Strategy of changing cracking furnace feedstock based on improved group search optimization

The scheduling process of cracking furnace feedstock is important in an ethylene plant. In this paper it is described as a constraint optimization problem. The constraints consist of the cycle of operation, maximum tube metal temperature, process time of each feedstock, and flow rate. A modified group search optimizer is proposed to deal with the optimization problem. Double fitness values are defined for every group. First, the factor of penalty function should be changed adaptively by the ratio of feasible and general solutions. Second, the “excellent” infeasible solution should be retained to guide the search. Some benchmark functions are used to evaluate the new algorithm. Finally, the proposed algorithm is used to optimize the scheduling process of cracking furnace feedstock. And the optimizing result is obtained.

Two kinds of feedstock are cracked in one cycle operation. Four products are considered, namely, ethylene, propylene, butadiene, and benzene. Their prices are known. The price of feedstock and operational costs are known. This scheduling model involves nonlinear object function and violation function. The improved GSO is used to solve the problem based on the previous model. Then, the best feedstock switchover can be achieved. For the feedstock NAP and HVGO, the feedstock is changed only once. The identified optimal solution can be achieved. NAP is cracked for 45 days and NVGO for 28 days. The yields of ethylene, propylene, and butadiene are considerably increased. Contrarily, the benzene yield is reduced.Figure optionsDownload as PowerPoint slide