(344e) Optimal Design of an Integrated Cyanobacteria-Based Biorefinery for Biofuels, PHAs and Bioproducts Production and Simultaneous Synthesis of Its Hen

In this work we propose a mixed integer nonlinear programming (MINLP) model for the optimal design of an integrated cyanobacteria-based biorefinery for the production of bioethanol, biogas, poly(hydroxyalkanoate)s (PHAs) and bioproducts (zeaxanthin and phycocyanin), including simultaneous heat exchanger network (HEN).

PHAs are a family of biodegradable polyesters synthesized by certain microorganisms as an energy reserve. PHAs mechanical and thermal properties together with its biodegradable abilities make them promising candidates for sustainable polymer production (Dietrich et al., 2017). Zeaxanthin and phycocyanin are intracellular 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 technology alternatives, embedded within a superstructure. Four Synechocystis sp. strains are considered in order to potentially produced bioethanol, PHAs and pigments. Different technologies related with phase isolation, cell harvesting and disruption are included in the separation stage. The purification step involves concentration equipment and purification and refinement technologies. The proposed PHAs production process presents different technologies for the two main stages: biosynthesis and biopolymer extraction and purification (Ramos et al., 2019). Also, an anaerobic digestion with a combined heat and power cycle is included in the model to produced biogas and fertilizers (Garcia Prieto et al., 2017).

According to the literature, some authors have proposed a superstructure-based approach (Fasahati et al., 2019) and simulation (Lopes et al., 2019) to assess the techno and economic feasibility of cyanobacteria biorefineries. As novelty, we carry out a simultaneous design of the process and its HEN in a problem with more than 50000 continuous and 10000 binary variables. To the best of our knowledge, the model addressed in this work would be the first simultaneous optimal design of a cyanobacteria biorefinery and its HEN.

The proposed superstructure is formulated as an MINLP problem and implemented in GAMS (McCarl et al., 2017) for net present value (NPV) and RePSIM maximization, a sustainability index proposed by Martin (2016). Model equality constraints include mass and energy balances, yield equations and detailed capital cost for process equipment, while inequality constraints include process and product specifications and operating bounds on process units. Also, we performed a sensitivity analysis in order to point out the technological aspects that could be improved to achieve a higher profit and sustainability on the integrated biorefinery. The proposed model constitutes a useful tool to shortlist PHA production pathways with higher economic potential looking forward to the improvement of 4th generation biofuels, biomaterials and bioproducts using cyanobacteria.

References

Dietrich, K.; Dumont, M. J.; Del Rio, L. F.; Orsat, V. Producing PHAs in the bioeconomy - Towards a sustainable bioplastic. Sustainable Production and Consumption. 2017, 9, 58-70.

Fasahati, P.; Wu, W.; Maravelias, C. T. Process synthesis and economic analysis of cyanobacteria biorefineries: A superstructure-based approach. Applied Energy. 2019, 253, 113625.

García Prieto, C. V.; Ramos, F. D.; Estrada, V.; Villar, M. A.; Diaz, S. Optimization of an integrated algae-based biorefinery for the production of biodiesel astaxanthin and PHB. Energy. 2017, 139, 1159-1172.

Lopes, T. F.; Cabanas, C.; Silva, A.; Fonseca, D.; Santos, E.; Guerra, T. L.; Sheahan, C.; Reis; A.; Girio, F. Process simulation and techno-economic assessment for direct production of advanced bioethanol using a genetically modified Synechocystis sp. Bioresource Technology Reports. 2019, 6, 113-122.

Martin, M. RePSIM metric for design of sustainable renewable based fuel and power production processes. Energy. 2016, 144, 833-845.

McCarl, B. A., Meeraus A., van der Eijk, P., Bussieck, M., Dirkse, S., Steacy, P., Nelissen, F., 2017. McCarl GAMS User Guide, Washington, DC, USA.

Patel, A. K.; Albarico, F. P.J. B.; Perumal, P. K., Vadrale, A. P.; Nian, C. T.; Chau, H. T. B.; Anwar, C.; Wani, H. M.; Pal, A.; Saini, R.; Ha, L. H.; Senthilkumar, B.; Tsang, Y. S.; Chen, C. W.; Dong, C. D.; Singhania, R. R. Algae as an emerging source of bioactive pigments. Bioresource Technology. 2022, 351, 126910.

Ramos, F.D., Delpino, C.A., Villar, M.A., Diaz, M.S., 2019. Design and optimization of poly (hydroxyalkanoate) s production plants using alternative substrates. Bioresource Technology. 289, 121699.