Application of intensified heat transfer for the retrofit of heat exchanger network

A number of design methods have been proposed for the retrofit of heat exchanger networks (HEN) during the last three decades. Although considerable potential for energy savings can be identified from conventional retrofit approaches, the proposed solutions have rarely been adopted in practice, due to significant topology modifications required and resulting engineering complexities during implementation. The intensification of heat transfer for conventional shell-and-tube heat exchangers can eliminate the difficulties of implementing retrofit in HEN which are commonly restricted by topology, safety and maintenance constraints, and includes high capital costs for replacing equipment and pipelines. This paper presents a novel design approach to solve HEN retrofit problems based on heat transfer enhancement. A mathematical model has been developed to evaluate shell-and-tube heat exchanger performances, with which heat-transfer coefficients and pressure drops for both fluids in tube and shell sides are obtained. The developed models have been compared with the Bell-Delaware, simplified Tinker and Wills-Johnston methods and tested with the HTRI® and HEXTRAN® software packages. This demonstrates that the new model is much simpler but can give reliable results in most cases. For the debottlenecking of HEN, four heuristic rules are proposed to identify the most appropriate heat exchangers requiring heat transfer enhancements in the HEN. The application of this new design approach allows a significant improvement in energy recovery without fundamental structural modifications to the network.     

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。     

管翅式换热器遗传算法优化

管翅式换热器作为一种高效的换热设备,提升其换热效率和降低投资成本显得至关重要.通过单目标遗传算法(GA)和多目标非支配排序遗传算法(NSGA-Ⅱ)对管翅式换热器进行优化设计,设置翅片高度、翅片间距、管长、横向管数和纵向管数5个自变量的合理设计范围,单目标优化选用换热器效率、压降熵产和最大收益3个目标函数,根据热力学第一...     

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.     

Achievements and suggestions of heat metering and energy efficiency retrofit for existing residential buildings in northern heating regions of China

In order to promote energy efficiency and emission reduction, the importance of improving building energy efficiency received sufficient attention from Chinese Government. The heat metering and energy efficiency retrofit for existing residential buildings of 0.15 billion m² in northern heating regions of China was initiated in 2007 and completed successfully at the end of 2010. This article introduced the background and outline of the retrofit project during the period of 11th five-year plan. Numerous achievements that received by retrofit such as environmental protection effect, improvement of indoor environment, improvement of heating system, investment guidance effect, promotion of relevant industries and increasing chances of employment were concluded. Valuable experience that acquired from the retrofit project during the period of 11th five-year plan was also summarized in this article. By analyzing the main problems emerged in the past, pertinent suggestions were put forward to promote a larger scale and more efficient retrofit project in the period of 12th five-year plan.     

Heat exchanger networks retrofit with considering pressure drop by coupling genetic algorithm with LP (linear programming) and ILP (integer linear programming) methods

This research is trying to develop a new procedure for retrofit of HENs including pressure drop using genetic algorithm (GA) coupled with linear programming (LP) and integer linear programming (ILP) methods. The GA is used to produce structural modifications whereas continuous variables are handled using a converted NLP formulation for Maximum Energy Recovery (MER). The converted NLP consists of an LP for MER with adding a search loop to find the best minimum approach temperature and split ratios which are easier to solve.To prevent complexity and ensure optimum solution, the pressure drops of streams are calculated from the results of LP and then a modified ILP problem is solved to determine the maximum profit of retrofit of HENs. The motivation of the ILP is decision making for elimination or reuse of current exchangers and pumps and/or introducing new ones to the network. Results show that the proposed method often finds better solutions than those reported in the literature.     

Pressure drop optimisation in debottlenecking of heat exchanger networks

Process integration technology is now widely applied in grass-roots design, energy saving retrofit and the debottlenecking of heat exchanger networks. This technology has been used in a variety of industries and proved to be reliable and applicable in engineering design. Debottlenecking may apply to a specific part or entire unit, whether it is due to increased throughput or process modifications. One of the advanced methods for debottlenecking that is currently used is based upon fixed allowable pressure drops, through which a retrofit can be achieved without a need for pump and/or compressor replacement. This research is trying to develop a new procedure for pressure drop optimisation in debottlenecking. This procedure enables the designer to study pump and/or compressor replacement whilst at the same time optimising the additional area and operating cost of the network. It deals with the problem of optimal debottlenecking of heat exchanger networks considering minimum total cost. Moreover, one can consider the possibility of the replacement of a given pump with a smaller one. The new procedure has been effectively applied to a crude oil pre-heat train, which was subject to some 20% increase in throughput, and the corresponding results proved to be accurate enough.     

Multi‐objective genetic algorithm optimization of thermoelectric heat exchanger for waste heat recovery

A model is developed to simulate a cross‐flow heat exchanger, including fins, in the wall of which thermoelectric generators are sandwiched. Such a system could be used for waste heat recovery. The model is used to optimize the device based on several objective functions: total volume, total number of thermoelectric modules, power output, and pumping power. The design variables are the local distribution of modules and of current, the shape of the fins, and the division of the heat exchanger in sub‐channels. Pareto fronts are achieved with a multi‐objective genetic algorithm, and are presented here. The results show that the number of sub‐channels in the heat exchanger has a larger impact on the overall performance than the fin geometry for this particular problem. Also, the net power output is mostly correlated to the number of thermoelectric modules, and less to the heat exchanger volume. Various relations between the different competing objectives are shown and analyzed. Copyright © 2011 John Wiley & Sons, Ltd.     

一种新的换热网络改造方法探析——基于原有网络拓扑结构和换热器的最优应用

通过对原有换热网络的拓扑结构和换热器匹配进行分析,在有分流的分级超结构物理模型的基础上,提出了一种新的可满足一般技改要求的换热网络改造方法.该方法能够在对原有换热网络的拓扑结构和原有换热器面积充分利用并满足冷热流股进出口温度需求的同时,实现对原有换热网络的节能改造.同时建立了换热网络改造的数学模型,并应用混合遗传算法对其进行了求解.实例分析结果表明,该方法具有操作简单、节能潜力大以及投资回收期短等优点.     

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．     

换热器网络设计的优化研究

基于感知器模型本文提出一种换热器网络优化新算法,在遗传迭代过程中,依据目标函数的适应值,该算法不断调节感知器的权值,使感知器以随机方式搜索网络拓扑结构和运行参数。经过本文的计算表明：这一算法对于多维、多峰、非凸函数也具有很好的适应性,能够有效地克服传统方法（混合整数非线性优化）的不足之处。     

基于智能技术的换热器经济运行的研究

换热器运行一段时间后,垢阻的增大使它的传热性能下降,输运泵功率增加。通过在线监测和遗传算法优化计算及神经网络的实时变频调控,使换热器在除垢周期内能够达到经济性运行,以此逼近它在设计时的运行工况点或满足实际使用时设定的需求。其目的达到高效节能和安全运行,其效果可以用热经济学分析法全面评价它的技术与经济性。     

Influence of heat exchanger effectiveness on performance of vapour absorption heat transformers

A thermodynamic analysis was made to study the effect of heat exchanger effectiveness on the performance of single stage vapour absorption heat transformers (VAHT). The working fluid pairs considered were R21-DMF and R21-DMETEG. Variations in the performance parameters such as coefficient of performance, exergetic efficiency, concentration difference and circulation ratio at different values of operating temperatures were studied. Among the two working pairs analysed, the R21-DMF pair yielded a high coefficient of performance and exergetic efficiency, whereas the R21-DMETEG pair yielded a high temperature lift at given operating conditions. The improvements in coefficient of performance and exergetic efficiency with heat exchanger effectiveness were more pronounced for R21-DMF than for R21-DMETEG. Correlations are presented for quick estimation of performance under various operating conditions.     

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.     

Predicting the capacity of a heat exchanger by a thermal network method

In this paper a thermal network method using the effective specific heat model of a refrigerant with phase change is proposed for predicting the capacity of a plate‐fin and tube‐type heat exchanger. The effective specific heat model can attain an accurate result of a condenser's heat exchanging capacity when it has a small number of elements. By comparing calculated results with those of an experiment, it is found that the error in the condenser's calculated capacity is less than 1% when the range of subcool temperature is from 15 to 22 K at the outlet of refrigerant flow. © 2002 Scripta Technica, Heat Trans Asian Res, 31(2): 128–140, 2002; DOI 10.1002/htj.10021     

基于夹点技术的航煤加氢换热网络优化

针对某航煤加氢装置现行换热网络夹点温差不合理导致能耗较大的现状,利用夹点技术对该装置换热网络进行分析、优化。在该装置实际工况下的夹点温差附近选取相应的夹点温差,计算出不同夹点温差对应换热网络的年总费用,得出年总费用最小的夹点温差,即最优夹点温差。在最优夹点温差的基础上生成新的换热网络,结果表明,节能效果显著。     

RWCE算法控制参数动态更新促进换热网络结构进化策略

相较其他进化算法,强制进化随机游走（RWCE）算法能够始终保持较高的种群多样性,从而有效地跳出局部最优。然而,目前对于该算法进化过程中的控制参数如最大步长、最小换热量或换热面积以及接受差解概率的设置仍无严格定义,其取值方法和取值范围都将对结构进化的进度、换热单元生成和消去速度以及最终的换热单元数产生直接影响。根据换热单元数设定逐渐变化的控制参数,进行逐级优化尝试。引入logistic函数作为接受差解概率的取值策略,使最大步长和保留系数均随换热单元数线性变化,实现控制参数的动态更新从而促进换热网络结构进化。通过算例验证,该策略能提高RWCE算法优化换热网络的效率,可获得更理想的网络结构。     

Thermal-economic multi-objective optimization of plate fin heat exchanger using genetic algorithm

Thermal modeling and optimal design of compact heat exchangers are presented in this paper. ε–NTU$\epsilon ''–''\mathit{NTU}$ method was applied to estimate the heat exchanger pressure drop and effectiveness. Fin pitch, fin height, fin offset length, cold stream flow length, no-flow length and hot stream flow length were considered as six design parameters. Fast and elitist non-dominated sorting genetic-algorithm (NSGA-II) was applied to obtain the maximum effectiveness and the minimum total annual cost (sum of investment and operation costs) as two objective functions. The results of optimal designs were a set of multiple optimum solutions, called ‘Pareto optimal solutions’. The sensitivity analysis of change in optimum effectiveness and total annual cost with change in design parameters of the plate fin heat exchanger was also performed and the results are reported. As a short cut for choosing the system optimal design parameters the correlations between two objectives and six decision variables with acceptable precision were presented using artificial neural network analysis.     

Energy recovery in petrochemical complexes through heat integration retrofit analysis

This paper proposes the principles of how to define a boundary for heat integration in petrochemical complexes which are composed of several interconnected processing units. In order to obtain retrofit schemes that offer significant energy saving potential and are easy to implement, heat integration strategies are also developed in this study. Two case studies based on an aniline plant and an aromatic hydrocarbon plant, each one comprising several processing units, are presented to illustrate the application of these principles and strategies. The boundary for heat integration in each plant can be the whole plant or its individual processing units, the choice of which is determined by their energy saving potentials. Based on energy saving potential, each processing unit in the aniline plant was selected as the boundary for heat integration. The boundary for heat integration in the aromatic hydrocarbon plant, by contrast, was the whole plant. Retrofit schemes for the heat exchanger networks of the two plants, developed using pinch analysis, revealed that significant heating utility savings could be realized with a small number of network structure modifications.     

Optimization of turbine cold-end system based on BP neural network and genetic algorithm

The operation condition of the cold-end system of a steam turbine has a direct impact on the economy and security of the unit as it is an indispensible auxiliary system of the thermal power unit. Many factors influence the cold-end operation of a steam turbine; therefore, the operation mode needs to be optimized. The optimization analysis of a 1000 MW ultra-supercritical (USC) unit, the turbine cold-end system, was performed utilizing the back propagation (BP) neural network method with genetic algorithm (GA) optimization analysis. The optimized condenser pressure under different conditions was obtained, and it turned out that the optimized parameters were of significance to the performance and economic operation of the system.