Optimal Heat Exchanger Network Research Articles

Different nanofluids as coolant in heat exchanger network: Thermoeconomic modeling and multi-objective optimization

Modeling and optimization of a multi tube heat exchanger (MTHE) network considering the effects of different nanoparticles on the tube side are carried out using Fast and elitist non-dominated sorting genetic algorithm. After thermal modeling in [Formula: see text] method, optimization is performed by increasing the effectiveness and decreasing total annual cost as two objective functions using eight design parameters such as number of MTHE and particles volumetric concentration. In addition, optimization is performed at three various cold mass flow rates and different nanoparticles including Al2O3, CuO and ZrO2 and results are compared with the base fluid (water). For the reliability of the present code, the modeling results are validated with the results obtained from both the numerical and experimental model. The results show that the optimal Pareto front is improved in nanoparticles case, and the rate of improvement in CuO nanoparticles case, especially in higher effectiveness and lower cold mass flow rate is more significant compared with the other studied cases. In addition, because of improvement in the thermal performance of MTHE network with nanoparticles, the heat transfer surface area and consequently the total volume of MTHE network for the fixed values of effectiveness are noticeably reduced. Finally, the effects of design parameters versus effectiveness are demonstrated and discussed.

Multiperiod optimization of heat exchanger networks with integrated thermodynamic cycles and thermal storages

This work proposes a multiperiod synthesis methodology to optimize simultaneously the utility systems, Rankine cycles and Heat Exchanger Networks considering different expected operating modes and off-design operating conditions. Heat exchangers are modeled with different approaches depending on the type of off-design control measure. The problem is formulated as a nonconvex MINLP. Being too challenging for general purpose MINLP solvers, a bilevel decomposition algorithm is specifically developed. One case study consists in designing a flexible Organic Rankine Cycle able to deal with different operating modes, and the returned solution shows a considerable improvement in economics compared to a single-period design. The other two case studies are an Integrated Gasification Combined Cycle able to operate in two different modes, and a flexible Integrated Solar Combined Cycle power plant. Despite the large number of hot/cold streams and technical design/operational constraints, the proposed method can find very good solutions featuring cost-effective designs.

Heat Exchanger Network synthesis considering prohibited and restricted matches

In the industry, there are frequently prohibited and restricted matches in the Heat Exchanger Networks (HENs). These matches could cause risk cost when failures happen. Some matches of streams can be entirely prohibited, but some may only have a certain level of restriction. The margins are set up, based on the risk cost assessment, whether to exchange the heat and by which type of equipment between specific streams. This study proposes a method based on the Advanced Grid Diagram to benefit from an optimised synthesis plan for HEN considering prohibited and restricted matches. A pre-designed HEN could be determined in the synthesis stage, not considering the prohibited or restricted matches. A follow-up topology evolution is performed to trade off the prohibitions and evaluate the restrictions. A Benefit Diagram has been developed to show how many economic benefits can be gained by implementing new heat exchangers. It is used for comparison between allowing all restricted streams and avoiding restricted streams to find the potential risk cost margin. The method is applied to a case study to analyse the restricted and prohibited matches. Optimal HEN design results offer the designers a guide to evaluate to which extent should implement the restricted matches.

A novel sequential synthesis algorithm for the integrated optimization of Rankine cycles and heat exchanger networks

The research theme of this work is the optimization of the heat integration and heat recovery in energy systems and chemical processes, specifically, the optimal synthesis and design of Rankine cycles (e.g., heat recovery cycles, heat pump cycles, etc.) integrated with the heat exchanger network. The challenging synthesis problem is formulated as a Mixed Integer NonLinear Program and tackled with a novel sequential algorithm based on the idea of optimizing the independent mass flow rates of the Rankine cycle superstructure with a derivative-free algorithm. At the lower level, for fixed Rankine cycle and utility mass flow rates, the synthesis of the heat exchanger network is performed with an efficient sequential algorithm. The proposed algorithm is compared against three state-of the-art approaches on six real-world case studies including Organic Rankine cycles, heat pumps/CHP cycles and heat recovery steam cycles with multiple pressure levels. Results indicate that the proposed algorithm finds optimal or near-optimal design solutions for all case studies proving its applicability as an effective design tool.

Plate-fin heat exchanger network modeling, design and optimization – a novel and comprehensive algorithm

PurposeThe purpose of this paper is to present a novel and applied method for optimum designing of plate-finned heat exchanger network. Considering the total annual cost as the objective function, a network of plate-finned heat exchanger is designed and optimized.Design/methodology/approachAccurate evaluation of plate-finned heat exchanger networks depends on different fin types with 10 different geometrical parameters of heat exchangers. In this study, fin numbers are considered as the main decision variables and geometrical parameters of fins are considered as the secondary decision variables. The algorithm applies heat transfer and pressure drop coefficients correction method and differential evolution (DE) algorithm to obtain the optimum results. In this paper, optimization and minimization of the total annual cost of heat exchanger network is considered as the objective function.FindingsIn this study, a novel and applied method for optimum designing of plate-finned heat exchanger network is presented. The comprehensive algorithm is applied into a case study and the results are obtained for both counter-flow and cross-flow plate-finned heat exchangers. The total annual cost and total area of the network with counter-flow heat exchangers were 12.5% and 23.27%, respectively, smaller than the corresponding values of the network with cross-flow heat exchanger.Originality/valueIn this paper, a reliable method is used to design, optimize parameters and the economic optimization of heat exchanger network. Taking into account the importance of plate-finned heat exchangers in industrial applications and the complexity in their geometry, the DE methodology is adopted to obtain an optimal geometric configuration. The total annual cost is chosen as the objective function. Applying this technique to a case study illustrates its capability to accurate design plate-finned heat exchangers to improve the objective function of the heat exchanger network from the economic viewpoint with the design of details.

Economic optimization of heat exchanger networks based on geometric parameters using hybrid genetic-particle swarm algorithm technique

PurposeThe purpose of this study is to provide a method for designing the shell and tube heat exchangers and examine the total annual cost of heat exchanger networks from the economic view based on the careful design of equipment.Design/methodology/approachAccurate evaluation of heat exchanger networks performance depends on detailed models of heat exchangers design. The simulations variables include nine design variables such as flow direction determination of each of the two fluids, number of tubes, number of tube passes, length of tubes, the arrangement of tubes, size and percentage of baffle cut, tube diameter and tube pitch. The optimal designing of the heat exchangers is based on geometrical and hydraulic modeling and using a hybrid genetic particle swarm optimization algorithm (PSO-GA) technique. In this paper, optimization and minimization of the total annual cost of heat exchanger networks are considered as the objective function.FindingsIn this study, a fast and reliable method is used to simulate, optimize design parameters and evaluate heat transfer enhancement. PSO-GA algorithms have been used to minimize the total annual cost, which includes investment costs of heat exchangers and pumps, operating costs (pumping) and energy costs for utilities. Three case studies of four, six and nine streams are selected to demonstrate the accuracy of the method. Reductions of 0.55%, 23.5% and 14.78% are obtained in total annual cost for the selected streams, respectively.Originality/valueIn the present study, a reliable method is used to simulate and optimize design parameters and the economic optimization of the heat exchanger networks. Taking into account the importance of shell and tube heat exchangers in industrial applications and the complexity in their geometry, the PSO-GA methodology is adopted to obtain an optimal geometric configuration. The total annual cost is chosen as the objective function. Applying this technique to case studies demonstrates its ability to accurately design heat exchangers to optimize the objective function of the heat exchanger networks by giving the detail of design.

A simultaneous optimization of a flexible heat exchanger network under uncertain conditions

Heat exchanger networks are important for energy recovery and cost reduction. Flexible networks can handle environmental disturbances, and is more practical for industrial processes than the conventional HEN design with fixed parameters. Previous research on flexible HEN synthesis has mainly applied sequential synthesis, in which the structure determination and area optimization are conducted separately, or other multi-period methods in which only a few extreme operating conditions are selected; however, these methods are not sufficiently accurate for solving nonconvex problems. In this study, a bi-level simultaneous optimization strategy is proposed for the synthesis of flexible HENs under the nominal and all the extreme operating conditions. A binary particle swarm optimization is used in the outer layer to optimize the structural variables, and an Alopex-based evolutionary algorithm is used in the inner layer to determine the heat exchanger areas. Via this method, the result of a convex problem can be directly obtained. Furthermore, to deal with nonconvex problems, a flexibility analysis is conducted to adjust the heat exchanger areas on each critical point. The results of two cases with lower total annual costs than those reported previously are included to demonstrate the efficiency of the proposed method.

Thermoeconomic analysis and multiobjective optimization of tubular heat exchanger network using different shapes of nanoparticles

AbstractIn this study, the effects of different nanoparticle shapes including blades, cylinders, and bricks on the thermoeconomic optimization of tubular heat exchanger (HE) networks have been studied. Boehmite alumina was used as nanoparticle and water as the base fluid. Optimal results were proposed to improve both thermal effectiveness and total annual cost simultaneously by eight design parameters. In addition, optimization was performed for four nanofluid mass flow rates, 0.5, 1, 1.5, and 2 kg/s. The results show that the application of nanoparticles was accompanied by an improvement in the thermal economic parameters of the HE network, and this improvement rate was noticeable in higher values of effectiveness. However, the results indicate a nanofluid optimal mass flow rate of 1.5 kg/s, whereas there was no significant improvement by increasing mass flow rate to 2 kg/s. The optimum results in this paper showed that the best‐studied nanoparticle shape was blade, followed by brick and cylinder shapes. For example, 9.60%, 10.68%, and 11.20% improvements in the effectiveness were obtained in cylindrical, brick, and blade forms at a fixed cost of 3000 $/year, compared with BF. These improvements are 10.40%, 11.25%, and 11.52%, respectively, for the constant value of total annual cost = 4400 $/year.

Design of optimal heat exchanger network with fluctuation probability using break-even analysis

Heat exchanger network (HEN), which is designed to achieve the maximum energy recovery (MER) involves the integration and interactions of multiple process streams. In a plant, the system operation may experience various disturbances such as changes in supply temperature and flowrates. Small disturbances on one stream can affect other connecting streams. To manage these disturbances, the process to process and utility heat exchangers with bypass streams installation are typically overdesigned, leading to higher capital investment. This study presents the cost optimisation of flexible MER HEN design which considers the fluctuation probability using Break-Even Analysis (BEA). Stream data is extracted for the Pinch study and assessment for flexibility and MER was performed. The MER heat exchanger maximum size (MER-HEM) able to handle the most critical supply temperature fluctuations while minimising the utility consumption is calculated. However, the overdesign factor can affect the total annualised cost (TAC) at a certain probability of fluctuation occurrence. Besides that, the fluctuations experienced by the stream can result in the utility increasing or decreasing. Therefore, the MER heat exchanger original size (MER-HEO) is favoured when the fluctuation resulted in the utility cost increasing. The BEA is performed to determine the probability that results in high savings of the TAC and developed an optimal HEN design of MER-HEM or MER-HEO. The break-even point (BEP) from BEA indicate the exact fluctuation probability at which the TAC of MER-HEM and MER-HEO is the same. A case study with fluctuation probability over one-year operation is used to demonstrate the methodology. Application of the proposed methodology on the case study shows that the optimum size of heat exchanger can be determined and the additional savings of TAC can be achieved.

Optimal heat exchanger network synthesis by sequential splitting of process streams

The paper introduces a new iterative sequential method for optimal heat exchanger network synthesis, that relies on an assignment problem. This method considers the splitting of hot and cold process streams, and uses a decomposition that fixes the split fractions for process streams at each subproblem. We apply this method to several heat integration problems to demonstrate its performance and efficiency. It is also compared with stage-wise superstructure optimization using mixed-integer nonlinear programming.

Multiobjective Optimization of Interplant Heat Exchanger Networks Considering Utility Steam Supply and Various Locations of Interplant Steam Generation/Utilization

A multiobjective optimization (MOO) framework considering the dual objectives of the economy and the environment is presented in this work for the extended integration of interplant heat exchanger ...

Optimization of heat exchanger network in the dehydration process using utility pinch analysis

Pinch analysis was applied to optimize the heat exchange network used in the moisture removal processes of energy plants. The moisture removal process absorbs moisture from natural gas using glycol as an absorbent, and the recycling process then separates moisture from the H2O-rich glycol in a regenerator column by applying the principle of vapor-liquid equilibria. For the dehydration process of a natural gas plant, the heat and mass flows are properly established and calculated by means of a static process model for a utility system embedded in the process based on the properties of natural gas. The results of the calculation generate a T-H composite curve that can be used to compare the pinch and to assess the installation and operating costs for the target temperature. The results show that approximately 61% of the total heat supply can be replaced with low-pressure steam, depending on the optimization of the heat exchanger network of the moisture removal process. Further, the annual operating costs can be reduced by about 17% in this case.

Modeling and optimization of inter-plant indirect heat exchanger networks by a difference evolutionary algorithm

Inter-plant indirect heat integration via intermediate fluid circuit is an efficient energy-saving and heat recovery method, but traditional optimization methods, such as sequential synthesis, may not provide the best solutions. This paper addresses a multi-plant indirect heat exchanger network problem using a two-layer simultaneous synthesis method. To reduce the nonlinear constraints in the simultaneous heat exchanger network model, the outer layer uses a differential evolution algorithm to determine the temperatures of the intermediate fluid, while the inner layer uses a deterministic method to obtain the heat capacity flow rate of the intermediate fluid and the heat exchanger network configuration. Optimization was performed to minimize the total annualized cost, as the sum of utility cost, heat exchanger cost, pump cost, and pipe cost. The differential evolution algorithm in the outer layer improved the simultaneous synthesis efficiency in the inner MINLP model and also provided better results in the case studies.

Non-structural model for heat exchanger network synthesis allowing for stream splitting

For more than three decades, heat exchanger network (HEN) synthesis has been primarily addressed by defining initial structures that embed different design alternatives, and near optimal HEN configurations are extracted from these structures during the optimization process. However, such initial structures are prone to missing necessary design alternatives and may require simplifying assumptions to ease the computational burden of optimization algorithms. This paper presents a non-structural model (NSM) for synthesis of HEN considering stream splitting and non-isothermal merging of branch streams. The model exhibits randomness in stream matching, generation and elimination by which potential matches are realized. Random walk algorithm with compulsive evolution is used for optimization of both integer variables (number of heat units) and continuous variables (heat duties and split fractions). The effectiveness of the approach is tested for small- and medium-size literature cases. The method demonstrates results comparable to or better than those reported in literature.

Enhancing strategy promoted by large step length for the structure optimization of heat exchanger networks

Random Walk algorithm with Compulsive Evolution can simultaneously optimize the continuous (heat load) and integer (structure) variables in heat exchanger networks, by giving a random step length to heat load and setting the minimum heat load. Meanwhile, the structural mutation is allowed, as imperfect solutions may be accepted, in the low probability event that it may avoid entrapment in the local optima. Consequently, the step length influences the efficiency of both continuous and integer variables optimization significantly. Specifically, this study observes the distribution of step length during the evolution process, while analyzing its effects on the structural mutation and optimization. The observation found that a sufficiently large step length can stimulate structure optimization and enhance the efficiency of escaping local optima. On this basis, the study proposes an enhancing strategy promoted by large step length to establish a rational distribution curve of step length during the evolution while also advance the structure optimization of heat exchanger networks. Finally, the analysis of four different cases verifies the validity of the presented enhancing strategy, showing that the proposed approach promoted by large step length facilitates the structure optimization and achieves more cost-effective results, compared to other existing strategies.

Heat integration of energy system using an integrated node-wise non-structural model with uniform distribution strategy

The present paper proposes an original node-wise non-structural model (NW-NSM) with no stream splits for the heat integration of energy system. Global optimization approaches using structural models such as the stage-wise superstructure model, have limitations for heat exchanger network synthesis. Instead of complying with the typical fixed multi-stage network frameworks of stage-wise superstructures, the new model generates stream matches by randomly connecting preset nodes in the hot and cold streams. Then, the NW-NSM is optimized using the random walk algorithm with compulsive evolution. Furthermore, the effects of nodes on the solution space and performance of the NW-NSM are analyzed. Finally, a uniform distribution strategy for node locations of existing heat exchangers is used to expand the solution space and to ensure the generation of all possible stream matches. The combination of a flexible model and stochastic algorithm improves the global optimization. The model was applied to medium and large-scale case studies to verify the feasibility and high efficiency of the NW-NSM with respect to the global optimization of heat exchanger networks. The model achieved more economical results compared to other models previously presented in the literature.

Synthesis and simultaneous MINLP optimization of heat exchanger network, steam Rankine cycle, and organic Rankine cycle

Process plants are typically energy intensive plants and pollutant emission contributors. Energy integration in process plants effectively reduces energy consumption and pollutant emission. In a traditional energy integration concept, a heat exchanger network (HEN) is typically constructed for heat recovery between process streams. However, a large amount of medium-to-low-temperature surplus heat usually occurs in hot streams, where further internal heat integration is impossible, and is inevitably cooled by external cold source. Integrating organic Rankine cycle (ORC) into the process HEN is an effect way in further enhancing the energy recovery. However, the HEN, utility plant, and ORC are traditionally designed and optimized separately or sequentially, resulting in local energy integration or optimization. In the present study, ORC is integrated into a HEN to generate power energy from surplus heat. An improved superstructure is constructed and a mixed integer non-linear programming model is developed for the synthesis and simultaneous optimization of the integration system containing process-process HEN, hot utility-cold stream HEN, process hot stream-ORC HEN, steam utility plant, and cold utility plant. Two case studies of different scale in complexity are elaborated to validate the proposed methodology. Sensitivity analysis of carbon tax and fuel price are finally conducted.

A Simple Method for Finding Optimal Paths of Hot and Cold Streams inside Shell and Tube Heat Exchangers to Reduce Pumping Cost in Heat Exchanger Network Problems

In this paper, a simple method is presented for the synthesis and retrofit of heat exchanger networks (HENs) by considering pressure drop as well as finding proper path of streams inside heat exchangers (HEs) to reduce the pumping cost of network. Generally, HEN problems lead to MINLP models which have convergence difficulties due to the existence of both continuous and integer variables. In this study, instead of solving these variables simultaneously, a combination of Genetic Algorithm (GA) with Quasi Linear Programming (QLP) and Integer Linear Programming (ILP) was used for solving the problem. GA was used to find optimal HENs structure and streams paths, whereas continuous variables were solved by QLP. For the retrofit of HENs, a modified ILP model was used. Results show that the proposed method has the ability to reduce the cost of annual pumping due to considering optimal paths for streams in the HEs compared to the literature.

Synthesis of Optimal Heat Exchanger Networks with Quantified Uncertainties and Non-isothermal Mixing

The primary objective of this study is to develop a simultaneous approach for the synthesis of flexible heat exchanger networks (HENs) with non-isothermal mixing assumptions. The HENs synthesis procedure presented in this study took into consideration quantified uncertainties in inlet temperatures and flow rates with an unpredictable time of shift. The proposed multi-period MINLP model was used to generate a HEN with optimized heat exchanger areas and total annualized costs attributed to utility duties. A framework for generating the flexible HEN over a specified range of variations in flow rates and stream temperature was proposed in this study. The framework was based on a two-stage strategy; a HEN design stage was first performed before the testing stage where the energy-saving potential of the synthesized HEN was established. The effectiveness of the proposed approach was tested for energy minimization using a case study in literature with variation in inlet temperature and flow rate. It was observed that the inclusion of non-isothermal parameters in the non-linear model resulted in a HEN that optimally works under fluctuating conditions without losing stream temperature targets while maintaining economically-optimal energy integration.

Mathematical Programming for Heat Exchanger Network Design with Temperature-Dependent Specific Heat Capacity

Heat Exchanger Network (HEN) optimization by mathematical programming has been developed for half of century. Stage-wise superstructure by Yee and Grossmann (1990) is one of the most popular HEN design models dividing process temperature into stages under assumption of constant specific heat capacity (Cp). To make model more realistic, the model is developed under temperature-dependent Cp which is a cubic equation of temperature. To simplify this circumstance, non-linearity of Cp is linearized by applying partitions of linear equations of Cp at different temperature intervals. HEN from the modified stage-wise superstructure model with variable Cp by GAMS software version 24.2 is validated with crude preheat train case from commercial simulation program (Pro/II software version 9.1). The Cp from Pro/II software as a function of temperature is divided into three linear equations of Cp at three temperature intervals. A case study of crude preheat train without HEN consists of five hot product streams and one cold crude oil stream, consuming hot and cold utilities of 175,353.53 kW and 107,945.89 kW, respectively. The new model synthesizes HEN for the crude preheat train, consuming less hot and cold utilities of 82,100.93 kW and 14,654.38 kW. The synthesized HEN is validated by Pro/II software, giving duties of hot and cold utilities of 81,835.30 kW and 14,417.20 kW. Percent error of hot and cold utilities of HEN from GAMS model are only 0.31 % and 1.65 %, compared to ones from Pro/II software. Compared to Pro/II results, percent error of process HEN area and utility HEN area from new model are 1.22 % and 2.91 %, respectively. New model with variable Cp assumption gives a good agreement with validated HEN by Pro/II. Compared to examples from other publications, the model shows that it generates HEN design with less TAC and less computational time.