Heat Exchanger Network Design Research Articles

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%.

Multi-Objective Optimal Design and Operation of Heat Exchanger Networks with Controllability Consideration

Controllability reflects the ease that a process can be controlled in practical operating environment. However, an unclear influence between the HEN synthesis and the control structure selection has been not investigated for the work of controllability of heat exchanger network (HEN). To address this challenge, this paper proposes a multi-objective optimization method by considering both the quantitative measures of economic and controllability, i.e., minimizing the total annual cost (TAC) and the relative gain array number (RGAn). This method is developed using a HEN synthesis procedure where a model-based superstructure is employed to involve the set of the network configuration alternatives and all the potential control structures. The effects of minimum approach temperature (ΔTmin) on the multi-objective optimization problem are investigated to distinguish the consistent and opposite variations of TAC and RGAn. The consistent change enables us to solve the single objective optimization problem for economical HEN design as well as for taking controllability into account. The opposite change prompts the Pareto front of the two objectives in order to develop a trade-off strategy. Results indicate that this method helps in the determination of the relationship-based nature between network configuration and control structure to yield a HEN design with economic and controllability considerations.

Investigation of process stream systems for targeting energy-capital trade-offs of a heat recovery network

The process industries consume a huge amount of heat energy contributing to environmental impact. Energy recovery is a key instrument of energy-saving that can be implemented via a heat exchanger network. Pinch-based approaches presume analysis of energy targets of industrial processes to find the optimal ΔTmin for heat exchanger network design. Classical Pinch Analysis do not account for the stream splitting in the super targeting procedure while parallel branches are usually needed. The splitters and mixers contribute a lot to the capital cost of the heat exchanger network. Current work proposes the update of super targeting procedure accounting stream splitting and mixing in a Pinch problem. The original algorithm of Composite Curves construction is proposed to analyse the distribution of process streams and stream splitting in subsystems above/below the Pinch before the design of the heat exchanger network. It was then used in a super targeting procedure to precise the capital cost and, as a result, the optimal ΔTmin. The process stream distribution and stream splitting are analysed in a whole range of ΔTmin. Identifying all possible starting points for heat exchanger network design. Two new criteria were proposed to estimate the topological complexity of network pre-design and the specific ratio of stream splitting. The case study analyses the ethylene oxide process and calculation of trade-off between capital and energy costs were performed and optimal ΔTmin = 16 °C. The result was compared with two known approaches, which account for the number of heat exchangers without stream splitting. Total annual costs and optimal ΔTmin was also calculated for different energy prices to show a possible deviation of starting point for heat exchanger network design. The range of optimal ΔTmin from 9 to 54 °C resulted in the range of hot utility prices from 42 to 291 $/kWy, and the emission targets will be from 14,380 to 77,919 tCO2/y. The methodology can be used for the pre-design of the heat exchanger network to better precise the optimal ΔTmin, capital cost targets, and check the optimum changing for different energy prices.

A novel post-combustion CO2 capture design integrated with an Organic Rankine Cycle (ORC)

Fossil fuel-based power plants are the significant sources of CO2 emitted into the atmosphere that significantly affect global warming. While these power plants provide the robustness of the grids, even with the fast development of renewable electricity, utilization of CO2 Capture and Storage (CCS) technologies is one of the best solutions to reduce their emissions and environmental risks. However, one of the most significant drawbacks of these technologies is their highest costs related to their energy consumption as well as the specific requirements of the solvents, which prevalently impact their adaptation. Among these technologies, Post-Combustion CO2 Capture (PCC) processes are widely used in the case of the power plant. This research develops an onshore Aqueous Post-Combustion CO2 Capture (APCC) process with water as a physical solvent to achieve a high CO 2 capture ratio with low energy consumption. The flue gas stream from a power plant flows into APCC, which can capture 72 kton/year of CO2. About 97.4% of CO2 was captured in the process with a 49.5% electricity production to consumption ratio (22.74 MWh/ton CO2) The captured CO2 is then delivered into a CO2 injection well to be used for Enhanced Oil Recovery (EOR) purpose with 15Mpa, 30 °C, and 80 mol% purity. Two scenarios were considered to decrease the external power requirements (1) the electricity production to consumption ratio is increased to 58.2% by adding a Hydro-Pump to the process; (2) coupling an Organic Rankine Cycle (ORC) with R125 working fluid to the process and using sensitivity analysis to gain the best thermodynamic conditions to increase the power production to consumption ratio to 80%. By considering both scenarios, the parasitic power is decreased by 52.78–28.44% and the net power production from the NGCC power plant is increased to 18.604 MW. Finally, Pinch Design Method (PDM) is used to reduce the Operating Cost of the process by the best utility selection from 2.48 M$/year to 0.945 M$/year, and the best Heat Exchanger Network (HEN) design in terms of the lowest Capital Cost at 4.71 M$/year was designed.