(185n) Optimal Design of PHAs Plants with Alternative Substrates | AIChE

(185n) Optimal Design of PHAs Plants with Alternative Substrates

Authors 

Diaz, M. - Presenter, Planta Piloto de Ingenieria Quimica-UNS
Delpino, C., PLAPIQUI, CONICET, UNS
Villar, M., PLAPIQUI, CONICET, UNS
Ramos, F., PLAPIQUI, CONICET, UNS
In this work we proposed a mixed integer nonlinear programming (MINLP) model for the optimal design of a poly(hydroxyalkanoate)s (PHAs) biorefinery. 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). The proposed PHAs production process present different technologies embedded within a superstructure for the three main stages: raw materials pretreatment, biosynthesis and biopolymers extraction and purification.

Different potential raw materials are considered as carbon source for pretreatment stage, namely, glycerol, starch and sugarcane. Crude glycerol (glycerol 60.05 wt %, methanol 22.59 wt %, water 10.00 wt %, ashes 2.80 wt %, sodium methoxide 2.62 wt %, soaps 1.94 wt %) can be fed to the biosynthesis stage or it can be purified to improve PHA productivity (Ramos et al., 2017). If glycerol purification step is selected, methanol can be sold as a co-product after distillation. Also selling purified glycerol is set as a possible alternative (García Prieto et al., 2017). Three potential processes are considered for starch obtention. The first one includes starch production process from corn, the second option involves the acquisition of corn starch from market and the third one contemplates the possibility of using cassava starch. In this point, the superstructure considers the possibility of obtaining glucose through the liquefaction and saccharification of starch, to be used as a substrate for the microbial growth in the PHAs production step. Furthermore, a sugarcane-based process for sucrose production is included in the propose superstructure. Sugarcane bagasse, an important residue from sugar industries, can be processed for thermal and electrical energy co-generation. Sugarcane juice (mainly sucrose) can be used as a carbon source for PHAs bioproduction. As alternatives to the mentioned process, the possibility of buying processed sucrose o sugarcane molasses are included in the model. Concerning the biosynthesis, the technologies involved in this stage are highly dependent of the selected substrate. They include a sterilization step and two bioreactors, one for biomass growth and the other one for biopolymer accumulation. Finally, four extraction and purification alternatives are considered in the PHA production process: use of enzymes, solvent, surfactant and NaOCl, or surfactant and chelate.

The proposed superstructure is formulated as an MINLP problem and implemented in GAMS (Brooke et al., 2013) for net present value (NPV) maximization. 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. The resulting MINLP model for the production of 10,000 t/y of PHA has 8,249 continuous variables, 25 discrete variables, 7,456 constraints and it is solved using DICOPT (CONOPT and CPEX) (Grossmann et al., 2003) in a CPU time of 14,625 s. The optimal configuration includes the use of sugarcane as raw material for the production of PHA employing the enzymatic extraction and purification method. The value of the objective function results NPV= 75.01 MM$. The biopolymer production cost is 3.02 $/kg, which is in concordance to worldwide PHA production cost (nearly 3 $/kg) reported by Koller et al. (2012). The energy consumption for the PHA production is 22,56 MJ/kg, which results similar to other PHAs plants presented by Lopez-Arenas et al. (2017) and Akiyama et al. (2003). Also, other profitability indexes are calculated. In this sense, considering a discount rate of 10 % and a project lifetime of 15 years, the return on investment (ROI) of 22.36 %, the payback period (PP) of 3 years, and the internal rate of return (IRR) of 52.53 % indicate the economic profitability of the project. Finally, we performed a sensitivity analysis in order to point out the technological aspects that could be improved to achieve a higher profit on the biorefinery.

References

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Ramos, F. D.; Villar, M. A.; Diaz, M. S. Optimal Design of poly(3-hydroxybutyrate) production using alternative carbon sources. Computer Aided Chemical Engineering. 2017, 40, 877-882.