改进粒子群算法及在油品调合问题中的应用
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摘要
汽油调合是利用炼厂各装置生产的多种汽油组分,按照适当的比例配方混合均匀后生产出符合各种成品汽油标准的调合汽油,是一个典型的非线性约束优化(NLP)问题。汽油调合是炼油厂生产汽油成品油的一个重要的生产环节,它影响到高牌号汽油成品油的生产和成品汽油调合的一次合格率,直接关系到炼厂的经济效益。作为成品油生产的重要环节,油品调和包含多种组分油的使用和多种产品的生产,涉及多个储油罐,不同的订单需求,严格的质量测试,以及复杂的物理和化学变化。建立完善的油品调和短期调度数学规划模型成为炼油工业调度问题的首要任务,而其中的难点同时也是最关键的环节便是如何获得满意的调合配方。
本文首先综合分析了国内外关于油品调合问题的研究情况及炼油厂的应用现状,分类比较了现有的调和方法和调和技术,针对现有油品调和配比优化模型不够准确和求解速度较慢的问题建立了新的汽油调和配比模型;并提出一种新的分化微粒群算法,在算法进化过程中引入变异因子,较大程度的降低了整个算法在进化过程中陷入局部极值的可能性,并保持了种群多样性,提高了算法在整个解空间内搜索全局最优解的能力。并针对油品调和配方优化问题进行应用,仿真结果表明算法能获得比较理想的调和配方,在满足调和利润最大的同时保证对调和指标的卡边,使调和成品由指标富余量大大降低。通过仿真将本文方法与现有方法进行比较,验证了该方法的有效性和广泛的适应性,为提高炼油厂经济效益创造了条件。
最后设计出了一个采用PID控制算法控制配方优化及执行的在线管道油品调和方案,可以实现调和配比的在线调整,为采用本文方法实现油品在线调和提供了综合解决方案。
Oil blending is an typical nor linear optimization problem.As the most important process of producing refined oil, This step refers to a serial of factors including components, products, oil storage tanks, different order demands and rigid quality test, relates to a large number of complicated physics and chemical reactions. It is complicated to analyze, optimize and simulate such a large system, especially mathematical model is the emphasis. Therefore, mathematical model become an important research direction in refinery scheduling. And resolving blending receipt is key and difficult.
This paper first integrally analyze study status about oil blending problems in and abroad and the application status of refinery, compare apart the existing blending methods and blending technology, and build a new oil blending proportion model for the problems about imprecision and speed slowness of the existing oil blending well-proportioned model. Proposing improved Particle Swarm Optimization arithmetic and introducing variation gene in the arithmetic evolution, greatly reduce the probability of convergence for the whole arithmetic, keep the swarm diversity, and improve the arithmetic ability of searching the best solution in the entire space. Applying for the oil blending optimization problem, the simulation result indicates that arithmetic can obtain a better oil blending recipe, and guarantee NLP for the blending constrains while contenting the maximal blending profit, and greatly reduce the constraining margin of refined blending oil. Comparing the method the existing methods, the result of simulations verifys that the method in this paper is effective and adaptive widely, it also creates conditions for improving economic benefit of refinery.
Finally, this thesis researches the online pipeline oil blending method by applying PID control methods to realize the recipe online optimization and excution. and points out future study direction.
本文首先综合分析了国内外关于油品调合问题的研究情况及炼油厂的应用现状,分类比较了现有的调和方法和调和技术,针对现有油品调和配比优化模型不够准确和求解速度较慢的问题建立了新的汽油调和配比模型;并提出一种新的分化微粒群算法,在算法进化过程中引入变异因子,较大程度的降低了整个算法在进化过程中陷入局部极值的可能性,并保持了种群多样性,提高了算法在整个解空间内搜索全局最优解的能力。并针对油品调和配方优化问题进行应用,仿真结果表明算法能获得比较理想的调和配方,在满足调和利润最大的同时保证对调和指标的卡边,使调和成品由指标富余量大大降低。通过仿真将本文方法与现有方法进行比较,验证了该方法的有效性和广泛的适应性,为提高炼油厂经济效益创造了条件。
最后设计出了一个采用PID控制算法控制配方优化及执行的在线管道油品调和方案,可以实现调和配比的在线调整,为采用本文方法实现油品在线调和提供了综合解决方案。
Oil blending is an typical nor linear optimization problem.As the most important process of producing refined oil, This step refers to a serial of factors including components, products, oil storage tanks, different order demands and rigid quality test, relates to a large number of complicated physics and chemical reactions. It is complicated to analyze, optimize and simulate such a large system, especially mathematical model is the emphasis. Therefore, mathematical model become an important research direction in refinery scheduling. And resolving blending receipt is key and difficult.
This paper first integrally analyze study status about oil blending problems in and abroad and the application status of refinery, compare apart the existing blending methods and blending technology, and build a new oil blending proportion model for the problems about imprecision and speed slowness of the existing oil blending well-proportioned model. Proposing improved Particle Swarm Optimization arithmetic and introducing variation gene in the arithmetic evolution, greatly reduce the probability of convergence for the whole arithmetic, keep the swarm diversity, and improve the arithmetic ability of searching the best solution in the entire space. Applying for the oil blending optimization problem, the simulation result indicates that arithmetic can obtain a better oil blending recipe, and guarantee NLP for the blending constrains while contenting the maximal blending profit, and greatly reduce the constraining margin of refined blending oil. Comparing the method the existing methods, the result of simulations verifys that the method in this paper is effective and adaptive widely, it also creates conditions for improving economic benefit of refinery.
Finally, this thesis researches the online pipeline oil blending method by applying PID control methods to realize the recipe online optimization and excution. and points out future study direction.
引文
[1]褚健,荣冈.流程工业综合自动化技术.北京:机械工业出版社,2004.
[2]Rigby B,Lasdon L S,and Waren A D.The evolution of Texaco blending systems-form Omega to StarBlend.Interfaces,1995,25(5):64
[3]Glismann K,Gruhn G.Short-term scheduling and recipe optimization of blending processes.Computers and Chemical Engineering,2001,25(6):627
[4]Jia Z,Iearapetritou M.Mixed-interger linear programming for gasoline bleing and distribution scheduling.Ind.Eng.Chem.Res.,2003,42(8):110-114
[5]Kennedy J.,Eberhart R.C.,Particle Swarm Optimization.Proceedings of the Sixth International Symposium on Micro Machine and Human Science,Nagoya,Japan,1995:39-43
[6]宋洁蔚.油品生产与储运调度问题研究.浙江大学博士学位论文,2003,5(3):64.
[7]侯祥麟.中国炼油技术.北京:中国石化出版社,1991.
[8]王基铭.21世纪我国炼油工业面临的挑战和对策.石油炼制与化工1999,30(5):1.
[9]彭朴,陆婉珍.汽油辛烷值和组成的关系.石油炼制,1981,2(6):27.
[10]唐立新,常佳忠,杨自厚.CIMS下多品种小批量主生产计划的可视化系统.系统工程理论与实践,1999,19(1):120-124.
[11]Chang B B,Zhang Q L,Xie Let al.The application of NIR in oii blending.Chinese Journal of Scientific Instrument,2001,22(3)(suppl):408-410.
[12]李歧强.生产过程的智能决策与调度.杭州:浙江大学博士学位论文,1998.
[13]张宁.石永杰,孙根旺.生产调度管理系统在企业生产管理中的应用.石油化工自动化,2003,5(6):44-45.
[14]刘振东,徐亚平.化工企业生产调度.北京:中国标准出版社,1992.
[15]徐用愚.流程工业的CIM5.化工自动化及仪表,1997,24(3):58-6.
[16]Nelson W L.Predict research octane number for gasoline blends.Oii & Gas J.,1955,54(20):135-138.
[17]Scott E J Y et al.A method of calculating the motoroctane of gasoline blends.Proc Am Petrol Inst,1958,38(3):90-92.
[18]Brown J E et al.Estimate octane number by concentration.Proc Am Petrol Inst,1962,42(3):515-519.
[19]Healy W C et al.A new approach to blending octane.Proc Am Petrol Inst,1959,39(3):132-136.
[20]彭朴,陆婉珍.汽油辛烷值和组成的关系.石油炼制,1981,2(6):27.
[21]A Brambilla et al.Estimate product quality with ANNs.Hydrocarbon processing,1996,15(2):78-89.
[22]Y Serpemen et al.Diesel blending system cuts quality give-aways at Ruhr refinery. Oil & Gas Journal,1991,23(7):102-110.
[23]A Espinosa et al.On-line NIT analysis and advanced control improve gasoline blending.Oil & Gas Journal,1994,18(3):85-92.
[24]Nelson,W.L.,Predict research octane number for gasoline blends,Oil&Gas J.,1995,54(20):135-138
[25]Schoen,W.F.,Calculating gasoline blend octane ratings,Ind And Engr Chem,1955,47(9):1740-1742
[26]Stewart,W.E.,Predict octanes for gasolineblends,Petroleum Refiner,1959,38(12):132-139
[27]Healy,Jr.W.C.,C.W.Maassen and R.T.Peterson,A new approach to blending octanes,Proc.Am Petrol Inst,1959,39(3):132-136
[28]Auckland,M.H.T.and D.J.Charnock,.The developmentof linear blending indics for petroleum properties,J.of the Inst of petroleum,1969,55(545),322-329
[29]morris,W.E.,The interaction approach to gasoine blending,NPRA paper,AM-75-30
[30]Rusin,M.H.,H.S.Chung and J.F.Marshall,A transformation method for calculating the research motor octane numbers of gasoline blends,I nd.Eng.Chem.,Fundam,1981,20(3):195-204
[31]Muller,A.,New method produces accurate octane blending values,Oil & Gas J.,1992,3(3):80-90
[32]Zahed,A.H.,S.A.Mullah and M.D.Bashir,Predict octane number for gasoline blends,Hydrocarbon Processing,1993,72(5):85-87
[33]Twu,C.H.and J.E.Coon,Predict octane numbers using a generalized interaction method,Hydrocarbon Processing,1996,75(2):51-56
[34]Twu,C.H.and J.E.Coon,Estimate octane numbers using an enhanced method,Hydrocarbon Processing,1997,76(3):65-68
[35]陈志新,调合汽油研究法辛烷值模型的建立,石油炼制与化工,1997,28(1):52-55
[36]钱伯章,当代石油化工自动化技术发展要点(续),化工自动化及仪表,1997,24(1):3-9
[37]袁洪福,褚小立,陆婉珍,发展适合我国炼油厂的汽油自动调合成套工艺技术,炼油技术与程,2004,34(7):1-5
[38]Vermeer,P.J.,C.C.Pedersen and W.M.Canney,Blend-control system all but eliminates reblends for Canadian refiner,Oil & Gas.,1997,7(1):74-79
[39]饶兴鹤,瑞典炼油厂安装先进调和控制系统提高油品调合操作水平,炼油技术与工程,200333:4-4
[40]杨名滨,测定汽油规格的良种智能在线分析仪,化工自动化及仪表,2000,20(4):49-53
[41]孙根旺,赵小强,王亚玲,汽油在线优化调合控制模型及应用,石油炼制与化工,1999,3(11):33-36
[42]蒋凡,何盛宝,刘东嵩,汽油在线调合及移动自动系统的应用,石油化工自动化,2004,6(6)39-41
[43]往秋灵,宋涛,冀长泰,汽油在线优化调合系统的工业应用,江苏化工,2004,32(6):56-58
[44]A.Singh,J.F.Forbes,P.J.Vermeer,S.S.Woo.Model-based real-time optimization of automotive gasoline blending operations.Journal of Process Control,2000,10:43-58
[45]Litvinenko V.I,Burgher J.A.,Vyshemirskij V.S.,Sokolova N.A.,Application of ge neticalgorithm for optimization gasoline fractions blending compounding.Proceedings o f the IEEEinternational Conference on Aritificial Intelligences Syetems(ICAIS'02).Div nomorskoe,Russia,2002:391-394
[46]Zhao Xiaoqiang,Rong Gang.Blending scheduling based on particle swarm optimizatio nalgorithm.Proceedings of the 2004 IEEE International Conferehce on Information Reuse and Integration,Las Vegas,USA,2004:618-622
[47]Mense R and Kennedy J.The Full Informed Particle Awarm:Simpler,Maybe Better.IEE:Transaction on Evolutionary Computation.2004,8(3):204-210
[48]J D Schaffer.Multiple objective optimization with vector evaluated genetic algori thms[A].Proceedings of the first conference on genetic algorithms[C].Princeton,NJ:Law rence Erlbaum,1985:93-100
[49]王继东,王万良.基于遗传算法的汽油调和生产优化研究.化工自动化及仪表,2005,32(1):6-9.
[2]Rigby B,Lasdon L S,and Waren A D.The evolution of Texaco blending systems-form Omega to StarBlend.Interfaces,1995,25(5):64
[3]Glismann K,Gruhn G.Short-term scheduling and recipe optimization of blending processes.Computers and Chemical Engineering,2001,25(6):627
[4]Jia Z,Iearapetritou M.Mixed-interger linear programming for gasoline bleing and distribution scheduling.Ind.Eng.Chem.Res.,2003,42(8):110-114
[5]Kennedy J.,Eberhart R.C.,Particle Swarm Optimization.Proceedings of the Sixth International Symposium on Micro Machine and Human Science,Nagoya,Japan,1995:39-43
[6]宋洁蔚.油品生产与储运调度问题研究.浙江大学博士学位论文,2003,5(3):64.
[7]侯祥麟.中国炼油技术.北京:中国石化出版社,1991.
[8]王基铭.21世纪我国炼油工业面临的挑战和对策.石油炼制与化工1999,30(5):1.
[9]彭朴,陆婉珍.汽油辛烷值和组成的关系.石油炼制,1981,2(6):27.
[10]唐立新,常佳忠,杨自厚.CIMS下多品种小批量主生产计划的可视化系统.系统工程理论与实践,1999,19(1):120-124.
[11]Chang B B,Zhang Q L,Xie Let al.The application of NIR in oii blending.Chinese Journal of Scientific Instrument,2001,22(3)(suppl):408-410.
[12]李歧强.生产过程的智能决策与调度.杭州:浙江大学博士学位论文,1998.
[13]张宁.石永杰,孙根旺.生产调度管理系统在企业生产管理中的应用.石油化工自动化,2003,5(6):44-45.
[14]刘振东,徐亚平.化工企业生产调度.北京:中国标准出版社,1992.
[15]徐用愚.流程工业的CIM5.化工自动化及仪表,1997,24(3):58-6.
[16]Nelson W L.Predict research octane number for gasoline blends.Oii & Gas J.,1955,54(20):135-138.
[17]Scott E J Y et al.A method of calculating the motoroctane of gasoline blends.Proc Am Petrol Inst,1958,38(3):90-92.
[18]Brown J E et al.Estimate octane number by concentration.Proc Am Petrol Inst,1962,42(3):515-519.
[19]Healy W C et al.A new approach to blending octane.Proc Am Petrol Inst,1959,39(3):132-136.
[20]彭朴,陆婉珍.汽油辛烷值和组成的关系.石油炼制,1981,2(6):27.
[21]A Brambilla et al.Estimate product quality with ANNs.Hydrocarbon processing,1996,15(2):78-89.
[22]Y Serpemen et al.Diesel blending system cuts quality give-aways at Ruhr refinery. Oil & Gas Journal,1991,23(7):102-110.
[23]A Espinosa et al.On-line NIT analysis and advanced control improve gasoline blending.Oil & Gas Journal,1994,18(3):85-92.
[24]Nelson,W.L.,Predict research octane number for gasoline blends,Oil&Gas J.,1995,54(20):135-138
[25]Schoen,W.F.,Calculating gasoline blend octane ratings,Ind And Engr Chem,1955,47(9):1740-1742
[26]Stewart,W.E.,Predict octanes for gasolineblends,Petroleum Refiner,1959,38(12):132-139
[27]Healy,Jr.W.C.,C.W.Maassen and R.T.Peterson,A new approach to blending octanes,Proc.Am Petrol Inst,1959,39(3):132-136
[28]Auckland,M.H.T.and D.J.Charnock,.The developmentof linear blending indics for petroleum properties,J.of the Inst of petroleum,1969,55(545),322-329
[29]morris,W.E.,The interaction approach to gasoine blending,NPRA paper,AM-75-30
[30]Rusin,M.H.,H.S.Chung and J.F.Marshall,A transformation method for calculating the research motor octane numbers of gasoline blends,I nd.Eng.Chem.,Fundam,1981,20(3):195-204
[31]Muller,A.,New method produces accurate octane blending values,Oil & Gas J.,1992,3(3):80-90
[32]Zahed,A.H.,S.A.Mullah and M.D.Bashir,Predict octane number for gasoline blends,Hydrocarbon Processing,1993,72(5):85-87
[33]Twu,C.H.and J.E.Coon,Predict octane numbers using a generalized interaction method,Hydrocarbon Processing,1996,75(2):51-56
[34]Twu,C.H.and J.E.Coon,Estimate octane numbers using an enhanced method,Hydrocarbon Processing,1997,76(3):65-68
[35]陈志新,调合汽油研究法辛烷值模型的建立,石油炼制与化工,1997,28(1):52-55
[36]钱伯章,当代石油化工自动化技术发展要点(续),化工自动化及仪表,1997,24(1):3-9
[37]袁洪福,褚小立,陆婉珍,发展适合我国炼油厂的汽油自动调合成套工艺技术,炼油技术与程,2004,34(7):1-5
[38]Vermeer,P.J.,C.C.Pedersen and W.M.Canney,Blend-control system all but eliminates reblends for Canadian refiner,Oil & Gas.,1997,7(1):74-79
[39]饶兴鹤,瑞典炼油厂安装先进调和控制系统提高油品调合操作水平,炼油技术与工程,200333:4-4
[40]杨名滨,测定汽油规格的良种智能在线分析仪,化工自动化及仪表,2000,20(4):49-53
[41]孙根旺,赵小强,王亚玲,汽油在线优化调合控制模型及应用,石油炼制与化工,1999,3(11):33-36
[42]蒋凡,何盛宝,刘东嵩,汽油在线调合及移动自动系统的应用,石油化工自动化,2004,6(6)39-41
[43]往秋灵,宋涛,冀长泰,汽油在线优化调合系统的工业应用,江苏化工,2004,32(6):56-58
[44]A.Singh,J.F.Forbes,P.J.Vermeer,S.S.Woo.Model-based real-time optimization of automotive gasoline blending operations.Journal of Process Control,2000,10:43-58
[45]Litvinenko V.I,Burgher J.A.,Vyshemirskij V.S.,Sokolova N.A.,Application of ge neticalgorithm for optimization gasoline fractions blending compounding.Proceedings o f the IEEEinternational Conference on Aritificial Intelligences Syetems(ICAIS'02).Div nomorskoe,Russia,2002:391-394
[46]Zhao Xiaoqiang,Rong Gang.Blending scheduling based on particle swarm optimizatio nalgorithm.Proceedings of the 2004 IEEE International Conferehce on Information Reuse and Integration,Las Vegas,USA,2004:618-622
[47]Mense R and Kennedy J.The Full Informed Particle Awarm:Simpler,Maybe Better.IEE:Transaction on Evolutionary Computation.2004,8(3):204-210
[48]J D Schaffer.Multiple objective optimization with vector evaluated genetic algori thms[A].Proceedings of the first conference on genetic algorithms[C].Princeton,NJ:Law rence Erlbaum,1985:93-100
[49]王继东,王万良.基于遗传算法的汽油调和生产优化研究.化工自动化及仪表,2005,32(1):6-9.