(173c) Synergistic Process Synthesis and Design Framework for Integrated Biorefineries

A key approach in expediting the transition towards a bio-based economy is the conceptual design and implementation of integrated second-generation biorefineries (iSGB) [1]. Despite tremendous efforts in research as well as past economic and political initiatives, the number of active iSGBs worldwide is dramatically low, mainly due to their deficient economic robustness [2]. A conceptual design approach for these iSGBs is Superstructure Optimization (SSO), which yields an optimal candidate process topology (CPT), but which is inherently limited by the initial search space and the fidelity of the unit operation models [3,4]. This contrasts highly with the complexity of fermentation processes and disregards recent advances in synthetic biology for the optimization of the cell factories employed in these processes [2]. From a biotechnological perspective, this hurdle is surmounted by a design approach, in which the products are specified a priori and subsequently the cell factory and the process are tailored towards the product and finally the feedstock is specified, thus “having the end in mind” [5,6]. Furthermore, by following a simulation-based optimization (SBO) approach, complex models including physiological and operational specifications of cell factories can be employed in the search for an optimal process design. Despite being computationally demanding, the second benefit from it is the possibility to include uncertainties into the process design with models of complex biological systems [7].

In this work, we therefore propose a novel synergistic framework for the synthesis and design of iSGBs: based on a hybrid approach integrating surrogate-based superstructure optimization (SSO) with simulation-based design optimization (SBO), it harnesses both the power of the SSO for process synthesis and the potential of SBO for detailed design optimization. The framework itself capitalizes thorough knowledge regarding biotechnology and synthetic biology in order to guide decisions for both SSO and SBO, which results in a consolidated framework and an expedited evaluation process.

The first step of the proposed framework involves defining possible products for an iSGB and subsequently developing high-fidelity mechanistic models for compulsory unit operations in the iSGB. In the following step, these models are combined with other optional unit operation models under a superstructure. The complexity of the superstructure is heavily reduced by removing binary decision variables for compulsory unit operations and thus downsizing the search space. In order to solve the underlying mixed-integer nonlinear program (MINLP) of the superstructure, a surrogate-based approach, using different surrogate model types [8], is employed to identify several promising CPTs. In the next step, these candidates are subjected to detailed design optimization under uncertainty in a novel SBO framework [7], which directly uses the high-fidelity process models instead of their surrogates to optimize the process under the objective of key techno-economic metrics (KTM). The resulting optimized CPT is a base-case process design for an iSGB and can be analyzed further regarding economic or sustainability aspects.

In this study, we apply the proposed framework in a case study to the process synthesis and design of a xylitol biorefinery. Xylitol is a platform chemical sugar substitute with manifold beneficial health properties. It can be produced by microbial fermentation and the current chemical production process is relatively expensive, which makes it an ideal product for an iSGB [9]. As the hemicellulosic fraction in lignocellulosic biomass – the feedstock for any iSGB – consists mainly of xylose, it is selected as substrate for a fermentation process towards xylitol. Consequently, succinic acid, another high-potential platform chemical- is selected as value-added co-product of a fermentation process with the cellulosic fraction as substrate [10]. In order to meet the high energy demand of the iSGB, the lignin fraction is chosen as substrate for a combustion process. The chosen feedstock for the base case is wheat straw.

The compulsory unit operation models for the xylitol biorefinery are the biomass pretreatment for the fractionation and depolymerization of the hemicellulosic fraction, as well as the fermentation processes for xylitol and succinic acid. Thus, based on domain knowledge, a detailed pretreatment model for dilute acid pretreatment is developed, as it proves to be the pretreatment with the highest hemicellulose monomer yield for the given case. Subsequently, both fermentation models are built based on domain knowledge of cell factories for fermentation in biomass hydrolysate media. This includes information about the physiology and the optimization of the cell factory by synthetic biology tools. Furthermore, mechanistic models for different downstream unit operations, the enzymatic hydrolysis and a model for the combustion process of lignin are developed and validated. All models are analyzed towards robustness by a comprehensive Monte Carlo-based uncertainty and sensitivity analysis. Based on this, surrogate models are developed and validated. For the SSO a state-task network representation is selected and the surrogate models are utilized for the composition of the superstructure. Solving the resulting MINLP then yields the CPTs. In the last step they are subjected to SBO including the uncertainties in the model, input and design parameters for the unit operations. The selected KTM are the net present value and the discounted cash flow of return of the iSGB, as well as the minimum selling prices of the products. This yields the base case process design. For a further analysis and validation of the economic viability of the base case, different scenarios are simulated by Monte Carlo-based uncertainty analysis under the assumption of fluctuating market prices. Additionally a Life-Cycle Analysis is performed in order to assess the sustainability of the final version of the iSGB.

The result of this hybrid approach is then a consolidated base-case process for a xylitol biorefinery, which can be easily extended in the superstructure towards the evaluation of further products, process integration, plant-wide optimization or value chain optimization. The resulting process itself is evaluated against both criteria of being economically viable and sustainable. With these criteria fulfilled, the process itself can be implemented. Hence, the presented hybrid approach can substantially assist the conceptual process design of further iSGBs in order to facilitate their implementation throughout industry as core part of a bio-based economy.

References

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[10] Mancini, E. et al. ‘From second generation feed-stocks to innovative fermentation and downstream techniques for succinic acid production’, Critical Reviews in Environmental Science and Technology, 2019, pp.1-45.