混合微分进化算法应用于换热网络优化

针对微分进化(Differential Evolution,DE)算法应用于换热网络优化存在局部搜索能力不足、收敛速度慢和求解精度低等问题,提出一种混合微分进化(Hybrid Differential Evolution,HDE)算法。当DE算法的变异、交叉和选择操作不再使种群的最优值继续进化时,加入梯度操作使当前种群的最优个体趋向更好的解。为了防止算法早熟收敛,当种群的多样性低于设定的阈值时,引入迁移操作,在最优个体附近区域重新生成新的个体并以此替换旧的个体,增强算法的种群多样性。通过算例验证了该算法可以有效适用于换热网络的优化过程,具有更强的局部搜索能力,更快的收敛速度和更高的优化效率。     

Thermodynamic optimization of cross flow plate-fin heat exchanger using a particle swarm optimization algorithm

This study explores the use of particle swarm optimization (PSO) algorithm for thermodynamic optimization of a cross flow plate-fin heat exchanger. Minimization of total number of entropy generation units for specific heat duty requirement under given space restrictions, minimization of total volume, and minimization of total annual cost are considered as objective functions and are treated individually. Based on the applications, heat exchanger length, fin frequency, numbers of fin layers, lance length of fin, fin height and fin thickness or different flow length of the heat exchanger are considered for optimization. Heat duty requirement constraint is included in the procedure. Two application examples are also presented to demonstrate the effectiveness and accuracy of the proposed algorithm. The results of optimization using PSO are validated by comparing with those obtained by using genetic algorithm (GA). Parametric analysis is also carried out to demonstrate the effect of heat exchanger dimensions on the optimum solution. The effect of variation of PSO parameters on convergence and optimum value of the objective has also been presented.     

基于GA-BP神经网络的土壤-空气换热器换热量预测分析

文章对位于太原市一个日光温室内的土壤-空气换热器进行夏季工况试验,获得了不同运行工况下换热管内空气的温度和湿度的分布数据。试验结果表明:土壤-空气换热器具有一定的除湿效果;当换热管长度为17.2 m,换热管内空气流速为2 m/s时,土壤-空气换热器潜热换热量占全热换热量的31.37%,且潜热换热量在全热换热量中的占比随着换热管长度的增加而逐渐降低。文章将得到的试验数据分为训练样本和测试样本,同时,分别基于BP神经网络和GA-BP神经网络建立了土壤-空气换热器换热量的预测模型,并对模拟结果进行对比。模拟结果表明:GA算法对BP神经网络具有较好的优化作用;与基于BP神经网络建立的土壤-空气换热器换热量预测模型相比,基于GA-BP神经网络建立的土壤-空气换热器换热量预测模型的预测精度较高,收敛所需的迭代次数也较少。     

基于粒子群神经网络的热力站供热负荷预测

结合河北省秦皇岛市碧水园热力站的供热实际情况,提出了利用BP神经网络进行热力站供热负荷的预测。为克服标准BP算法收敛速度慢和易于陷入局部最小的问题,提出利用进化算法——粒子群算法进行神经网络初始状态的优化。在此基础上,进一步提出了混合粒子群算法和速度变异粒子群算法两种改进算法提高优化性能。计算结果表明,采用粒子群算法和BP算法相结合的办法,可以明显提高热负荷的预测精度。     

蚁群算法在换热网络优化中的应用

提出将蚁群算法应用于换热网络优化中,按照相等的能量份额将各股热流体分解成能量集合,热流体能量通过换热器在与冷流体换热的过程中得到分配,换热器单元面积得到相应地调整．能量分配过程中换热网络得到优化,从而使年综合费用减少的换热器面积不断积累,最终形成了一个最优的换热网络结构．通过具体算例验证了该方法的可行性和有效性,最终优化的结果证明该方法具有较强的全局搜索能力,能够应用于复杂换热网络的优化问题中．     

换热网络全局优化的多维峰谷轮换法

在峰谷轮换法的基础上提出了利用多维峰谷轮换法对以年综合费用最少为目标函数的无分流换热网络进行优化.在换热网络变量寻优过程中,首先将目标函数极小化得到一个局部极小值点,然后沿着多个方向进行变量搜索,找出最先跳出局部极小值点的变量组合,使得跳出局部极小值的搜索效率高于单变量的搜索效率,并可寻找到更好的换热网络结构,将极小化与跳出局部极小值点过程交替进行直至求得全局最优解.通过算例验证了该方法的可行性,且可找到比其它方法的优化结果更优的换热网络结构.     

改进精度的换热网络优化遗传算法

在换热网络分级超结构及其数学模型基础上,提出了改进精度的换热网络优化综合遗传算法,该算法采用三层优化结构,利用中间层修正换热系数和流体物性,在计算量上升不多的情况下,从本质上提高了换热网络优化过程中的精度。采用此方法对炼油厂常减压系统进行优化,得到了良好的效果。     

基于分级超结构的换热网络改造优化

建立了基于分级超结构模型的换热网络改造同步优化数学模型。该模型不依赖于夹点约束,不需要预先给定最小传热温差,能够有效权衡改造投资费用与运行费用之间的关系。改造投资费用中考虑了现有换热器的重新配置费用、现有换热器新增传热面积费用和新增换热器费用,符合工程实际要求。针对换热网络改造优化数学模型具有不连续和非线性的特点,数学模型的求解采用双层优化策略,其中表示网络结构调整的离散变量优化利用遗传算法,而表示操作参数的连续变量优化利用粒子群算法优化。2个不同规模的换热网络改造算例用于验证所提出方法的有效性。     

隔代强制进化遗传算法在换热网络优化中应用

在对换热网络分级超结构及其数学模型分析的基础上,对网络综合优化问题进行了研究．针对普通遗传算法及其它优化算法无法保证网络优化质量和效率的缺点,对遗传算法进行了改进,提出了换热网络隔代强制进化遗传算法。该方法将换热网络结构信息转化为种群中染色体信息,利用种群的进化实现网络结构的优化,在进化过程中使用隔代强制策略,使种群向更优方向稳步进化,保证各代优化结果的有效性,降低最优群体的生成代数,并利用最优个体保存技术记录优化过程中最佳换热网络结构。采用此方法对具体换热网络实例进行了优化综合,结果表明：隔代强制进化遗传算法能在网络优化过程中避免早熟收敛而陷入局部最小点的现象,使搜索质量和效率得到有效提高。用隔代强制进化遗传算法对有分流和无分流换热网络进行优化综合,均能获得综合性能良好的网络结构。     

基于连续性的换热网络整型变量优化策略

换热网络优化是典型的混合整数非线性问题,其整型变量(换热网络的结构)的组合情况对于其优化的走向以及局部最优解的质量具有至关重要的作用.分析了换热网络结构与性能之间的连续性特征;利用最速下降法对换热网络整形变量进行初步优化以确定合适的换热器数目,生成一系列连续变化的换热网络结构;以结构序列作为优化变量,借助换热网络性能连续性原理,将多维整型变量转换为一维连续变量,对整型变量进行启发式的连续性搜索.通过具体算例求解,该方法帮助优化过程跳出了局部最优的陷阱,并得到了较好的优化结果.     

Studies on the retrofit of heat exchanger network based on the hybrid genetic algorithm

The retrofit of heat exchanger networks (HENs) is an important branch of investigation for systematic heat integration. The studies on the economical and efficient retrofit techniques are very important for the high energy-consumption enterprises to save energy, protect environment and improve their market competitiveness. Because the retrofit of HEN is an optimization problem normally solved by a mixed integer nonlinear program (MINLP) which requires enormous solution space, it is very difficult to solve it with the traditional optimization methods. In this paper, by the analysis of an existing heat exchanger network, the hybrid genetic algorithm is applied to obtain the optimal retrofitted HEN with full utilization of the existing heat exchangers and structures. Two examples are taken to show the better effect of the retrofit method with the optimal new heat exchangers and re-piping cost and energy saving.     

基于温差均匀性因子协进化的双层算法同步优化换热网络

针对同时存在整型变量和连续型变量的换热网络综合问题,提出一种双层优化方法。外层以换热网络的温差均匀性因子作为网络结构性能的评价指标,通过蒙特卡洛随机抽样技术产生试探结构,采用整型优化算法逐步进化外层结构;内层以最小年综合费用作为优化指标,采用动态更新子群的改进粒子群算法优化连续变量。优化结果表明,温差均匀性因子可以有效评价换热网络的结构性能,从而指导结构的进化;改进的粒子群算法具有更强的全局搜索能力,相关算例均找到了更优的网络设计,应用于工业生产实际,可以有效节约成本。     

The application of field synergy number in shell-and-tube heat exchanger optimization design

In the present work the field synergy principle is applied to the optimization design of the shell-and-tube heat exchanger with segmental baffles. The field synergy number which is defined as the indicator of the synergy between the velocity field and the heat flow is taken as the objective function. The genetic algorithm is employed to solve the heat exchanger optimization problems with multiple design variables. The field synergy number maximization approach for heat exchanger optimization design is thus formulated. In comparison with the initial design, the optimal design leads to a significant cost cut on the one hand and an improvement of the heat exchanger performance on the other hand. The comparison with the traditional heat exchanger optimization design approach with the total cost as the objective function shows that the field synergy number maximization approach is more advantageous.     

Population-diversity enhancement strategy against clustering of individuals in stochastic method for heat exchanger network synthesis

Random walk algorithm with compulsive evolution (RWCE) performs better for global optimization of heat exchanger network synthesis than other stochastic methods though it faces the inevitable decrease in optimization efficiency during the late period. This paper aims to analyze the relationship between population diversity and optimization performance. Firstly, population diversities are contrasted to explain the relatively satisfactory performance of RWCE. It is found that the optimal structures for individuals become significantly similar with evolution. Secondly, key evaluation indexes are established to identify similar individuals and clusters formed during the evolution. A noteworthy observation of the study is the clustering phenomenon in RWCE where most individuals cluster together with structural community while 5% individuals alone are excluded from the clusters. Finally, a population-diversity enhancement strategy is established to weaken the negative effect of the clustering phenomenon and enhance the global optimization efficiency. The new strategy is efficient in achieving more economical solutions compared to those in literatures.     

Optimizing heat exchanger networks with genetic algorithms for designing each heat exchanger including condensers

This paper presents a procedure for the design of the components of a heat exchanger network (HEN). The procedure first uses pinch analysis to maximize heat recovery for a given minimum temperature difference. Using a genetic algorithm (GA), each exchanger of the network is designed in order to minimize its total annual cost. Eleven design variables related to the exchanger geometry are considered. For exchanger involving hot or cold utilities, mass flow rate of the utility fluid is also considered as a design variable. Partial or complete condensation of hot utility fluid (i.e., water vapor) is allowed. Purchase cost and operational cost are considered in the optimization of each exchanger. Combining every exchanger minimized cost with the cost of hot utility and cold utility gives the total cost of the HEN for a particular ΔT_min. The minimum temperature difference yielding the more economical heat exchanger network is chosen as the optimal solution. Two test cases are studied, for which we show the minimized total cost as a function of the minimum temperature difference. A comparison is also made between the optimal solution with the cost of utilities and without it.     

Applying multiple decomposition methods and optimization techniques for achieving optimal cost in mixed materials heat exchanger networks

The optimization of the total annual cost in heat exchanger networks has been one of the overarching goals when synthesizing these networks. Several methodologies and techniques have been developed to achieve optimal costs in mixed material heat exchanger networks. This paper demonstrates the application of two decomposition methodologies (total decomposition and partial decomposition) for typical cost rules. The objective function was defined as the optimization and minimization of the total annual cost in mixed materials heat exchanger network. Three optimization algorithms, hybrid genetic‐particle swarm optimization (GA‐PSO), shuffled frog leaping algorithm (SFLA) techniques, and ant colony optimization (ACO), were used to further optimize the total cost in mixed materials heat exchanger network. The results indicate that the total annual cost in partial decomposition method was smaller than that in full integration method and total decomposition method. The reduction of the total annual cost was about 27% for GA‐PSO algorithm, 24% for SFLA and 10% for ACO relative to the results reported in this work. In partial decomposition method, at least one mixed material of heat exchanger was used to reduce the hot and cold utility for decreasing the total annual cost. Partial decomposition method resulted in the highest reduction of the total annual cost compared with other methods. Percentage of difference of the total annual cost were 0.36%, 1.92%, and 5.05% for full integration, total decomposition, and partial decomposition methods, respectively, in comparison with the previous studies. Results have been compared with the results of other studies to demonstrate the accuracy of the applied algorithms.     

基于启发式免疫遗传算法的配电网广义电源规划

在分布式电源接入配电网的规划中将广义电源的有功功率作为控制变量,考虑了广义电源无功功率对配电网分布式电源优化配置的影响,从而合理规划广义电源接入,降低系统的网络损耗,进一步提高系统运行的电压水平。针对传统优化算法在局部搜索能力和收敛性能等方面的缺陷,根据累加优化原理对系统种群进行初始优化以提高收敛速度,在疫苗接种时利用矢量矩浓度的概念进行抗体选择,依据抗体浓度和抗体适应性原则进行个体优选,提出了启发式免疫遗传算法。对IEEE-33节点系统的计算分析表明,该方法能够对广义电源在配电网中的选址和定容进行有效配置和优化,在寻优能力和收敛速度上优于传统算法。     

进化概率差异化策略优化有分流换热网络

强制进化随机游走算法优化换热网络时具有程序简单、全局搜索能力强等特点,但在优化过程中不同的进化阶段对进化概率需求不同,算法中设置单一的进化概率难以满足实际进化需求。因此,提出一种进化概率差异化策略,该策略的核心思想是智能识别流股的换热程度,动态调整进化概率,对存在公用工程的流股强制参与进化,使算法在前期具有较强的结构搜索能力;完全换热的流股通过降低进化概率,提升算法全局的精细搜索能力。采用15SP和39SP算例进行验证,所获年综合费用分别为1 494 690和1 894 477$/a,验证了该策略能够提升算法的优化效率与质量。     

Optimization design of shell-and-tube heat exchanger by entropy generation minimization and genetic algorithm

In the present work, a new shell-and-tube heat exchanger optimization design approach is developed, wherein the dimensionless entropy generation rate obtained by scaling the entropy generation on the ratio of the heat transfer rate to the inlet temperature of cold fluid is employed as the objective function, some geometrical parameters of the shell-and-tube heat exchanger are taken as the design variables and the genetic algorithm is applied to solve the associated optimization problem. It is shown that for the case that the heat duty is given, not only can the optimization design increase the heat exchanger effectiveness significantly, but also decrease the pumping power dramatically. In the case that the heat transfer area is fixed, the benefit from the increase of the heat exchanger effectiveness is much more than the increasing cost of the pumping power.     

夹点理论及其在换热网络中的优化分析

本文主要介绍了利用夹点技术设计换热网络的原则及需要注意的问题,并利用夹点技术对乙烯生产原有换热网络进行夹点分析,研究换热网络利用的瓶颈,找出换热网络不合理的环节和原因。经优化改造后新增4台换热设备,新增设备及改装费用约2 900万元,但每年节约公用工程费用2 949万元,回收期为一年,故改造合理,节能明显。