Optimal Design of an Integrated CyanobacteriaBased Biorefinery for Biofuels, PHAs and Bioproducts Production and Simultaneous Synthesis of Its HEN

MATIAS RAMOS; ROMINA LASRY TESTA; FERNANDO D. RAMOS; VANINA ESTRADA; M. SOLEDAD DIAZ

Phoenix

Congreso; AIChE Annual Meeting 2022; 2022

In this work we propose a mixed integer nonlinear programming(MINLP) model for the optimal design of an integratedcyanobacteria-based biorefinery for the production of bioethanol,biogas, poly(hydroxyalkanoate)s (PHAs) and bioproducts(zeaxanthin and phycocyanin), including simultaneous heatexchanger network (HEN).PHAs are a family of biodegradable polyesters synthesized bycertain microorganisms as an energy reserve. PHAs mechanicaland thermal properties together with its biodegradable abilitiesmake them promising candidates for sustainable polymerproduction (Dietrich et al., 2017). Zeaxanthin and phycocyanin areintracellular pigments that can be used in many practices,particularly used in medicine and food applications (Patel et al.,2022).The proposed production process includes different technologyalternatives, embedded within a superstructure. Four Synechocystissp. strains are considered in order to potentially producedbioethanol, PHAs and pigments. Different technologies related withphase isolation, cell harvesting and disruption are included in theseparation stage. The purification step involves concentrationequipment and purification and refinement technologies. Theproposed PHAs production process presents different technologies for the two main stages: biosynthesis and biopolymer extraction andpurification (Ramos et al., 2019). Also, an anaerobic digestion witha combined heat and power cycle is included in the model toproduced biogas and fertilizers (Garcia Prieto et al., 2017).According to the literature, some authors have proposed asuperstructure-based approach (Fasahati et al., 2019) andsimulation (Lopes et al., 2019) to assess the techno and economicfeasibility of cyanobacteria biorefineries. As novelty, we carry out asimultaneous design of the process and its HEN in a problem withmore than 50000 continuous and 10000 binary variables. To thebest of our knowledge, the model addressed in this work would bethe first simultaneous optimal design of a cyanobacteria biorefineryand its HEN.The proposed superstructure is formulated as an MINLP problemand implemented in GAMS (McCarl et al., 2017) for net presentvalue (NPV) and RePSIM maximization, a sustainability indexproposed by Martin (2016). Model equality constraints include massand energy balances, yield equations and detailed capital cost forprocess equipment, while inequality constraints include process andproduct specifications and operating bounds on process units. Also,we performed a sensitivity analysis in order to point out thetechnological aspects that could be improved to achieve a higherprofit and sustainability on the integrated biorefinery. The proposedmodel constitutes a useful tool to shortlist PHA production pathwayswith higher economic potential looking forward to the improvementof 4th generation biofuels, biomaterials and bioproducts usingcyanobacteria.