380562 Dynamic Load Optimization for Ethylene Cracking Furnace System

Tuesday, November 18, 2014: 4:05 PM
Crystal Ballroom B/E (Hilton Atlanta)
Wang Zhenlei, East China University of Science and Technology, Shanghai, China, Li Jinlong, East China University of Science and Technolgy, Shanghai, China and Xu Qiang, Dan F. Smith Department of Chemical Engineering, Lamar University, Beaumont, TX

Cracking furnace is the key equipment of an ethylene plant as it primarily determines the plant productivity. Because the furnace operation is semi-continuous, which involves periodical decoking operations, multiple furnaces have to be simultaneously employed to keep the plant production continuously. It should be noted that in reality the performance of each furnace is different when cracking different feedstock under different operating conditions. Thus, it is a very challenging task to optimize processing loads for each furnace under conditions that plant production recipe is changing or some furnace is experiencing the decoking operation.

In this paper, a general methodology framework for dynamic load optimization of ethylene cracking furnace systems has been developed to maximize the plant profitability. The methodology includes three stages of work.  Firstly, predictive yield models for major cracking products such as C2H4, C3H6, H2, C4H6 and C6H6 are developed based on a radical reaction mechanism. Secondly, the simplified heat transfer model and coking model are developed based on operating data and further validated according to the CO concentration in the furnace tail gas. These data-driven based models are used to predict the run length of each furnace batch operation. Finally, based on all the simulation models obtained from the above, an optimization model is developed and optimally solved to smartly allocate feedstock to different furnaces under various operating conditions, so as to maximize the total profitability of the ethylene plant furnace system. The modeling performance and different solving strategies will be extensively discussed in this study.


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See more of this Session: Process Innovation and Optimization for Agile Manufacturing
See more of this Group/Topical: Process Development Division