摘要
原油蒸馏过程是一个复杂的连续工业过程，其操作优化将为企业带来可观的经济效益，解决该问题的难点主要在于过程数据协调，过程建模及优化算法。针对某炼油化工有限公司原油蒸馏过程，进行了基于物料平衡的过程数据协调计算，建立了以过程严格机理模型为约束的轻油收率优化模型，并提出应用遗传算法求解上述高维非线性工程优化问题，取得了满意的结果。
Crude distillation process optimization will bring out remarkable benefits for refineries. However, there exist lots of difficulties, such as data reconciliation, process modeling and optimization algorithm, to obtain the optimal operation parameters. In this paper, the measured data of a practical crude distillation process are reconciled and a light product yield optimization model is presented based on a rigorous process model. This problem is a typical nonlinear programming problem with constrains, which is computationally difficult because the equality constrains are implicit functions of optimization variables and it is hard to get any information of the derivatives of the optimization variables. Simulation study shows that GA is a powerful algorithm to overcome the above difficulties and an example given illustrates that how GA can be successfully applied to solve the large scale crude distillation process optimization problem.
出处
《清华大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
1998年第3期49-53,共5页
Journal of Tsinghua University(Science and Technology)
基金
国家"八六三"高技术项目资助
关键词
原油
蒸馏
过程优化
数据协调
遗传算法
crude distillation
process optimization
data reconciliation
genetic algorithm
