多流股换热器网络综合方法在原油预热系统中的应用

以原油常减压蒸馏装置原油预热网络为研究对象,进行了多流股换热器网络的实例综合. 基于超结构物理模型建立了改进的多流股换热器网络综合数学模型,提出将该网络综合问题由混合整数非线性规划问题转化为简单的非线性规划问题的求解策略,并利用改进的遗传/模拟退火新算法进行了原油预热网络的综合. 与Hextran软件的综合结果以及现场换热网络的对比表明,本模型和求解策略可以应用于工业规模的多流股换热器网络综合,有可能取得较好的经济效益.     

基于群体智能算法的换热网络同步最优综合

换热网络同步综合方法一般需要建立复杂的混合整数非线性数学规划模型,该模型具有非凸、非线、不连续的特点,属于最难求解的一类NP-hard问题,应用传统的优化算法很难确定其全局最优解,尤其是对大规模换热网络综合问题,甚至无法在合理时间内接近全局最优的局部最优解。针对换热网络同步综合问题,提出基于群体智能算法的分层优化策略,外层采用离散粒子群算法与遗传算法相结合的混合群体智能算法优化换热网络结构,内层在结构变量给定条件下利用改进粒子群算法优化冷热物流分流比与换热负荷。两个典型算例研究证明了该方法能以较高的效率和稳定性得到较好的优化结果。     

基于状态空间超级结构的多流股换热网络最优设计

多流股换热器以其结构紧凑、高效低耗等特点,成为过程强化研究的热门领域,但对于多流股换热的过程与设备优势所在仍然值得商榷。基于多流股换热匹配改进状态空间超级结构,将多流股换热网络综合转化为超级换热器设计。首先,构造级联多流股换热器匹配过程操作算子,通过相邻换热流股匹配,传递温位效应,实现多流股间传热严格计算;借助热容流率混合分配机制,实现各流股间任意分混操作。然后,考虑散热因素,改进目标函数,引入冷热损失和保温材料费用项,清晰体现多流股换热器因换热面互相覆盖而带来的外表面封包优势。进而,建立相应非线性数学规划模型,实现公用工程、设备投资、冷热损耗同步优化。最终,通过文献示例对所提方法可行性与优越性进行验证。     

基于状态空间超级结构的多流股换热网络最优设计

多流股换热器以其结构紧凑、高效低耗等特点,成为过程强化研究的热门领域,但对于多流股换热的过程与设备优势所在仍然值得商榷。基于多流股换热匹配改进状态空间超级结构,将多流股换热网络综合转化为超级换热器设计。首先,构造级联多流股换热器匹配过程操作算子,通过相邻换热流股匹配,传递温位效应,实现多流股间传热严格计算;借助热容流率混合分配机制,实现各流股间任意分混操作。然后,考虑散热因素,改进目标函数,引入冷热损失和保温材料费用项,清晰体现多流股换热器因换热面互相覆盖而带来的外表面封包优势。进而,建立相应非线性数学规划模型,实现公用工程、设备投资、冷热损耗同步优化。最终,通过文献示例对所提方法可行性与优越性进行验证。     

多股流换热器网络及其衍生网络法综合优化

在介绍了多股流换热器网络特点及其与传统网络区别的基础上,提出了一种基于衍生网络的多股流换热器网络综合优化方法,重点在衍生网络的生成、多股流换热器网络的合成以及全局优化格式的生成等方面进行了探讨,结果表明,采用衍生网络的方法能够实现多股流换热器网络的优化.     

基于超结构法的热集成间接式功交换网络综合

换热网络综合的研究和应用对于提高能源利用率已被证明是有效的,而用于回收更高品质能量的功交换网络综合的研究仍处于起步阶段。针对间接式功交换网络综合中复杂推动力约束对流股匹配的制约问题,构建了一种考虑级间热集成的拓展超结构,基于线性拟合压缩机和涡轮机的操作曲线,提出了功源与功阱间流股匹配的识别方法;针对压力、流量与温度的高度非凸非线性关系,提出了采用热集成优化每一级入口温度的松弛策略,建立了以年度总费用最小为目标的混合整数非线性规划模型,通过GAMS求解得到最优的间接式功交换网络结构。最后通过一个算例分析,验证所提方法的有效性和可行性。     

粒子群算法最优同步综合换热网络

采用粒子群算法,对无分流换热网络综合问题提出改进的优化策略.运用超结构建立换热网络模型,以最小年度总费用为优化目标,按顺序求解思路优化换热器换热量.该算法比遗传算法简单,所需调节参数少,且不易陷入局部最优解,能迅速得到换热网络的结构与参数,具有获得全局最优解的能力.仿真研究验证了方法的有效性.     

最小年度化费用换热网络综合的匹配规则研究

本文在分析换热器投资费用的基础上，指出在进行换热网络综合时应以壳程数作为一个综合目标，并通过与公用工程费用的权衡得到年度化费用的换热网络，提出了基于最小壳程数的换热网络综合方法的匹配规则，指出了为获得最小壳程数，冷热流股进行匹配的最大可能交叉程度以及流股间进行匹配的顺序，并提出了不可行匹配的基本准则，通过实例分析得到较好的效果。     

采用浓度差同步优化的质量交换网络设计

质量交换网络(MEN)综合作为过程集成的一个分支，越来越受到过程系统工程领域的广泛关注。因为质量交换网络综合时，贫、富流股之间对应的浓度差(ε)反映传质推动力，影响操作费用和投资费用的大小，所以对其进行优化意义重大。而现有的质量交换网络综合设计一般将贫、富流股之间对应的最小允许浓度差假设为固定值，不能保证得到最优的质量交换网络。针对这一问题，介绍了一种同步优化方法，既能处理单杂质体系，又能处理多杂质体系，建立质量交换网络的超结构模型, 以年度总费用(TAC)最小为目标,将每一对贫、富流股对应的浓度差作为变量，权衡操作费用和投资费用，并利用改进的遗传算法求解，同步得到年度总费用的最小值以及对应的一组最优浓度差，从而得到最优的质量交换网络。     

考虑污垢生长的柔性换热器网络综合

污垢生长会对换热器网络的传热性能产生不利影响。研究基于限制换热器网络柔性的临界操作点,提出同时考虑流股入口温度和热容流率波动以及各流股污垢生长的柔性换热器网络综合方法。首先,提出柔性分析方法,采用搜索矩阵法和并行模拟退火算法,能够有效计算柔性指数且准确识别临界操作点。其次,建立混合整数非线性规划模型,获取在全周期内满足柔性需求且年度总费用最小的换热器网络结构。结果表明,所得网络在全周期内的柔性指数F均大于1,验证了该方法的有效性。     

用伪并行遗传/模拟退火算法进行多流股换热器网络综合的研究

The multi-stream heat exchanger network synthesis (HENS) problem can be formulated as a mixed integer nonlinear programming model according to Yee et al. Its nonconvexity nature leads to existence of more than one optimum and computational difficulty for traditional algorithms to find the global optimum. Compared with deterministic algorithms, evolutionary computation provides a promising approach to tackle this problem. In this paper, a mathematical model of multi-stream heat exchangers network synthesis problem is setup. Different from the assumption of isothermal mixing of stream splits and thus linearity constraints of Yee et al., non-isothermal mixing is supported. As a consequence, nonlinear constraints are resulted and nonconvexity of the objective function is added. To solve the mathematical model, an algorithm named GA/SA (parallel genetic/simulated annealing algorithm) is detailed for application to the multi-stream heat exchanger network synthesis problem. The performance of the proposed approach is demonstrated with three examples and the obtained solutions indicate the presented approach is effective for multi-stream HENS.     

Synthesis of flexible multi-stream heat exchanger networks based on stream pseudo-temperature with genetic/simulated annealing algorithms

The synthesis of flexible heat exchanger network (HEN) is generally regarded as an over-design of process units over a specified range of deviations in process parameters from their nominal values. The HEN obtained is more costly because of the over-design of HEN. The global solution to flexible design problems cannot be guaranteed because of the resulting non-differentiable, non-convex, max–min–max constraint of mixed integer nonlinear programming (MINLP) models. In this paper a new simultaneous two-stage strategy for synthesizing flexible multi-stream HEN (FMSHEN), optimized by genetic/simulated annealing algorithm (GA/SA), is presented. First, based on the pseudo-temperature enthalpy (T–H) diagram method, a new nonlinear programming (NLP) formulation involving all of the vertices of the polyhedral uncertainty region in the space of process parameters is proposed, with the supposition that the feasible region defined by the reduced inequality constraints is convex. An over-design FMSHEN is obtained by optimizing the stream heat transfer temperature difference contribution. Secondly, the optimal structure of the over-design FMSHEN is retained and each heat exchanger area is modified in order to make the FMSHEN less costly. The total annual cost of MSHEN, obtained from the simulation of MSHEN according to the vertices of the polyhedral uncertain region, is regarded as an objective function, and GA/SA is adopted for optimizing the heat exchanger areas. The remarkable feature of the strategy is that the size and the complexity of the problem are reduced significantly and with more probability of locating the global solution. Finally, two examples are illustrated to demonstrate the performance of the strategy for the synthesis of flexible multi-stream heat exchanger networks.     

Synthesis of cost-optimal heat exchanger networks using differential evolution

Heat exchanger network synthesis (HENS) has been one of the most-studied problems in process synthesis. Nevertheless, the complexity of the HENS problem provides enough scope for the development of novel algorithms involving the application of specialized optimization techniques. Evolutionary algorithms (EA) have emerged as viable alternatives to traditional methods for optimizing functions of both continuous and discrete variables. Differential evolution (DE) is one such evolutionary algorithm that promises simple, fast and robust optimization. The present study illustrates the application of this novel technique for the synthesis of heat exchanger networks. The HENS model proposed here considers stream splitting, does away with the simplifying assumption of isothermal mixing of the split streams and has the capability to handle compulsory and forbidden matching of streams. The DE-based model (DEM) does not rely on the decomposition of the problem into subproblems but employs a simultaneous method of approach to optimize the structure of the network of heat exchangers, the heat loads of these exchangers, the split stream heat flows and the minimum approach temperature. The proposed model has been applied to some case studies available in the literature and the results of these studies are very encouraging. The present work represents thus a step forward in the search for robust and efficient global optimization algorithms for the solution of the HENS problem.     

序列数编码的遗传算法柔性优化多股流板翅式换热器通道排列

实数编码的遗传算法在优化多股流板翅式换热器通道排列中进行个体间交叉、变异操作后,存在无法保证各流体的通道数恒定不变的问题。对此,以通道的热负荷累积均方差为目标函数,建立通道排列的优化模型,提出基于序列数编码方式的改进遗传算法进行多股流板翅式换热器通道优化设计,实现了个体间交叉和变异遗传操作。对一包含4个流股57个通道的板翅式换热器通道排列进行优化,并通过多工况点设计对系统柔性进行分析。结果表明:本文优化设计方案的累积热负荷均方差为3562.9W,比文献经验值小2.7%,相比于实数编码遗传算法得到的结果,减少了15.1%,且累积热负荷在零线上下均匀波动。文章表明序列数编码的遗传算法增加了遗传算法种群中个体的多样性,提高了搜索效率具有更好的全局搜索能力。     

Synthesis of multipass heat exchanger networks using genetic algorithms

In this work, a methodology based on genetic algorithms (GAs) is developed for the optimal synthesis of multipass heat exchanger networks (HENs). The network model is based on a stagewise superstructure, and the problem of finding the optimum number of 1–2 shells in series of multipass heat exchangers is aided by an efficient optimization model that uses the standard F_T design method. The proposed methodology allows for proper handling of the trade-offs involving energy consumption, number of units, number of 1–2 shells and network area to provide a network with the minimum total annual cost. The results of the examples show that the new approach is able to find more economical networks than those generated by other methods.     

柔性换热器网络综合与清洗时序安排同步优化

提出在柔性换热器网络设计时考虑设备投入运行后实施在线清洗时序安排的同步优化方法,实现换热器网络动态综合。为降低该问题计算的复杂性,提出采用两阶段法。第一阶段利用虚拟温-焓图法初步综合获得考虑设备结垢过程和流股入口温度、热容流率发生变化时的多周期柔性网络,在同步优化之前识别出较优匹配候选。第二阶段,换热网络结构、设备面积和清洗时序安排利用遗传/模拟退火算法进行同步优化。通过积分方法来计算随时间变化的公用工程消耗,所建立的数学模型因此比以往文献更加严格。计算实例表明,所提方法有效降低年度总费用,同时能够解决大规模柔性换热器网络综合问题。     

A hybrid optimization strategy for simultaneous synthesis of heat exchanger network

The heat exchanger network synthesis problem often leads to large-scale non-convex mixed integer nonlinear programming formulations that contain many discrete and continuous variables, as well as nonlinear objective function or nonlinear constraints. In this paper, a novel method consisting of genetic algorithm and particle swarm optimization algorithm is proposed for simultaneous synthesis problem of heat exchanger networks. The simultaneous synthesis problem is solved in the following two levels: in the upper level, the network structures are generated randomly and reproduced using genetic algorithm; and in the lower level, heat load of units and stream-split heat flows are optimized through particle swarm optimization algorithm. The proposed approach is tested on four benchmark problems, and the obtained solutions are compared with those published in previous literature. The results of this study prove that the presented method is effective in obtaining the approximate optimal network with minimum total annual cost as performance index.     

用于超结构换热器网络热计算和网络综合的显式解

For the optimal design of a heat exchanger network, the inlet and outlet stream temperatures of each heat exchanger in the network should be known. An explicit analytical solution of stream temperatures of an arbitrary connected heat exchanger network was introduced, which is suitable for the thermal calculation of heat exchanger networks. For the heat exchanger network synthesis, this solution was further developed and coupled with the stage-wise superstructure heat exchanger networks. The new calculation procedure reduced the computer memory requirement dramatically. On the basis of this solution, a mathematical model for synthesis of heat exchanger networks with genetic algorithm was formulated, which is always feasible and no iteration is needed. Two examples were calculated with the proposed approach and better results were obtained.     

Globally optimal synthesis of heat exchanger networks. Part III: Non-isothermal mixing in minimal and non-minimal networks

In this work, the enumeration algorithms presented in Parts I and II for the globally optimal synthesis of minimal and non-minimal heat exchanger networks are extended to consider non-isothermal mixing. New mathematical models, including non-isothermal mixing constraints, are proposed to target the bounds of energy consumption and the binding exchanger minimum approximation temperature. These models are solved using the algorithms, which involve solving systems of equations instead of mathematical programming. Three global optimization strategies are proposed to optimize each enumerated structure, involving the use of a global solver directly, or the use of a Golden Search based on energy consumption and a flowrate optimization model considering non-isothermal mixing. The flowrate optimization model is reformulated as a convex problem, which is solved by using nonlinear programming or a mathematical programming-free methodology, that is, solving Karush–Kuhn–Tucker equations. A new Global Optimum Search Algorithm is developed and examples are tested comparing different optimization strategies.