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Through gasification and methanol synthesis, biomass can produce methanol and then produce light olefins through the methanol-to-hydrocarbon (MTH) process. To make this new biomass based production route profitable, the efficiency of the MTH process is important. Catalyst deactivation is the main reason for the decline of conversion and selectivity. NMR was applied to detect the relaxation and diffusion of liquid molecules in a series of coked ZSM-5, investigating the effect of coke on molecular transport properties. n-Heptane was chosen as a probe molecule in describing pore network connectivity, whereas methanol was used for relaxation measurements. Though there were only minor differences of pore connectivity among the samples, the longitudinal relaxation time showed an almost linear relationship with coke contents, suggesting that the interaction between reactants and catalyst surface influences the catalyst performance within low coke contents. PFG-NMR and NMR relaxation, as fast and straightforward measurements, could simulate catalyst behaviors during the reaction process.

Deposition of carbonaceous compounds was used to improve the propylene selectivity of ZSM-5 by deactivating some acid sites meanwhile maintaining the high activity for methanol conversion. The carbonaceous species of pre-coked samples before and after MTP reactions were investigated by elementary analysis and thermogravimetric analysis (TGA). The results showed that pre-coke formed at low temperature (250°C) was unstable and easy to transform into polyaromatics species at the high reacting temperature, while combining 5% pre-coking process with 95% steam treatment at high temperature (480°C) was effective in inhibiting the formation of coke deposits and presented a significant improvement in the propylene selectivity.

This work proposes a simulation-based multiobjective optimization model for the operation of the product separation process in a methanol to propylene (MTP) plant, striving to enhance the system energy utilization efficiency. The formation of byproducts including an oxygenated hydrocarbon, dimethyl ether (DME), makes the product refining process highly energy-intensive, not only because that the various hydrocarbon byproducts require a long train of distillation columns but also owing to the fact that DME forms azeotrope with product propylene. Furthermore, the formation of oxygenated DME byproduct varies with the catalyst activity, which makes the system more complex. The contribution of this paper is 2-fold. First, it proposes a novel way of DME removal with responsive consumption of extractant methanol according to the DME concentration during one production period. In this way, the energy consumption of the condenser and reboiler of the methanol recovery unit can be expected to decrease by 61.5% and 37.6%, respectively. Second, a simulation-based multiobjective optimizaton framework is introduced to minimize the total heating and cooling costs and maximize the product purity, by integrating a rigorous process simulation model with an intelligent optimization algorithm. Given the characteristics of the MTP production process, three different operation scenarios, namely, the start of run, the designed operation condition, and the end of run, which correspond to different DME concentrations in the system, are covered. The approach is illustrated by its application to a real MTP plant, in which numerical results indicate that the proposed method is capable of identifying appealing operation options, and it can be utilized to support decision-making of the product separation of MTP plants.