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汽油调合调度优化
引用本文:张冰剑,华贲,陈清林.汽油调合调度优化[J].化工学报,2007,58(1):168-175.
作者姓名:张冰剑  华贲  陈清林
作者单位:华南理工大学强化传热与过程节能教育部重点实验室
基金项目:国家重点基础研究发展计划(973计划)
摘    要:采用连续时间建模方法,建立了一种新的汽油非线性调合和调度集成优化的混合整数非线性规划(MINLP)模型,克服了当前在油品调合调度中采用线性调合模型或者将非线性调合过程和调度分开优化的缺陷。针对建立MINLP模型的特点,将原MINLP问题转化为求解一系列的混合整数线性规划(MILP)模型,避免了直接求解MINLP模型的复杂性。最后以某大型炼油企业为例,验证了模型和算法的实用性。

关 键 词:调合  调度  混合整数非线性规划  连续时间  优化
文章编号:0438-1157(2007)00-0168-08
收稿时间:2005-10-29
修稿时间:2005-10-292006-02-15

Optimization of gasoline blending and scheduling in refinery complexes
ZHANG Bingjian,HUA Ben,CHEN Qinglin.Optimization of gasoline blending and scheduling in refinery complexes[J].Journal of Chemical Industry and Engineering(China),2007,58(1):168-175.
Authors:ZHANG Bingjian  HUA Ben  CHEN Qinglin
Affiliation:Key Laboratory of Enhanced Heat Transfer and Energy Conservation, Ministry of Education, South China University of Technology, Guangzhou 510640, Guangdong , China
Abstract:Gasoline blending and scheduling is the last and important operation in a refinery.It is also the last chance to improve the quality of products and to reduce the production costs.Firstly,a novel mixed integer nonlinear programming(MINLP) formulation based on continuous time representation,is presented in this paper.Gasoline blending and short-term scheduling are integrated in the proposed model to optimize blending and scheduling simultaneously,and a nonlinear blending model is employed to reduce the quality excess of gasoline products.Empirical knowledge and some effective sets are added to the model to reduce the model scale and to improve the solve performance.A novel algorithm for the presented model is proposed.A series of mixed integer linear programming(MILP) model is solved instead of solving the original MINLP problem directly.Finally,a real industrial example,provided by a refinery complex,is used to demonstrate the performance of the presented model and algorithm.The model can get the optimal results in a reasonable time,which is more profitable than the conventional or other methods.
Keywords:blending  scheduling  MINLP  continuous time  optimization
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