In recent years China has seen speedy development of its ethylene industry. Compared to other advanced countries the per capita ethylene consumption in China is still low. With successive startup of grassroots ethylen...In recent years China has seen speedy development of its ethylene industry. Compared to other advanced countries the per capita ethylene consumption in China is still low. With successive startup of grassroots ethylene projects in China after 2006 and debottlenecking and expansion of existing ethylene units China will be confronted with the major issues related with increase of feedstocks for steam cracking. Naphtha is the main feedstock for producing ethylene, and the hydrocracked tail oil is increasing its share in the steam cracker feedstock pool over recent years. This article has analyzed the possibility for maximization of steam cracking feedstock and estimated steam cracker feedstock output based on processing 5 Mt/a of different crudes including the mixed crude transferred through Lu-Ning pipeline and Arabian light crude using corresponding process technologies at the refinery.展开更多
Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multip...Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non- linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables （MDNSGA-II） is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta- tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.展开更多
文摘In recent years China has seen speedy development of its ethylene industry. Compared to other advanced countries the per capita ethylene consumption in China is still low. With successive startup of grassroots ethylene projects in China after 2006 and debottlenecking and expansion of existing ethylene units China will be confronted with the major issues related with increase of feedstocks for steam cracking. Naphtha is the main feedstock for producing ethylene, and the hydrocracked tail oil is increasing its share in the steam cracker feedstock pool over recent years. This article has analyzed the possibility for maximization of steam cracking feedstock and estimated steam cracker feedstock output based on processing 5 Mt/a of different crudes including the mixed crude transferred through Lu-Ning pipeline and Arabian light crude using corresponding process technologies at the refinery.
基金Supported by the National Natural Science Foundation of China(21276078)"Shu Guang"project of Shanghai Municipal Education Commission,973 Program of China(2012CB720500)the Shanghai Science and Technology Program(13QH1401200)
文摘Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usually run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non- linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables （MDNSGA-II） is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta- tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.
