Optimal Heat Exchanger Network Research Articles

Globally optimal simultaneous heat exchanger network synthesis and basic heat exchanger design

Globally optimal simultaneous heat exchanger network synthesis and basic heat exchanger design

Multi-objective optimization of heat exchanger network with disturbances based on graph theory and decoupling

Disturbance poses a significant challenge to highly coupled chemical systems. In this work, a multi-objective optimization framework is developed for reducing the impact of fluctuations on heat exchange networks (HENs) based on graph theory and decoupling. The framework bridges the gap between algebra and structure of HEN through a directed graph (Digraph) and defines the Excitation as a fluctuation impact indicator. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is improved for generating feasible solutions and global optimality, and the quasi-gradient is applied to select an equilibrium solution from the Pareto Front. Two case studies are conducted, and the equilibrium solution is selected based on quasi-gradient. For the literature case, the Excitation of the equilibrium solution and the total annual cost is reduced by 56.15% and 2.12%, respectively. For the coal-to-methanol system, the utility consumption and Excitation are 29.6% and 264.50% lower than the results of the Aspen Energy Analyzer, respectively.

A novel two-step approach for multi-plant indirect HENs design

Implementing interplant heat integration indirectly via intermediate fluid circuits is a reliable and promising means of enhancing the overall energy efficiency and reducing the carbon emissions of a chemical industrial zone. Although optimization-based sequential and simultaneous synthesis methods have been developed for interplant heat integration, obtaining optimal multi-plant indirect heat exchanger networks (HENs) remains a challenge due to the problem's size and complexity. Under this content, a two-step method is proposed based on the decomposable structural features of the HENs. In the first step, a mathematical model incorporating superstructure representation and pinch location technique is developed to optimize interplant intermediate stream allocation, by which the optimal configuration of intermediate fluids is determined by balancing utility targets and intermediate stream cost with pumps and pipelines. This approach enables multiple HENs synthesis to become independent, and in the second step, a compact MINLP model is proposed for the cost-optimal HEN design in each plant. The effectiveness and advantages of the proposed method are demonstrated by the better results obtained within reasonable computing times for three literature examples, particularly an industrial-scale problem.

Unlocking the potential of synthetic fuel production: Coupled optimization of heat exchanger network and operating parameters of a 1 MW power-to-liquid plant

The use of synthetic fuels is a promising way to reduce emissions significantly. To accelerate cost-effective large-scale synthetic fuel deployment, we optimize a novel 1 MW power-to-liquid (PtL) plant in terms of PtL-efficiency and fuel production costs. For numerous plants, the available waste heat and temperature level depend on the operating point. To optimize efficiency and costs, the choice of the operating point is included in the heat exchanger network synthesis. All nonlinearities are approximated using piecewise linear models and transferred to MILP. Adapting the epsilon constraint method allows us to solve the multi-criteria problem with uniformly distributed solutions on the Pareto front. We improved the lowest production costs of 1.89 €/kg and the highest efficiency of 58.08% from the conventional design process to 1.83 €/kg and 61.33%. By applying the presented method, climate-neutral synthetic fuels can be promoted and emissions can be reduced in the long term.

A novel mass–heat exchange network analogy, regression, and synthesis method for mass exchanger networks

Synthesis of mass exchanger network (MEN) is significant to save the material and reduce the pollution for process industries. Considering its small magnitude and concentration constraints, the optimized configuration of MEN can easily violate the concentration constraints, leading to a reduction in the structural diversity during the optimization process compared to that of a heat exchanger network (HEN) of the same size. Moreover, the constraint on the mass transfer driving force based on the equilibrium composition may also have major effects on the optimization process. To address these issues, this study presents a process–equipment–system analogy between the MEN and the HEN, proposing a novel mass–heat exchange network analogy, regression, and synthesis method. First, the generalized HEN was established by using an analogy considering the MEN based on either the original composition or the equilibrium composition. In this regard, a coordination coefficient was introduced to correct the deviation of the analogy relationship between the heat transfer and the mass transfer processes. Then, the generalized HEN was optimized by employing the random walk algorithm with compulsive evolution (RWCE). A regression method was proposed to regress the optimized HEN solution to the MEN expression, allowing the continuous optimization by using the RWCE with finer parameters. The final optimal solution obtained was found to be lower than those reported in the literature with enhanced structural diversity, demonstrating the effectiveness of the presented method and providing new ideas for further synchronous optimization of combined heat and mass exchanger networks.

Retrofit heat exchanger network optimization via graph-theoretical approach: Pinch-bounded N-best solutions allows positional swapping

Retrofit heat exchanger network (HEN) optimization is a fundamentally unique problem which requires the consideration of existing structures, compared to grassroots design problems. The optimization of retrofit HENs is particularly difficult due to the integration of both existing and newly acquired equipment. The re-routing of existing equipment can lead to various network topologies, increasing the complexity of considerations. In this work, we exploit the P-graph framework to solve retrofit HEN problems, guaranteeing to find the topology of optimal solutions within the constrained space of the HEN retrofit problem. The P-graph framework has additional advantages that allows topologically-efficient search space, simplifies additional unit placement, considers unit positional swapping (re-sequencing and re-piping within search constraints), considers stream splitting, and n-best solution visualization. The pinch minimum utility constraint also provides a bound for the maximum number of modifications in the HEN, significantly reducing search space. The proposed P-graph-based approach is demonstrated using a real refinery case study to show its capability in obtaining the topology of the optimal HEN, highlighting the economic and energy benefits. Further extensions to other retrofit process integration problems (e.g. retrofit water network, hydrogen network etc.) will be enabled via the proposed P-graph approach.

Estimating parameters of plate heat exchanger for condensation of steam from mixture with air as a component of heat exchanger network

The condensation of vapours in the presence of non-condensable gas is happening in a number of industries. Its efficient realisation must be considered in optimisation of Heat Exchanger Networks (HENs) to increase efficiency of energy usage. In these processes, Plate Heat Exchanger (PHE) with enhanced heat and mass transfer can be effectively used. The method of preliminary selection of the PHE heat transfer area, plate size and corrugation geometry is proposed for the case of steam condensing from its mixture with air. The method uses the developed earlier one-dimensional mathematical model, modernized for PHE consisting from commercially produced plates. The heat transfer area of PHE is minimised by proper selection of plate sizes and geometrical characteristics of its corrugation. The optimisation variables are the corrugation angle to the main flow direction inside PHE channel, the corrugations depth and the length of plate. The case study illustrates the application of the method in case of utilisation low grade heat from exhaust gases after process of drying by superheated steam. The method is implemented as a computer program which can be included as a Dynamic Link Library module in software for HEN optimisation.

Synthesis of multiperiod heat exchanger networks: n-best networks with variable approach temperature

In industrial processes, the stream parameters of the heat exchanger network (HEN) synthesis problem can vary during different periods. As a result of the change in inlet and outlet temperatures and the flow rates of the streams, the optimal HEN and the optimal heat transfer areas of the heat exchangers can be different in each period. In our previous work, the standard HEN synthesis for minimum utility consumption was extended to consider varying stream parameters, where bypasses at the heat exchangers are used to ensure the exit streams meet the expected outlet temperatures. This requires optimization of the total annualized cost based on the maximal heat transfer areas of the heat exchangers for each period. Minimum approach temperature is applied to ensure that the areas of the heat exchangers stay within reasonable limits in the solution network. Since minimum approach temperature affects both the structure of the HEN and the total annualized cost, its value needs to be determined during the optimization procedure. The current work proposes a procedure for HEN synthesis which determines the best, n-best, or all feasible HENs for all periods considering variable approach temperature. The proposed method extends the P-graph-based HEN synthesis method for determining all feasible networks in all periods. Three case studies are used to demonstrate the application of the proposed method. The case studies show that while the commonly applied minimum approach temperature of 10 °C does indeed gives near-optimal results, some problems need different values, such as 25 °C or 30 °C.

Heat Exchanger Network (HEN) Analysis of The Power Plant Industry Using Aspen Energy Analyzer Software

Heat recovery is considered as the key to improve energy efficiency in the process design. An appropriate heat exchanger network (HEN) design is an effective tool to maximize heat recovery from the process streams and to minimize energy consumption. The objectives of this study were arranging optimum HEN based on the annual cost in the power industry. HEN in the Paiton Steam Power Plant, East Java, Indonesia, was designed using spreadsheet and Aspen Energy Analyzer with Peng-Robinson equation. Pinch analysis was conducted by comparing Tmin (10°C - 19°C) to obtain Maximum Energy Recovery (MER) and Heat Exchanger Area (HEA). The HEN design was optimized using grid diagram. Simulation in this study succeeded to reduce the annual cost the most effectively at ∆Tmin 16°C. This design optimized the process integration and contributed to the capital, operation, and total annual cost reduction of 14.3%. The maximum energy recovery was 286,706 kW and HEA 138.790 m2. This result is a solution for Steam Power Plant as an effort for enhancing energy efficiency and the company competitiveness.

Pinch-Based General Targeting Method for Predicting the Optimal Capital Cost of Heat Exchanger Network

Pinch analysis is vital in optimizing heat exchanger networks (HENs). Targeting methods are used when determining cost effectiveness with pinch analysis. However, the existing targeting methods for the capital cost of HEN are not suitable for wide application scenarios. Therefore, we developed a high-accuracy general capital-cost-targeting method. It is built on a final structure that was evolved from the spaghetti structure of HEN through four loop elimination stages. This structure helps to reduce the prediction deviation of the method. To achieve high adaptability while establishing this method, we considered the different heat exchanger cost categories, different cost laws for one stream pair, and area limitations of heat exchangers that may be encountered in practice. In addition, allowing streams to use individual temperature difference contributions enhances the method’s predictive capacity. The potential defects of the method found in numerical experiments and case studies were corrected with improvement measures. As a result, the accuracy and stability of the targeting method were further enhanced, with absolute target deviations generally within 10% and often within 5%. This study provides a benchmark for the optimal capital cost of HEN, allowing for a better economic effect when applying pinch analysis.

Optimization of Heat Recovery Networks for Energy Savings in Industrial Processes

Among the pillars of decarbonization of the global energy system, energy efficiency plays a key role in reducing energy consumption across end-use (industry, transport and buildings) sectors. In industrial processes, energy efficiency can be improved by exploiting heat recovery via heat exchange between process streams. This paper develops a stage-wise superstructure-based mathematical programming model for the optimization of heat exchanger networks. The model incorporates rigorous formulation to handle process streams with phase change (condensation or evaporation), and is applied to a case study of an ethylene glycol production plant in Taiwan for minimizing utility consumption. The results show a compromise between steam savings and process feasibility, as well as how the model is modified to reflect practical considerations. In the preliminary analysis, with a substantial potential steam saving of 15,476 kW (28%), the solution involves forbidden matches that pose a hazard to the process and cannot be implemented. In the further analysis without process streams that cause forbidden matches, although the space limitation in the plant renders the best solution infeasible, the compromise solution can achieve a considerable steam saving of up to 8448 kW (91%) and is being evaluated by the plant managers and operators.

Cleaning Schedule Optimization of Heat Exchanger Network Using Moving Window Decision-Making Algorithm

A moving window decision-making algorithm is proposed for the cleaning schedule optimization of heat exchanger network system subject to fouling in refinery crude preheat train. This algorithm is designed by incorporating the moving window scheme into a conventional multi-period optimal control problem (OCP) framework and has a distinct feature that it can efficiently handle a complex problem where a long-time horizon is considered. When compared with the conventional multi-period OCP method using fixed time horizon, our algorithm always shows an excellent performance regarding the computational time, still finding a compatible optimal solution. In our moving window decision-making algorithm, it is important to determine the optimal moving window size for the given time horizon as it significantly influences the optimization performance.

Exploring N-best solution space for heat integrated hydrogen regeneration network using sequential graph-theoretic approach

To achieve the ever-stringent sustainable goals, this paper aims to synthesize a heat integrated hydrogen regeneration network (HIHRN) using a graph-theoretic-based sequential method. Firstly, the optimal and near-optimal structures for a hydrogen regeneration networks (HRN) are determined using P-graph model with consideration of both impurity and pressure constraints. These networks are then used as inputs in P-HENS software to generate a list of optimal and near-optimal heat exchanger network (HEN) structures. An eight source and sink problem is used to demonstrate the effectiveness of the proposed method. There are 199,677 feasible HIHRN structures identified, while the 6 near-optimal solutions which are within 0.05% tolerance of the optimal network cost (i.e., less than 33.04 M$/y) are presented together with the top four HEN designs that can offer comparable costs (∼115,500 $/y). In addition, the impacts of pressure swing adsorber (PSA) pressure drop consideration and minimum temperature difference on the optimal design are also presented.

Graphical Prediction of Optimum Pinch Point Value with AEA Software Simulation and Validation Applied in Closed Cycle Gas Power Plant

Studying industries energy saving is very important prospect for many researchers in the last four decades. In this respect, better process heat transfer can be achieved to improve process operating and capital cost. Thereafter, obtaining higher amount of heat recovery, which will help to reach system optimum heat exchanger network design. Application of Pinch analysis (PA) in our current study, was found to be as an effective method towards economic solution and assessment for all system thermal processes. Whereby, minimizing energy losses, and thus, prediction of maximum energy saving. In addition, application of "Aspen Energy Analyzer (AEA)" simulation software assist our effort to optimize Heat Exchanger Network design (HEN), with various application scenario towards best design. This study represents a "Case study" as a Brayton closed cycle gas turbine power plant in Al-khairat district, which is one of a number of sites used to generate electricity for Iraq national grid. However, the plant original design is open cycle. This study, represent an attempt to apply (PA) in system closed cycle model with the same working conditions. The results predicted, on the contrary of open cycle, that using closed cycle (PA) with temperature difference ∆Tmin can be acceptable with several design propositions. The optimum (∆Tmin = 15℃) were evaluated in the closed cycle system pinch analysis, thereby the maximum Qrec. process that minimize the QHmin & QCmin requirement were identified by the software simulation for the best HEN design. These results were found as Qrec. = 318.330 MW, QHmin = 88.607 MW and QCmin =39.564 MW.

Energy saving and pollution reduction through optimal scheduling of cleaning actions in a heat exchanger network

Heat exchanger fouling may impair energy recovery in Heat Exchanger Networks (HENs), thereby increasing the energy intensity of production processes. Fouling growth on the heat-transfer surfaces of the exchangers can be monitored to mitigate its adverse effects, using measurement data that also enable scheduling exchanger cleaning when economically justified. The research builds on the authors’ previous work devoted to different measurement-aided monitoring methods of fouling thermal resistance, where the method based on the least-square approach to measurement data is the preferred one. The aim is to apply the preferred approach to and perform a case study on the optimization of scheduling of cleaning actions on heat exchangers operated in a HEN. The avoided HEN operating cost is employed as an objective function to be maximized by the optimal cleaning schedule that also has to satisfy a set of constraints related to the timing of cleaning actions. The mathematical formulation of the schedule optimization problem is simplified to make solution finding easier. The case study uses historical operation records covering three years of the real-life HEN composed of 26 shell-and-tube heat exchangers working continuously in connection with a Crude Distillation Unit. Having identified historical time characteristics of the thermal resistance of fouling in all the heat exchangers, one can retroactively determine optimal HEN cleaning schedules. The optimization results are discussed, considering their economic aspects and potential for energy saving and pollution reduction.

Optimization of Ethylene Glycol Plant Heat Exchanger Network with Non-Catalytic Hydration Process from Ethylene Oxide

Heat integration is a method to increase energy efficiency in a series of processes by utilizing the energy potential of other process units, so that Maximum Energy Recovery (MER) will be achieved. One way to perform heat integration is through the design of a heat exchanger network (HEN). The HEN design simulation in this study was carried out in an ethylene glycol plant where in the process there is still a lot of wasted and unused heat. After the HEN simulation was applied, it was found that the heating value decreased by 59% from the existing condition, while the cooling value decreased by 79% from the existing condition. This causes the operation cost for utilities to decrease drastically but increase the capital cost due to the addition of 2 heat exchangers.

Globally optimal design of Minimal WHEN systems using enumeration

AbstractThe process synthesis problem referred to as work and heat exchange networks (WHENs) asks to determine the optimal heat exchanger network intertwined with compressors, expanders, and valves, all integrated into one single network, such that streams with certain initial temperature and pressure attain their temperature and pressure targets at minimum cost. This article presents a procedure that obtains the globally optimal solution of Minimal WHEN systems using an enumeration scheme, using only a few subproblems, each one solved using mathematical programming to global optimality. Minimal structures feature one compression/decompression task and one heat exchange task per stream. In addition, we depart from the ideal gas assumption and use a cubic equation of state for stream properties. Finally, the approach allows for the use of turboexpanders. Four examples are presented to show the effectiveness and accuracy of the proposed method.

Enhanced superstructure optimization for heat exchanger network synthesis using deterministic approach

Heat Exchanger Network (HEN) synthesis is primarily formulated as a mixed integer non-linear programming (MINLP) problem based on method of stage-wise superstructure (SWS). Approaches to obtain an optimal HEN configuration can adopt deterministic algorithms. But, as a large scale problem, it is difficult to solve due to the complexities arisen from nonlinearities of SWS. To overcome the model nonlinearities, stochastic algorithms and meta-heuristic approaches have been proposed in the literature to tackle the problem. However, it reaches a near-optimal HEN configuration from a series of stochastic solutions, which are obtained by the execution of many computational procedures with extensive time resource, and a global optimum will not be guaranteed from only randomly generated results. In this paper, an enhanced SWS approach is proposed, in which new temperature and heat duty constraints are updated to reduce the redundant combinations and avoid conflicted calculation of non-isothermal mixing energy balance. The present model is also extended to allow flexible stream splitting for practical applications. Then, a deterministic-based global solver (GAMS/BARON) is applied in solving three case studies. The results show that the proposed approach can provide cost-efficient HEN solutions with lower TAC than using existing stochastic and deterministic algorithms.

Parameters for cost estimation in shell and tube heat exchangers network synthesis: A systematic literature review on 30 years of research

Heat exchangers are essential elements used in a wide range of engineering applications. Heat Exchanger Networks (HEN) synthesis and optimization is an important field in process integration and different objective functionshave been used to calculate the network total annual cost. This paper presents a comprehensive review in terms of the published literature on HEN cost calculations, highlighting papers related to the design and optimization of HEN. The main research in HEN’s parameters for total cost calculation and its contribution to how these costs are formed, through a systematic literature review is presented in the present paper. It can be noteda gap in this field indicating that apart from a few studies published after 2005 and despite the emergence of new studies on changes in HEN cost functions, the use of more traditional cost calculation models still prevails in the current literature. This review also identifies the current challenges regarding this research field through analysis and comparison. Finally, issues related to cost parameters of objective functions concerning HENoptimization are highlighted and scope for future research is discussed.

A novel two surfaces hybrid approach for Multi-period heat exchanger networks synthesis by combination of imperialist competitive algorithm and linear programming method

• A two-surface hybrid approach was introduced for multi-period HENs synthesis. • It was combined linear programming (LP) + imperialist competitive algorithm (ICA). • The ICA is used to find the structural variables on the 1st surface. • The continuous variables are handled with a combined LP and ICA on the 2nd surface. • The relatively linear behavior improved its ability to deal with HENs problems. In this paper, an efficient hybrid approach to deal with multi-period heat exchanger networks (HENs) synthesis, which is inherently formulated as a mixed-integer non-linear programming (MINLP) model, is proposed. In this novel two surfaces approach, the creation and determination of optimal HENs structures are accomplished by an imperialist competitive algorithm (ICA) on the first surface. In each HEN structure, there is a sequence of stages containing the addresses of the exchanger(s). The HENs generated by the ICA are sent to the second surface, where their minimum total annual cost (TAC) is calculated as an overall objective function. This surface works on two levels. For all periods of each HEN, the local optimal solutions are determined based on the maximum energy recovery at the outer level, including an external search loop and a linear programming (LP) model. Based on the outer level results, the ICA is re-used, at the inner level, to find the final minimum TAC of the network. As a result, the MINLP model is transformed into a relatively linear LP + ICA hybrid model, which is easily solvable. The results demonstrate that this approach can sometimes reduce the network TAC even by over 7.2% compared to the literature.