Coal-based methanol-to-olefins (MTO) is a vital technology for establishing the “coal/natural gas-to-olefins” pathway. In this study, an industrial MTO unit of a Chinese coal chemical enterprise was modeled and optimized using plant data. For the reactor-regenerator system, a lumped kinetic model based on the SAPO-34 catalyst was validated against 4 industrial measured datasets, showing high accuracy in predicting effluent distributions and spent catalyst coke content. Multifactor optimization across another 4 measured operating cases increased the total yield of light olefins (ethylene and propylene) by up to 2.22%. Subsequently, a separation flowsheet based on measured plant data was developed in Aspen Plus using the RK-Soave and ENRTL-RK methods, resulting in low relative errors (0.12% for ethylene and 0.05% for propylene). Under the constraints of meeting product quality specifications, sensitivity analysis based on the optimized simulated yield of light olefins was conducted to optimize the side-draw rate of the ethylene column and the reflux ratio of the propylene column, corresponding to an annual energy saving of approximately 1.196 × 108 kW·h, together with an annual increase of 168 t in ethylene production. This work provides a quantitative reference for optimizing operating parameters and reducing energy consumption in industrial units. The optimized operational boundaries proposed herein are within the controllable range of the actual plant, providing operators with actionable guidelines for real-time process intensification and energy reduction.
Jia et al. (Thu,) studied this question.