Heat Exchanger Network Design Research Articles

Thermal management of sodium-oxygen-hydrogen (Na-O-H) thermochemical water splitting for sustainable hydrogen production

Owing to environmental problems caused by the consumption of fossil fuels and the growing global demand for energy, interests in usage of hydrogen as a green energy carrier has grown. In particular, water is considered a prospect source for green hydrogen production. In this paper, a three-step sodium-oxygen-hydrogen (Na–O–H) thermochemical cycle, which is a newly developed cycle that can operate between 400 and 500 °C is implemented. Also, low number of steps, which results in less system complexity and easier system design is another advantage of the Na–O–H thermochemical cycle. In the first step of this study, a basic model of the three-step pure Na–O–H cycle is modeled in order to produce 1 kg/s of hydrogen. Moreover, output data from basic modeling is used for cycle energy management. Then, heat recovery is performed within the cycle streams to reduce the external energy demand and make the Na–O–H cycle more feasible. To achieve this objective, pinch method, which is an effective method for designing and optimizing plants is used. Several heat exchanger network designs have been developed and compared from different aspects. Finally, a design with the least heat requirement among others is selected and optimized based on total annualized cost objective function to introduce the optimum final design exchanger network. As a result of this work, it is found that using the final optimized design, external heating loads accounted for just 5.8% of the total load, while external cooling loads accounted for 19.3% of the total load. This implies that the Na–O–H thermochemical cycle recovered 74.7% of the energy required for heating and cooling of the streams. The implementation of the proposed heat exchanger network design boosts the overall energy efficiency of the Na–O–H thermochemical cycle. Using final heat recover scheme the overall efficiency of the cycle increased from 45.36% to 52.86%, representing an impressive 7.50% improvement. This significant achievement underscores the pivotal role of this study in developing an effective and optimized model for the Na–O–H thermochemical cycle, which holds great promise for future applications.

Development and empirical verification of non-uniformly layout semiconductor liquid cooling garment model based on CFD simulation

Personal cooling garments (PCGs) are important to help human body regulate its own thermal comfort under high temperature environments. This study focuses on the thermal comfort of personal cooling garment in high temperature environments, which is of great significance in the context of current climate warming and frequent extreme high temperature events. Traditional research on cooling garment mainly focuses on improving its cooling performance, but ignores how to improve human thermal comfort by optimizing cooling equipment and garment parameters. This study developed a semiconductor liquid cooling garment (SLCG) that can adjust and help the human body achieve optimal thermal comfort under different environmental conditions. Through computational fluid dynamics (CFD) simulation, this study established a human body model wearing SLCG to analyze the effects of parameters such as external ambient temperature, flow rate, and inlet water temperature on thermal comfort. Different from traditional research, this study proposed a heat exchange network design with non-uniformity layout, this layout accounted for the variations in heat dissipation across different regions of the human body, enabling targeted optimization of the cooling effect. The results show that among the five different pipe spacings, the spacing of 2–3.5 cm can most effectively improve human thermal comfort. Specifically, in an environment of 34 °C, the parameter combination of inlet water temperature of 24 °C and flow rate of 26 kg/h was selected; at 36 °C, the inlet water temperature was 22 °C and the flow rate was 40 kg/h; at 38 °C, the inlet water temperature was 20 °C and the flow rate was 54 kg/h. The accuracy of the newly developed numerical model was evaluated through a series of experiments. Validation efforts involved comparing the model’s numerical results with experimental outcomes derived from human trials. The error between the simulated and experimental temperatures at each inlet and outlet was confined to within 0.2 °C. The error of cooling power is within 8 %, which proves the accuracy of the numerical model and the rationality of SLCG optimal parameters. This study not only proposed a new SLCG design idea, filling the research gap on thermal comfort optimization in the field of cooling garment, but also provided a theoretical basis and practical reference for the future design of cooling garment in different high temperature environments.

A novel optimization framework integrating multiple initialization, automatic topologization and MINLP reduction to accelerate large-scale heat exchanger network synthesis

Ensuring the solution feasibility and achieving an acceptable solution time for the non-deterministic polynomial-time hard (NP-hard) problem of heat exchanger network (HEN) synthesis is still challenging. In this study, we developed a novel optimization framework for efficiently solving large-scale HEN synthesis problems to obtain near global optimal solutions, simultaneously addressing the solution's infeasibility and time. The optimization framework consists of a multiple initial HEN design model (M-INI model), a new distance-based auto structure transformer (A-STR transformer), and a reduced non-linear programming model (R-NLP model). The M-INI model generates various HEN designs based on pinch analysis by varying the minimum approach temperature and the modes of stream splitting and mixing. The A-STR transformer is first proposed to automatically convert various HEN designs into associated superstructure-based topologies as multiple initial starting points for accelerating the solution of the R-NLP model. A strategy for approximating the temperature difference calculation is further applied to reduce the computational loads. Four case studies were conducted using the proposed method to minimize the total annual cost (TAC). The solutions of general cases 1 and 2 are almost equal to the best results in the literature, while the solution time is reduced by 98.7 % and 99.8 %, respectively, which demonstrates the performance of the proposed method. Especially, the method was applied to two practical industrial HEN cases: a large-scale low-grade heat recovery system and a crude distillation unit. The results of large-scale case 3 show that the optimal solution near the global optimal solution only requires 251.7 s. Case 4 includes pre-splitting in scenario A and free splitting in scenario B. Compared to scenario A, the TAC and solution time in scenario B were reduced by 33.9 % and 93.1 %, indicating that the pre-splitting strategy excludes the optimal from the search space. The proposed novel optimization framework demonstrates the efficiency and applicability of handling large-scale HEN synthesis problems. It can also guide engineers in the design of a large-scale HEN with lower costs and effort.

Simultaneous process optimization and heat integration for ethylene-to-ethylene oxide process: A surrogate model-based approach

Since the production process of ethylene to ethylene oxide (EO) is highly energy-intensive, it is necessary to perform a whole process heat integration. However, due to the technical barriers, it is always a challenge to design the heat integration system while optimizing the process parameters by mechanistic models. In response to this issue, this study presented a novel surrogate model-based framework that allows for the seamless integration of process optimization and heat exchanger network (HEN) design. The EO production process is modeled and simulated to provide the essential data for surrogate model training. Considering the inherent complexity of the process and the challenges associated with model training, the whole production process is decomposed into parts and the output parameters relevant to heat integration are included within the surrogate models training by Artificial Neural Network. Building upon these preliminary steps, a flexible optimization framework built upon the Genetic Algorithm, integrating the developed process surrogate model and any HEN synthesis model, is constructed to achieve synchronous optimization. The results show that the obtained process saves 22.93 % utility cost and finally leads to a 2.60 % increase in total profit than the alternative designed by the conventional stepwise method, showing the priority of the proposed method.

A Formulated Method for Streams Splitting in Heat Exchanger Network Design Using Pinch Analysis

Abstract Thermal processes constitute a significant portion of energy consumption in the industrial sector. In this context, pinch analysis has emerged as a powerful method for achieving substantial energy savings. By systematically analyzing process streams and their heat transfer characteristics, pinch analysis enables the identification of heat recovery opportunities, leading to the design of an optimized heat exchanger network that minimizes energy requirements. In this study, a formulated stream splitting method is proposed to design a feasible minimum energy requirement heat exchanger network. This method aims to achieve two main goals. First, it gives a practical formulated method to help the designer when splitting streams and focuses on splitting the streams in such a way that creates sub-streams with the exact enthalpy required to satisfy heat exchanges with a specific number of streams, in order to minimize the need for process-utility heat exchangers whenever possible. Subsequently, the method aims to eliminate exergy destruction caused by temperature differences in the mixer used to recombine the split streams, by ensuring an isothermal mixture of streams, preventing unnecessary energy losses. The design of the heat exchanger network is conducted using the hint software, allowing for a comprehensive and detailed analysis of each step. The results obtained show that the heat exchanger network attained not only achieves the minimum energy consumption but also mitigates exergy destruction and avoids unnecessary process-utility heat exchangers, resulting in enhanced overall system performance.

Total Site Targeting Approach for Heat Recovery at a Paper Factory

The total Site heat integration approach has been used extensively in the industry, including process services and heat exchanger network design integrated with the site service system. This work aims to propose a design for the heat recovery network in the paper factory through Total Site targeting. A procedure that includes the energy analysis and Pinch Analysis methodologies, with the use of Aspen Energy Analyzer is applied. The heat exchanger network design through total site heat integration shows that the rehabilitation of the heat recovery system of the paper machine and boiler blowdown is feasible, with a potential annual saving of 259 t of fuel oil and 116 000 m3 of water, which make it feasible to invest in the factory’s heat recovery system, whose project budget is estimated to recover in a year. Heat exchanger network retrofit design allows to recover 46.2% of the maximum energy recovery.

Combining reinforcement learning with mathematical programming: An approach for optimal design of heat exchanger networks

Heat integration is important for energy saving in the process industry. It is linked to the persistently challenging task of optimal design of heat exchanger networks (HEN). Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem, it is not easy to find solutions of high quality for large scale problems. Reinforcement learning (RL) method which learns strategies through ongoing exploration and exploitation, reveal advantages in such area. However, due to the complexity of the HEN design problem, the RL method for HEN should be dedicated and designed. A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods. An insightful state representation of HEN structure as well as a customized reward function are introduced. A Q-learning algorithm is applied to update the HEN structure using the ϵ-greedy strategy. Better results are obtained from three literature cases of different scales.

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.

A Systematic Heat Recovery Approach for Designing Integrated Heating, Cooling, and Ventilation Systems for Greenhouses

Ventilation heat loss is one of the most important factors contributing to energy performance of greenhouses. This paper suggests a systematic method based on dynamic pinch analysis (PA) to design an integrated heating, cooling, and ventilation system that uses ventilation waste heat in a cost-effective and energy efficient way. A heat recovery system including an air handling unit, borehole thermal storage, and a heat pump is proposed to investigate all heat integration scenarios for an entire year. In the first step, the heat integration scenarios are reduced to a few typical days using a clustering technique. Then, a generic methodology for designing a heat exchanger network (HEN) for a dynamic system, ensuring both direct and indirect heat recovery, is presented and a set of HENs are designed according to the conditions of typical days. Afterwards, the best HEN design is selected among all design alternatives using a techno-economic analysis. The whole procedure is applied to a commercial greenhouse and the best HEN configuration and required equipment sizes are calculated. It is shown that the best-performing design for the greenhouse under study produces primary energy savings of 57%, resulting in the shortest payback period of 9.5 years among all design alternatives.

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.

Cost allocation evaluation of a multi-plant flexible heat exchanger network design based on fuzzy game

A multi-plant heat exchanger network (HEN) can recover waste heat across plant boundaries and reduce utility consumption in industrial parks. Conventional multi-plant heat integration using nominal conditions cannot handle uncertainties from the environment or plant operations that affect stream properties; therefore, a flexible HEN design is more practical. This study is focused on the evaluation of an already designed flexible HEN with a fixed network structure and the provided heat exchanger areas to maintain operability under disturbances. Although the capital cost is determined, utility consumption is uncertain to meet possible target temperatures. Consequently, the total annual cost (TAC) varies and forms a distribution that can give plant operators more information about possible costs as well as extreme parameter values. To provide the TAC distribution, a mathematical model is established to calculate utility costs after inputting different stream parameters into the designed HEN configuration. In addition, an interval Shapley value from the fuzzy game, which considers the contribution of each plant when the decision environment is uncertain, is used to generate a cost allocation interval. For example, the potential costs paid for Plant 1 and Plant 2 in Case study 1 ranged from $18,195.95 to $25,897.80 and $14,778.05 to $19,921.20, respectively. These results demonstrate that the proposed approach can be used to evaluate a provided flexible HEN design before construction.

Synthesis and optimization of energy integrated advanced distillation sequences

This paper explores the basis on which reliable screening of distillation sequences for energy-efficient separation of zeotropic multicomponent mixtures can be carried out. A case study for the separation of natural gas liquids is used to demonstrate the approach. To solve this generic problem, a screening algorithm has been developed using optimization of a superstructure for sequence synthesis using shortcut models, in conjunction with a transportation algorithm for the synthesis of the heat integration arrangement. Different approaches for the inclusion of heat integration are explored and compared. The best few designs from this screening are then evaluated using rigorous simulation. It has been found that separation problems of the type explored can be screened reliably using shortcut distillation models in conjunction with the synthesis of heat exchanger network designs. Non-integrated designs using thermally coupled complex columns show much better performance than the corresponding designs using simple columns. However, once heat integration is included the difference between designs using complex columns and simple columns narrows significantly.

Critique – Comparison between P-HENS and Aspen Energy Analyzer for heat exchanger network synthesis

This critique evaluates the use of the P-HENS software for developing recommended heat exchanger network designs compared to the commercial simulator Aspen Energy Analyzer. The similarities between the two software when carrying out an energy integration are discussed, as well as their advantages and possible improvements to be implemented in the tool.

A heuristic approach to design a cost-effective and low-CO2 emission synthesis in a heat exchanger network with crude oil distillation units

This paper presents a tradeoff grassroots design of cost-effective and low-CO2 emissions heat exchanger networks for crude oil distillation units (CDUs) to address high energy consumption in CDUs. To reduce the impact of the objective's magnitude on the optimization searching direction, a normalization process handling the objectives to the dimensionless indexes to assess the performance of CDU is presented. An originally designed random walk algorithm with compulsive evolution (RWCE) and a special superstructure nodes-based non-structural model (NNM) is adopted for the multi-objective optimization problem. The comparison analysis shows that the proposed model and the heuristic algorithm are robust in solving the global optimization problem. In addition, aiming to investigate the evolution mode of utilities in RWCE, an active evolution strategy of utilities (RWCE-AU) is proposed to promote structural evolution by altering the heat loads of utilities by a certain probability. Finally, several industrial CDU cases are optimized by RWCE and RWCE-AU in this work. The continuous improvement solutions have highlighted that the RWCE could yield a better optimal total annual cost (TAC) compared to the reported initial case. Moreover, the RWCE-AU enhances the searching ability of RWCE and provides a better tradeoff between the economic benefits and the environmental impacts.

Utility targeting in heat exchanger network with parametric uncertainties

For almost a half-decade, the methodology of Pinch Analysis (PA) and heat integration (HI) has been used to optimize the requirements of external utilities. Though much has been done, optimizations under uncertain conditions still need more work, discussion, and practical implementation. In most of the HI problems, it has been observed that variation in the minimum driving force affects the shape of the source and sink profile eventually the heat exchanger network (HEN) design. Due to changing operating conditions, human errors, and sometimes poor maintenance, it has been experienced that the process plants along with their equipment and vessels do not operate at the desired value upon which they are expected to run. The parameters with variations and uncertainties due to disturbances in the process plants need to be addressed for the desired product output. In this work, the concept of PA has been unified with robust optimization (RO) to target the utility requirements in HEN optimization where the uncertainties in the heat capacity flow rate F and supply temperatures Tin of the source streams are considered. The developed nominal forms of mathematical programming are converted into the deterministic robust counterpart equivalents to incorporate the uncertainties whose set of variations is known. RO is an optimization technique where the information of accurate probability distribution needs not be known; rather, it works in a defined set of uncertainty ensuring the feasibility of the solution. Using two examples from the literature, the developed models have been solved and results for the solutions against the range of uncertainties in parameters have been established. The produced data demonstrates, in the case of uncertain inlet temperature the rise in total utilities is 115% and 225% in examples 1 and 2 for worst case is calculated. Plots of budget parameter Γ vs the utility requirement have also been compared with results. Application of this model will further assist the plant engineers/managers in deciding the requirements of hot utilities and cold utilities under the parametric uncertainties as needed.

Optimal Economic–Environmental Design of Heat Exchanger Network in Naphtha Cracking Center Considering Fuel Type and CO2 Emissions

In the petroleum industry, naphtha cracking centers (NCC), which produce ethylene, propylene, propane, and mixed-C4, are known to consume a large amount of energy and release a significant amount of carbon dioxide (CO2). This necessitates economic and environmental assessments with the aim of achieving a reduction in energy use in order to ensure efficiency in terms of cost and environmental impact. Herein, a heat exchanger network (HEN) is considered with the aim of determining its optimal operating strategy. In addition, the trade-off between reduction in utility costs (i.e., profit) and the installation cost of the heat exchanger (i.e., loss) is evaluated in terms of economic efficiency. Finally, an environmental impact assessment is performed with respect to the source of fuel consumed for steam generation. The HEN’s energy consumption in the three configurations analyzed herein was found to be reduced by 3%, 6%, and 8%. When considering variations in the fuel used for steam generation, the changes in the payback period caused differences in the results for the most economical configuration. On the basis of this study, it was possible to design the use of waste heat in the pinch network and the network configuration for the installation of additional heat exchangers in an economically feasible manner, while analyses of various fuel source were used to determine favorable conditions with respect to environmental impact.

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.

Study of Energy Integration in Chlorobenzene Production Process Using Pinch Technology

In this paper, the industrial application of detailed heat integration in the chlorobenzene production plant has been solved by using the Pinch design method. Designing a Heat Exchanger Network (HEN) through pinch analysis is an effective energy integration technology. In addition, minimizing unit and cost, operability and process control are essential parameters for selecting a suitable HEN design. In this research, the HEN of the existing process has been designed and analyzed using HINT software to minimize energy consumption and cost, thereby achieving maximum energy recovery. The analysis shows that the existing plant has been well integrated, and sound energy-saving effects and minimum energy requirements have been observed through the energy integration between processes. The total energy saving has been 91.80 %, while the energy recovery for heating and cooling have been 86.99 % and 96.23 %, respectively. Based on the economic analysis, the total annual cost of the proposed HEN design has been calculated to be 80912.5 $.

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.

Study on the random walk classification algorithm of polyant colony

Abstract With the sustained and healthy development of economy, saving energy and reducing consumption and improving energy utilization rate is a major task that enterprises need to solve. With the complex and large-scale chemical process, the heat exchange network has become complex and diverse. For more and more complex and large-scale industrial heat exchange networks, there are many different kinds of heat exchangers, the flow is complex, so the heat exchange network presents a high degree of complexity, a node status change; its disturbance transfer will influence the stability of other nodes associated with it, because of the system coupling, thus affecting the controllability and reliability of the whole heat exchanger network. Process optimization design of heat exchange network is one of the main methods of energy saving in the industrial field. As a typical simulated evolutionary algorithm in swarm intelligence algorithm, ant colony algorithm combined with random walk classification algorithm, this article proposes an optimized heat transfer network based on multi-ant colony random walk classification algorithm. The heat exchanger was abstracted as a node, and the heat exchanger pipeline was abstracted as a side. According to the maximum geometric multiplicity of the eigenvalue of the adjacency matrix and the linear correlation row vector of the matrix, and combining the importance of the edge of the heat exchange network with the controllable range of the driving edge, the optimal control driving edge of the heat exchange network is identified. The results show that compared with the traditional heat exchanger, the size of the enhanced heat transfer equipment and the influence of pressure drop change. Compared with the results of the size of the heat exchanger strengthening heat transfer equipment and the stepwise optimization of the heat exchange network in this study, the cost of public engineering is reduced by 5.98% and the total cost is reduced by 8.83%.