石油炼制与化工 ›› 2025, Vol. 56 ›› Issue (5): 134-141.

• 特约文章 • 上一篇    下一篇

催化裂化灵活-低碳-智能化生产新技术

赵云鹏1,石孝刚1,蓝兴英1,2,高金森1,徐春明1,2   

  1. 1. 中国石油大学(北京)重质油全国重点实验室
    2. 中国石油大学(北京)碳中和未来技术学院

  • 收稿日期:2024-12-25 修回日期:2025-01-22 出版日期:2025-05-12 发布日期:2025-04-14
  • 通讯作者: 赵云鹏 E-mail:ypzhao@cup.edu.cn
  • 基金资助:
    国家自然科学基金创新研究群体项目

FLEXIBLE-LOW CARBON-INTELLIGENT PRODUCTION TECHNOLOGY OF FLUID CATALYTIC CRACKING


  • Received:2024-12-25 Revised:2025-01-22 Online:2025-05-12 Published:2025-04-14

摘要: 流化催化裂化(FCC)一直是我国重质油轻质化的关键工艺之一,在成品油需求逐渐达峰的背景下,FCC成为炼油厂实现“减油增化”的重要工艺。在如今原料供给逐渐重质化和产物需求逐渐轻质化的要求下,FCC工艺的发展面临多重挑战:原料高效深度转化、绿色低碳及智能化长周期运行。围绕这些挑战,中国石油大学(北京)通过技术理论创新、工艺路线重构和人工智能(AI)+计算流体力学(CFD)智能保障持续优化升级FCC工艺。本文总结了乳化进料和汽提强化技术、FCC结焦/跑剂智能预测预警技术和再生烟气CO2原位富集技术,并在此基础上对FCC工艺的进一步发展提出展望。

关键词: 流化催化裂化, 高效深度转化, 绿色低碳, 人工智能, 计算流体力学

Abstract: Fluid catalytic cracking(FCC) remains a pivotal process for converting heavy oil into lighter products in China. It has also become essential for refineries aiming to achieve the strategic goal of “reducing gasoline production while increasing chemical product” particularly as gasoline demand approaches its peak. The development of the FCC process is currently facing multiple challenges, including the efficient and deep conversion of feedstocks, the production of green and low-carbon products, and intelligent long-term operation, driven by the heavier nature of feedstocks and the growing demand for lighter products. Focusing on these challenges, China University of Petroleum has continuously optimized and upgraded the FCC process through technological theory innovation, technology theory innovation, process reconfiguration and the implementation of artificial intelligence(AI)+computational fluid dynamics(CFD) intelligent guarantee. In this paper, emulsified feeding and steam stripping enhancement technology, FCC coking and catalyst loss intelligent prediction and warning technology, and regenerator flus gas CO2 in-situ enrichment technology are summarized, and an outlook for the further development of the FCC process is presented.

Key words: fluid catalytic cracking, high-efficiency deep conversion, green and low carbon, artifical intelligence, computational fluid dynamics