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.     

A systematic approach for synthesizing a low-temperature distillation system

In this paper, by combining a stochastic optimization method with a refrigeration shaft work targeting method, an approach for the synthesis of a heat integrated complex distillation system in a low-temperature process is presented. The synthesis problem is formulated as a mixed-integer nonlinear programming (MINLP) problem, which is solved by simulated annealing algorithm under a random procedure to explore the optimal operating parameters and the distillation sequence structure. The shaft work targeting method is used to evaluate the minimum energy cost of the corresponding separation system during the optimization without any need for a detailed design for the heat exchanger network (HEN) and the refrigeration system (RS). The method presented in the paper can dramatical y reduce the scale and complexity of the problem. A case study of ethylene cold-end separation is used to il ustrate the application of the approach. Compared with the original industrial scheme, the result is encouraging.     

基于专家系统和遗传算法的换热网络的建模和优化

A new superstructure from of heat exchanger networks(HEN) is proposed based on expert system (ES). The new superstructure from is combined with the practical engineering.The different investment cost formula for different heat exchanger is also presented based on ES.The mathematical model for the simultaneous optimization of network configuration is established and solved by a genetic algorithm.This method can deal with larger scale HEN synthesis and the optimal HEN configuration is obtained automatically.Finally,a case study is presented to demonstrate the effectiveness of the method.     

炼油厂氢气网络建模与多目标优化(英文)

The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming (MINLP). A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.     

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.     

考虑操作分解的热集成用水网络设计

This article deals with the design of energy efficient water utilization systems allowing operation split. Practical features such as operating flexibility and capital cost have made the number of sub operations an important parameter of the problem. By treating the direct and indirect heat transfers separately, target freshwater and energy consumption as well as the operation split conditions are first obtained. Subsequently, a mixed integer non-linear programming （MINLP） model is established for the design of water network and the heat exchanger network （HEN）. The proposed systematic approach is limited to a single contaminant. Example from literature is used to illustrate the applicability of the approach.     

质量交换网络集成的状态空间法

State space approach is an effective method to mass-exchange network (MEN) synthesis. By decomposing the network into two interactive parts, a distribution network and a process operator, the synthesis problem can be formulated into a mixed integer nonlinear programming (MINLP) model. In this article, a generalized state space model based on typical MEN is established and verified in two cases. A new asymmetrical operator and cost index are also adopted to speed up the solution process. The results demonstrate the efficiency of the proposed approach.     

模拟退火方法用于带有中间换热器精馏塔的优化综合

This article presents a simulated annealing-based approach to the optimal synthesis of distillation column considering intermediate heat exchangers arrangements. T-he number of intermediate condensers and/or intermediate reboilers, the placement locations, the.operating pressure of column, and the heat duties of intermediate heat exchangers are treated as optimization variables. A novel coding procedure making use of an integer number series is proposed to represent and manipulate the structure of system and a stage-to-stage method is used for column design and cost calculation. With the representation procedure, the synthesis problem is formulated as a mixed integer nonlinear programming （MINLP） problem, which can then be solved with an improved simulated annealing algorithm. Two examples are illustrated to show the effectiveness of the suggested approach.     

COMPUTER AIDED OPTIMAL HEAT EXCHANGER NETWORK SYNTHESIS BY A TWO-STAGE METHOD

This paper presents a two-stage method for the optimal heat exchanger network synthesis.In the firststage based on the study of the pinch point properties,a network minimizing the utility consumption and thenumber of exchangers is developed.Usually,this network is close to the optimal.In the second stage,anonlinear programming formulation is developed,and its solution with features of minimum capital andannual operating costs provides an improvement on the network obtained in the first stage.An integratedsoftware package for heat exchanger network synthesis has been developed.This package consists of a sp-readsheet,a graphics program,a data base management system,a menu program,an application networksynthesis program,a network simulation program and a data base of standard size exchangers.The appli-cation of this method is illustrated with several examples which include a complex crude oil preheating heatexchanger network.     

A numerical study on heat transfer enhancement and design of a heat exchanger with porous media in continuous hydrothermal flow synthesis system

The aim of this study is to use a new configuration of porous media in a heat exchanger in continuous hydrothermal flow synthesis (CHFS) system to enhance the heat transfer and minimize the required length of the heat exchanger.For this purpose,numerous numerical simulations are performed to investigate performance of the system with porons media.First,the numerical simulation for the heat exchanger in CHFS system is validated by experimental data.Then,porous media is added to the system and six different thicknesses for the porous media are examined to obtain the optimum thickness,based on the minimum required length of the heat exchanger.Finally,by changing the flow rate and inlet temperature of the product as well as the cooling water flow rate,the minimum required length of the heat exchanger with porous media for various inlet conditions is assessed.The investigations indicate that using porous media with the proper thickness in the heat exchanger increases the cooling rate of the product by almost 40％and reduces the required length of the heat exchanger by approximately 35％.The results also illustrate that the most proper thickness of the porous media is approximately equal to 90％ of the product tube's thickness.Results of this study lead to design a porous heat exchanger in CHFS system for various inlet conditions.     

用遗传算法进行多流股换热器网络综合的研究

建立了多流股换热器网络综合数学模型，该模型改进了文献中等温混合的不合理假设。多流股换热器网络综合问题本质上是一个混合整数非线性规划问题(MINLP)，这类问题的非凸非线性的特性使得目标函数存在多个局部最优解。传统的基于梯度的搜索方法在处理这类问题时由于计算规模庞大且极易陷于局部最优解而不再适用，而遗传算法却为解决这类问题提供了很有希望的一个方向。因而对遗传算法求解多流股换热器网络综合问题进行了研究，提出了可以自动产生可行的多流股换热器网络的方法策略，最后通过两个例题说明所提方法是可行的。     

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.     

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.     

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.     

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。     

基于新策略粒子群算法优化换热网络

换热网络综合优化是过程系统中最广泛研究的方向。尽管如此,MINLP的复杂性给粒子群算法的应用提供了广泛的空间。首先,提出两种不同机理的局部搜索策略来完善粒子群算法作为启发式算法局部搜索能力不强和精度不高的问题,使算法能更有利地接近全局最优的局部极值。其次,对含固定投资费用的算例,采用费用计算替换公式的策略,来避免迭代计算初期面积较小时因为固定投资费用权重较大而使算法陷入局部最优问题。最后用4个四股流算例分别从不同侧面说明以上两种策略的有效性,并都得到了该算例目前为止最好的局部极值。     

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.     

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.     

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.     

过程系统能量集成同步最优综合法

将换热网络超结构混合整数非线性规划多目标同步最优综合方法进一步扩展到与过程系统的联合优化,提出了改进的过程热集成同步综合方法,并以反应分离过程与换热网络能量集成为例,建立了同步优化超结构模型,采用混合整数非线性规划的遗传算法求解,可同时得到热集成系统最优的流程结构和操作条件。