【作者】 贾涛；

【导师】 夏涛；

【作者基本信息】 北京化工大学 ， 控制理论与控制工程， 2008， 硕士

【摘要】 在石油化工生产中,一些物流需要加热,另一些物流需要冷却,换热网络把这些物流匹配在一起,利用热物流加热冷物流,提高系统的热回收,减少公用工程加热与冷却的负荷,从而达到节能的目的。换热网络需要具有最小投资费用和运行费用,并满足在各种约束条件下,把每一物流由初始温度加热或冷却到目标温度。换热网络的设计是一个优化问题,是石油化工生产节能技术研究的重要方面。换热网络的设计一是朝着智能化方向发展,一是需要借鉴更多的经验知识。本文把粒子群优化算法加以改进,结合经验设计规则,运用到换热网络的设计中,目的在于提高换热网络设计过程的智能化、快速性和设计结果的优良性,提高企业的经济效益。本文采用不同的超结构模型分别描述无分流和有分流换热网络,提出了换热网络的粒子群同步综合设计法,以最小总费用为设计目标,同步考虑投资费用和运行费用。在无分流换热网络的设计中,以换热网络中各个换热器的换热量为演化个体,按照一定的顺序,借鉴夹点技术的设计规则,按照粒子群算法寻优设计,计算各个换热器的存在及其换热量的大小。在有分流换热网络的设计中,以各流股在各级的分流情况为演化个体,采用两级优化方法,首先采用遗传算法优化各流股在各级的分流股数,再在确定的分流股数下,采用粒子群优化算法计算最佳分流情况。整个设计解决了各个换热器的换热量受到多种约束条件、相互制约等影响设计的难题,仿真研究证明了设计方法的可行性和优越性。以某炼油厂的常减压蒸馏过程换热网络的设计为实际仿真对象,解决了实际目标温度是一个范围而不是定值的问题,设计的换热网络的总体性能较好。本文的研究工作证明了粒子群优化算法等优化技术在换热网络节能设计中的可行性,并具有较好的效果,可以进一研究与完善,以提高换热网络设计的智能性和节能效果。更多还原

【Abstract】 Heat exchanger networks are very common in petrochemical industry. They put hot streams which need to be cooled and cool streams which need to be heated together to use hot streams heat cool streams. Thus a lot of energy can be recycled and much utility can be saved. Energy saving can be fulfilled. Usually a better heat exchanger networks must make each stream temperature from initial to target under several conditions with minimum investing cost and minimum operating cost. Designing heat exchanger networks is an optimization problem. It is also a very important aspect in energy saving of petrochemical producing. On one hand, intelligent design approach is need in designing more and more. On the other hand, more practical knowledge must be used. This paper modified particle swarm optimization algorithm and used it to design heat exchanger networks with some practical knowledge in order to get a quick design rate, get better heat exchanger networks and make more benefit to factories.In this paper, different super structures were used to describe heat exchanger networks without split and with splits. A novel design approach based on particle swarm optimization algorithm was developed. The design objective is minimizing total cost. And minimizing investing cost and minimizing operating cost were designed at the same time.In designing heat exchange networks without split, it used individuals in population to describe heat transfer quantity of each exchanger. Besides getting some practical knowledge, it calculated heat transfer quantity of each exchanger on special order using particle swarm optimization.In designing heat exchange networks with splits, it used individuals to describe splits of each stream. It used two-layer optimization approach: firstly optimizing split number of each stream based on genetic algorithm, and then optimizing split duty based on particle swarm optimization.As heat transfer quantity in each exchanger is restricted under several conditions and each quantity affects each other, this approach used swarm intelligence to solve these problems and make designing process intelligent base on avoiding sophisticate calculation and keeping feasible of each individual during designing. The simulation result proves it effective. Then it is put into designing heat exchanger network in atmospheric and vacuum distillation to solve the actual simulation problem.All this work proves that intelligent technology such as particle swarm optimization is feasible in designing heat exchanger networks and has better result. It can be study more to design better heat exchanger networks and to get improved effect of energy saving.更多还原