基于分解算法的功热交换网络多目标优化

功热网络设计问题指在流程设计中对变压和换热过程进行耦合优化设计的问题,以此来提高整体系统的能效并降低成本。前人工作中一般采用数学规划法对功热网络建模优化。然而,由于存在变压过程和换热器面积计算的非线性约束,以及换热匹配的二元变量,整体模型往往是一个高度非凸的混合整数非线性规划模型,难以求解。本文提出一种高效的功热网络优化方法。模型中分别用透平压缩机和换热器实现功热网络中轴功和热的交换。求解过程采用分解算法,主问题中用随机算法对关键变量优化,功和热两个子网络问题中用确定性算法求解。目标函数考虑了经济和环境影响。案例测试对比了不同优化目标得到的结果以及多目标Pareto曲线,验证了所提出方法的高效性。     

工艺过程与换热网络的联合优化

提出了用超结构回归模型法来解决工艺过程与换热网络联合优化综合的课题,并且对超结构中整型变量的处理提出了整型变量连续化的方法,为有效地求解混合整数非线性规划问题(MINLP)提供了一种新的途径;应用该方法对某化肥厂的改造扩建进行了优化计算,表明该方法的应用可以产生很大的经济效益.     

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。     

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.     

考虑污垢影响的换热器网络清洗时序优化研究进展

在化工生产中,换热器存在普遍结垢现象,这给生产和操作带来了一定的损失。通过定期清洗换热设备,能够有效地减少损失。本文首先对换热设备表面结垢及应对方法进行介绍,在此基础上系统地概述了国内外换热器网络清洗时序优化的研究进展及其应用情况,并且对现有的求解方法及开发软件进行对比分析。最后针对目前研究状况,本文提出了几点展望。     

基于弹性分析的空分变负荷操作优化

针对空分装置变负荷过程的优化控制问题,提出用弹性分析对不同控制精度下的操作变量进行优化的方法.建立等价超结构换热网络模型用以描述多股流换热器,进而建立可用于操作分析的空分装置机理模型以准确描述空分变负荷过程.引入弹性指数表示关键操作变量的控制范围和精度,用柱形代数分解方法求解关键操作变量弹性边界的显式表达式,将复杂多变...     

基于自适应粒子群优化算法的预测控制算法及其在加热炉支管平衡中的应用

多变量和输出受限系统的预测控制问题一般表现为一个不易直接求解的多变量且多约束的非线性动态规划问题.传统优化方法在解决此优化问题时,存在易收敛到非法解或局部极小、计算时间长以及对模型参数与初值依赖性强的缺点.提出了一种基于自适应粒子群优化的预测控制算法(APSO-DMC),采用自适应粒子群优化算法(APSO)作为模型预测控制的优化方法,在线实时求解最优控制律,从而有效地克服了传统优化方法的不足.将此算法应用于常减压装置加热炉支管温度平衡控制中,仿真试验结果显示了该方法的有效性.     

化工过程综合问题MINLP算法中整型变量的连续化

化工过程系统综合问题需要同时考虑设备结构参数和工艺操作参数,一般用整型变量表示设备的取舍,用连续变量表示操作参数,这就构成一个流程的超结构,在数学形式表现为一个混合整型非线性规划（MINLP）问题。混合整型非线性规划问题的求解成为化工过程综合优化的关键。今根据超结构中整型变量的特征,提出整型变量连续化处理的思路,将MINLP问题简化为NLP问题,然后采用罚函数法求解。最后将该算法运用于加氢脱烷基化（HDA）过程综合的实例研究,结果表明该算法克服了传统方法在处理整型变量时出现的麻烦,为有效快速地进行化工过程综合优化问题提供了一种新的途径。     

基于Kalman滤波的换热器非线性状态参数校正

炼化工艺系统中换热网络数据的准确提取将直接影响到集成优化方案和优化控制的性能。针对换热器非线性状态参数的数据校正,构建了换热器分段线性集总参数传热过程模型,有效地解决了换热器流股物性非线性变化所引起的非线性状态空间方程求解的问题;提出了分段线性的Kalman滤波状态空间方程建立和换热器状态参数校正方法,并通过蜡油加氢装置反应流出物高压换热器工业实例阐述了所提出方法的实现过程和效果。研究表明：换热器分段线性集总参数模型中分段数对Kalman滤波的计算收敛性具有重要影响,随着分段数的增大,换热器状态参数收敛于固定值,分段数需根据计算精度通过试差确定。本文方法可对换热器非线性状态参数实施有效的数据校正,对流股物性进行分段线性化处理具有较高的计算精度,可用于大温差或物性变化较剧烈情况下换热器非线性状态参数的数据校正。     

基于鲁棒模型优化的工艺设计与控制系统集成

采用一种基于鲁棒模型优化方法求解工艺设计与控制集成问题,其核心思想是采用参数不确定状态空间模型描述闭环系统的非线性行为,基于该模型以及二次李雅普诺夫函数可估计系统在外部扰动作用下过程变量变化的最大边界,同时也可测试系统的鲁棒稳定性。该方法避免了求解集成优化问题常用的动态优化方法,可将其转化成一个非线性规划问题。该方法应用于CSTR反应过程的集成优化设计中,结果表明在存在外部扰动时,不仅可以保证过程的经济性能和动态性能,也可保证系统的鲁棒稳定性。     

考虑关键换热器备用的原油预热系统清垢周期优化

原油结垢是原油预热过程面临的一个严峻问题,它使换热器的传热系数降低,影响正常的生产过程。应对原油预热过程的结垢问题最普遍的方法就是对换热器进行周期清洁,并优化清洁周期。许多结垢严重的行业都采用换热器备用的方式来减少因换热器离线造成的热回收减小,但原油预热系统尚未考虑,因而进一步考虑了关键换热器的备用来进行原油预热系统清垢周期优化。首先选取关键换热器,再通过模拟退火算法进行清洁周期优化。应用所提出的方法对简化的原油预热系统进行了清垢周期优化,结果显示,考虑换热器备用时所得到的清垢周期经济效益更好。     

Simultaneous MINLP synthesis of heat exchanger networks comprising different exchanger types

This paper describes the simultaneous MINLP synthesis of heat integrated heat exchanger networks comprising different heat exchanger types. The stage-wise superstructure of heat exchanger networks (HEN) by Yee and Grossmann (Comput. Chem. Eng. 14 (1990) p. 1165) is extended to alternative exchanger types. The selection of the types is modeled by disjunctions based on operating limitations and the required heat transfer area. Since different types of heat exchangers involve different design geometries, which influences the inlet and outlet temperatures of heat exchangers, additional constraints are specified to provide a feasible temperature distribution in HEN. The consideration of different exchanger types drastically increases the combinatorics, size and computation effort needed to solve the problem. The integer-infeasible path MINLP approach has been applied to perform an efficient initialization scheme and to halve CPU times for solving MILP master problem of the modified OA/ER algorithm. A special multilevel MINLP procedure in reduced integer space has been proposed to solve medium size HEN problems (20 streams) comprising 10³ and more binary variables.     

Heat exchanger network synthesis with detailed exchanger designs—2. Hybrid optimization strategy for synthesis of heat exchanger networks

We propose a new strategy to synthesize heat exchanger networks with detailed designs of individual heat exchangers. The proposed strategy uses a multistep approach by first obtaining a heat exchanger network topology through solving a modified version of the mixed integer nonlinear programming (MINLP) stage-wise superstructure of Yee and Grossmann, which includes a smoothed LMTD approximation and pressure drops. In a second nonlinear programming (NLP) suboptimization step, we allow for nonisothermal mixing to solve problems with or without exchanger bypasses. The selected heat exchangers along with the mass and energy balances obtained are then used to design the network with detailed exchanger designs through solving a sequence of NLPs for individual heat exchanger designs. The NLPs are based on the detailed discretized optimization models of Kazi et al., which solve quickly and reliably to obtain heat exchangers based on rigorous, first-principles derived coupled differential equations. These models solve a differential algebraic equation system and do not rely on usual assumptions associated with other heuristic-based exchanger design methods, such as log mean temperature difference and F_T correction factors. These detailed exchanger designs are then used to update the network optimization model through sets of correction factors on heat exchanger area, number of shells, heat transfer coefficients, and pressure drops of each exchanger design, in a method based on that of Short et al. The method solves reliably, guaranteeing feasible exchangers for every potential network generated by the shortcut models, through validation with rigorous heat exchanger models at every iteration. In addition, the method does not increase the nonlinearity of the MINLP model, nor does it require any manual intervention or initialization from the user. Three examples are solved and the results are compared to those obtained in the literature.     

微分进化算法应用于换热网络全局最优化

前言换热网络是过程系统中实现能量回收和高效利用的重要环节,其性能直接关系到整个系统的能量利用水平。目前,换热网络优化设计的方法主要分为三类,分别是夹点法[1-2]、数学规划法[3-4]与启发式方法[5-7]。     

柔性换热网络综合与清洗计划同步优化(英文)

A novel methodology is presented for simultaneously optimizing synthesis and cleaning schedule of flexible heat exchanger network (HEN) by genetic/simulated annealing algorithms (GA/SA). Through taking into account the effect of fouling process on optimal network topology, a preliminary network structure possessing twofold oversynthesis is obtained by means of pseudo-temperature enthalpy (T-H) diagram approach prior to simultaneous optimization. Thus, the computational complexity of this problem classified as NP (Non-deterministic Polynomial)-complete can be significantly reduced. The promising matches resulting from preliminary synthesis stage are further optimized in parallel with their heat exchange areas and cleaning schedule. In addition, a novel continuous time representation is introduced to subdivide the given time horizon into several variable-size intervals according to operating periods of heat exchangers, and then flexible HEN synthesis can be implemented in dynamic manner. A numerical example is provided to demonstrate that the presented strategy is feasible to decrease the total annual cost (TAC) and further improve network flexibility, but even more important, it may be applied to solve large-scale flexible HEN synthesis problems.     

基于遗传/模拟退火算法考虑压降的换热网络优化改造

工艺系统中需要加入新物流、现存的换热网络结构需要改动、换热网络有较大的能量回收潜力,这些都是换热网络需要进行改造的原因.本文基于非等温混合分级超结构,建立了换热网络优化改造的MINLP数学模型,同时考虑了改造后的公用工程费用、新增换热器的费用、原有换热器新增面积的费用、新增动力设备的费用.将用于换热网络综合的分级超结构模型进行了简要的改进,增加了一些和现存设备相关的限制条件和二元变量.通过对现存换热网络进行分析,充分的利用原有的换热设备和换热网络结构,基于GA/SA算法求解可 得到优化改造的换热网络结构.实际算例的计算结果和文献结果对比表明,本文得到的改造方案用较少的投 资,实现了较多的公用工程节省,新增设备费用的静态投资回收期为0.53年,为换热网络改造提供了好的可行方案.     

Optimal cyclic cleaning scheduling in heat exchanger networks under fouling

This work addresses the problem of cyclic cleaning scheduling in heat exchanger networks (HENs). A salient characteristic of this problem is that the performance of each heat exchanger decreases with time which can then be restored to its initial state by performing cleaning operations. Due to the cyclic nature of the schedule, some operations may span successive cycles (wrap-around) which should be taken into account in the mathematical models. A tight mixed integer linear programming (MILP) model is proposed minimising cleaning cost and energy requirements. A complex heat exchanger network example is presented to illustrate the applicability of the proposed model.