Jiang Hongbo, Yuan Linzhi, Li Defei, Chen Yushi
Research Institute of Petroleum Processing, East China University of Science and Technology, Shanghai 200237, China.
Petro-CyberWorks Information Technology Co., Ltd., Shanghai 200050, China.
ACS Omega. 2023 Mar 3;8(10):9630-9643. doi: 10.1021/acsomega.3c00304. eCollection 2023 Mar 14.
The methanol-to-olefins (MTO) technology creates a new non-oil route to produce light olefins. This paper reports a 14-lump MTO kinetic model for SAPO-34 catalyst, combined with the hydrodynamic model for the fast fluidized bed reactor of the industrial SMTO process. Selective deactivation is considered to quantify the product selectivity and abrupt catalytic activity change. Moreover, referring to the parallel compartment (PC) model, the activity difference between the circulating spent catalyst and the regenerated catalyst is considered. The validation results with the optimized kinetic parameters showed good agreement between the calculated value and the actual value. Sensitivity analysis of the industrial SMTO process was performed. According to the results, the established mathematical model can provide guidance for industrial production operations.
甲醇制烯烃(MTO)技术开创了一条生产轻质烯烃的新型非石油路线。本文报道了一种用于SAPO - 34催化剂的14集总MTO动力学模型,并结合了工业SMTO工艺快速流化床反应器的流体动力学模型。考虑了选择性失活以量化产物选择性和催化活性的突然变化。此外,参照平行反应区(PC)模型,考虑了循环废催化剂和再生催化剂之间的活性差异。优化动力学参数后的验证结果表明计算值与实际值吻合良好。对工业SMTO工艺进行了敏感性分析。结果表明,所建立的数学模型可为工业生产操作提供指导。