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Automation and Control of Energy Efficient Fluid Catalytic Cracking Processes for Maximizing Value Added Products

机译:高效节能的流体催化裂化工艺的自动化和控制,以实现增值产品的最大化

摘要

With an aim to optimize propylene production, petroleum oil is catalytically cracked by contacting the oil with catalyst mixture consisting of a base cracking catalyst containing an stable Y-type zeolite and small amounts of rare-earth metal oxide, and an additive containing a shape-selective zeolite, in an up-flow type fluid catalytic cracking apparatus having a regeneration zone, a separation zone, and a stripping zone. According to this fluid catalytic cracking process, the production of light-fraction olefins such as propylene is maximized by applying appropriate process control, monitoring, and optimizing systems. The present invention provides mathematical process models, including: neural networks, statistical models and finite impulse models. These various mathematical process models are used in conjunction with advanced controllers and optimizing routines to calculate optimal settings for various process parameters. A microwave based system can also be employed for optimizing the performance of a stripping zone, which further optimizes catalyst regeneration. Process model and historical data to test a predictive system can provide early warning of potential performance degradation and equipment failure in the FCC unit, which decreases overall operating costs and increases plant safety.
机译:为了优化丙烯的生产,使石油与催化剂混合物进行催化裂化,该催化剂混合物包括:含有稳​​定Y型沸石和少量稀土金属氧化物的基础裂解催化剂,以及含有以下形状的添加剂:在具有再生区,分离区和汽提区的上流式流化催化裂化装置中选择沸石。根据这种流化催化裂化工艺,通过应用适当的工艺控制,监控和优化系统,可以最大限度地提高轻质烯烃(如丙烯)的产量。本发明提供了数学过程模型,包括:神经网络,统计模型和有限冲激模型。这些各种数学过程模型与高级控制器和优化例程结合使用,以计算各种过程参数的最佳设置。也可以采用基于微波的系统来优化汽提区的性能,这进一步优化了催化剂的再生。用于测试预测系统的过程模型和历史数据可以为FCC单元中的潜在性能下降和设备故障提供预警,从而降低总体运营成本并提高工厂安全性。

著录项

  • 公开/公告号US2009095657A1

    专利类型

  • 公开/公告日2009-04-16

    原文格式PDF

  • 申请/专利权人 OTHMAN A. TAHA;M. RASHID KHAN;

    申请/专利号US20080266197

  • 发明设计人 OTHMAN A. TAHA;M. RASHID KHAN;

    申请日2008-11-06

  • 分类号C10G11;

  • 国家 US

  • 入库时间 2022-08-21 19:36:09

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