Abstract: An ethylene plant employs multiple cracking furnaces in parallel to convert various hydrocarbon feedstocks to smaller hydrocarbon molecules.The continuous operational performance of cracking furnaces gradually decays because of coke formation in the reaction coils,which requires each furnace to be periodically shut down for decoking.Given multiple feeds and different cracking furnaces as well as various product prices and manufacturing costs,the operational scheduling for the entire furnace system should be optimized to achieve the best economic performance.In this paper,a new MINLP (mixed-integer nonlinear programming) model is developed to obtain cyclic scheduling strategies for cracking furnace systems.Compared to previous studies,the new model has more capabilities to address operation profitability of multiple feeds cracked in multiple furnaces.Meanwhile,solving the problem of the choice for the right time of changing feedstock in the process of cracking furnace,case studies demonstrate the efficacy of the developed methodology.

Key words: changing feedstock, coking, control, mixed-integer nonlinear programming, optimization

摘要： 乙烯裂解炉炉群通常由多台裂解炉并行运行，将烃类原料裂解成小分子烃类化合物。由于随着裂解炉连续运行不可避免地在炉管内壁产生结焦，结焦导致裂解炉运行效率下降，所以需要对裂解炉进行周期性的停炉清焦。对于不同价格参数的多种原料不同清焦费用的多台裂解炉来说，整个乙烯裂解炉炉群系统的循环调度应是求得最优解使得收益最大化。本文对此类裂解炉炉群循环调度问题提出了一个新的混合整数非线性（MINLP）模型，相比较以前的研究该模型能够得到更好的求解多原料多裂解炉的问题，同时解决了裂解过程中切料时机选择的问题。最后，以某乙烯厂为研究实例进行切料时机的优化，优化后裂解炉全周期的运行效益显著提高，为操作人员选择最佳切炉时机提供了理论依据，说明了此模型的有效性。

关键词: 切料, 焦化, 控制, 混合整数非线性规划, 优化