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A coke distribution model of catalyst particles in three‐dimensional space was developed based on population balance theory, and an analytic expression of coke distribution for zero‐dimensional time‐independent problem was deduced. The expression shows that the coke distribution is determined by the average catalyst residence time, coke deposition (or burning) rate, and coke distribution of catalyst inflow. The coke distribution model was further applied to the methanol to olefins (MTO) process. The critical factors influencing coke distribution in MTO process, as well as the effect of coke distribution on product selectivity, were investigated. Three scales of MTO fluidized bed reactor–regenerator systems, i.e., pilot‐scale, demonstration‐scale and commercial‐scale with the reactor diameter of 0.261, 1.25, and 10.5 m, respectively, were simulated. The simulated results were in good agreement with the operation data. The model could be helpful in the operation optimization and reactor design. © 2018 American Institute of Chemical Engineers AIChE J, 65: 1149–1161, 2019 [ABSTRACT FROM AUTHOR]

The methanol to olefins (MTO) process has received considerable interest due to its importance in transforming abundant resources such as coal, natural gas, and biomass to widely‐demanded light olefins. In the MTO process, the coke deposited on the catalyst governs the catalyst activity and product selectivity, and thus is critical to the reaction behaviour. In the industrial processes, the residence time and coke content of catalyst particles in the reactor show a certain distribution due to the continuous outflow of spent catalyst and inflow of regenerated catalyst, which need further attention. The multi‐phase particle‐in‐cell (MP‐PIC) approach was used in the current work to simulate the catalyst residence time and coke content distribution. The effect of gas‐solid flow patterns, reactor structure, and average catalyst residence time on the residence time and coke content distribution was investigated. It was found that at high superficial velocities, the coke content distributions obtained with the MP‐PIC method are consistent with the distribution deduced from the ideally mixed flow assumption of catalyst particles. The results suggested that it is possible to simulate large‐scale MTO reactors by use of the coke distribution. In particular, by incorporating an initial coke distribution, the time needed to reach steady state in the MTO reactor simulations could be greatly reduced. [ABSTRACT FROM AUTHOR]

A kinetic model for methanol to olefins (MTO) process over SAPO‐34 catalyst was established based on the dual‐cycle reaction mechanism. Simplifications were made by assuming olefins‐based cycle as virtual species S, and aromatics‐based cycle as R, where the former mainly accounts for the production of higher olefins, while the latter for lower olefins. Transformation of S to R was considered with the participation of methanol and olefins. Meanwhile, a phenomenological deactivation model was developed to account for the deactivation process. With the proposed model, the evolution of methanol conversion and product selectivity with time on stream could be predicted, and key reaction characteristics, such as the autocatalytic nature of the reaction, could also be captured due to its mechanism‐based nature. Further simulations of MTO reactors at different scales validated the robustness and applicability of the current model in MTO process development and optimization. © 2018 American Institute of Chemical Engineers AIChE J, 65: 662–674, 2019 [ABSTRACT FROM AUTHOR]

In this work, a comparative study on methanol to olefins (MTO) kinetics in fixed and fluidized bed reactors was conducted. Based on the analysis of experimental observations, a modeling approach that can be used to simulate both reactor configurations was proposed. The coke deposition was shown responsible for the difference of product selectivities for these two reactor configurations. In a fluidized bed reactor, the distribution of the coke deposition is spatially uniform, and evolves with time on stream. However, the coke deposition shows a distribution along the bed height in a fixed bed reactor, and olefins conversions were taken into consideration to account for the selectivity changes with time on stream. With the proposed model, we established a linkage between fixed bed reactors and fluidized bed reactors through coke deposition. By use of this model, it is possible to predict the performance of MTO reaction over SAPO-34 catalyst in fluidized bed reactor with experimental data obtained in fixed bed reactor, or verse vice. [ABSTRACT FROM AUTHOR]