve [8]. These simplifications allow solving the resulting mixed-integer nonlinear program (MINLP) with the global deterministic solver BARON [9]. We demonstrate the new method with a case study on future tailor-made spark-ignition engine fuels consisting of up to seven potential bio-derived components. An analysis of the tradeoff between fuel production cost and GWI reveals how the composition and the process configurations of the rationally formulated fuels change along the Pareto-optimal curve from the minimal cost design to the minimal GWI design.


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