In Part I of this work, the synthesis of minimal heat exchanger networks using the isothermal mixing stage‐wise superstructure was presented. In this Part II, an extension of the algorithm presented ...in Part I is made to consider networks that allow multiple solutions regarding heat allocation, that is, they have energy loops where heat loads can be rearranged without changing the overall energy consumption. We extend the strategy of our Part I to use a set of nested loops to enumerate the number of units, the structure of matches, the energy consumption, different values of exchanger minimum approximation temperature (EMAT), and different locations where EMAT is active. All the models used are linear and are aided by capital cost evaluations. As in Part I, we claim global optimality based on our conjectures. Literature examples are solved to show the effectiveness of the algorithm.
•A penalty-free hybrid stochastic-deterministic algorithm framework is proposed for large-scale HENS.•The proposed framework significantly reduces the complexity of HENS and effectively takes ...advantages of the strengths of stochastic and deterministic methods.•A novel HEZV is proposed to expand the potential of the framework for producing HEN populations.•A feasible stream matching principle is developed to prevent the generations of infeasible HENs without the need for penalty terms.
In this work, a penalty-free hybrid stochastic-deterministic algorithm framework is proposed for large-scale heat exchanger networks (HENs) synthesis (HENS), formulated as a computationally-hard mixed-integer nonlinear programming (MINLP) problem. In the outer level, an improved genetic algorithm (GA) is developed to optimize process stream matches represented by integer variables whose values are generated by a unique heat exchanger vector. Unlike previous researches, the improved GA does not rely on any penalty terms, because we propose a feasible stream matching principle to exclude all infeasible process stream matches and only feasible matches are considered in optimization process. In the inner level, a reduced-size MINLP model is solved using deterministic methods to minimize total annualized costs (TACs), which are then used to evaluate the fitness of candidate HENs. Through this way, the proposed framework combines deterministic and stochastic methods to enhance optimization efficiency and global search capability. Illustrative tests on six benchmark cases demonstrate that the framework can efficiently achieve lower-cost solutions compared to deterministic, stochastic, or hybrid methods. The results show a decrease in TAC for all six cases and a reduction in solution time ranging from 11.1% to 97.2%. Importantly, the proposed framework can be extended to solve MINLP problems in other process networks.
Absorptive CO2 Capture (ACC) is widely embraced as a mature technology to mitigate CO2 emission, but it is energy-intensive and expensive to implement on a commercial scale. It is envisaged that ...energy recovery could be achieved during ACC by synthesizing and integrating a complex network of flexible heat exchangers to transfer as much energy as possible from a set of hot flows to cold flows. This review provides information on the progress made in the development of process and non-process integration-based techniques alongside their benefits for effective energy recovery during ACC. An exposition on the integration of flexible Heat Exchanger Networks (HENs), its synthesis methodologies, and developments for improving energy recovery during ACC is presented. Furthermore, this review highlights the current state of knowledge creation in process integration and ACC, as well as its underpinning principles, challenges, and opportunities to provide a summary and important discussion on current practices in process integration-based strategies for energy recovery. Current opinions on the integration of flexible HENs for energy recovery during ACC are highlighted. The review also presents a proposed roadmap for large-scale energy recovery during ACC, and suggestions on the improvement opportunities for future research and development were provided. Finally, this review revealed that the integration of flexible HENs is a promising technique for energy recovery during ACC. This study will be beneficial to researchers exploring cost-effective methods for designing sustainable energy systems for effective energy recovery.
•Emerging techniques for energy recovery during absorptive CO2 capture (ACC) are categorized.•A new perspective for energy recovery during ACC is proposed.•Non-process integration-based techniques are effective but increase process costs.•Integration of flexible heat exchanger networks is a reliable technique for energy recovery during ACC.•A proposed roadmap for large-scale energy recovery during ACC is presented.
•Introducing a simple method to solve HENs synthesis using the GA-MQLP model.•Using GA to find the structural variables.•Using the MQLP, which consists of two inner and outer surfaces, to find the ...optimal values of each HEN's continuous variables.•Finding the local optimal values of variables by combining an LP and a search loop, on the outer surface.•Increasing probability of finding the global optimal of these variables and the OOF on the inner surface by solving a set of linear equations.
In this paper, an efficient as well as reliable approach to deal with heat exchanger networks (HENs) synthesis problems, which is inherently known as a mixed-integer non-linear programming model, is presented. The structural variables as the discrete variables are optimized by a genetic algorithm (GA), whereas continuous variables are handled by a modified quasi-linear programming (MQLP) model. Each HEN is considered as a chromosome consisting of a sequence of genes. Each gene also contains the address of the exchanger(s) in the network. The HENs generated by the GA are sent to the MQLP to calculate their overall objective function (OOF) (i.e. minimum total annual cost (TAC)). The MQLP model includes two inner and outer surfaces. On the outer surface, the local optimal values of the continuous variables are found according to the maximum energy recovery of HEN, while on the inner surface, the globally optimal values of them are found to reach the minimum TAC of HEN. Due to the relatively linear behavior of the proposed method, a comparison of results with references showed that this method can reduce TAC of HENs compared to the studied references by about (0.51% to 2.37%).
Sustainable energy systems are crucial for reducing carbon emissions because renewable energy sources leave a footprint. The petrochemical industry often suffers from inefficient heat exchange ...network (HEN) systems, leading to substantial energy wastage. In the current work, a real case study of the residue hydrogenation process was analyzed to identify potential energy savings. A new method combining Pinch Analysis and Thot–Tcold diagram analysis methods was proposed. This graphical analysis method plots the cold-flow temperature of each heat exchanger unit on the x-axis and the hot-flow temperature on the y-axis. By applying the Thot–Tcold diagram to a practical case of residue hydrogenation in Zhejiang, the existing process energy state was evaluated, and HEN was retrofitted to achieve energy savings and carbon emission reduction. Following optimization, the energy recovery amounted to 202.71 GJ/h with an energy recovery rate of 14.3 %. The proposed method saves approximately 4.058 × 105 GJ/y compared to current operations, resulting in an annual cost saving of approximately $ 2.76 M/y, with an investment payback period of less than 0.36 y. This study offers a solution to the energy challenges of industrial residue hydrogenation by enhancing the economic and environmental sustainability of existing process flows.
•Case data of a real factory's heat exchanger network are studied.•New method combining pinch analysis and Thot–Tcold diagram analysis methods.•Optimized energy-saving retrofit plan for an actual industrial process.•Energy savings of 4.058 × 105 GJ every year using the proposed process.•The payback period is 0.36 y.
•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.
•Dynamic flexible aspect is taken into account in early integration stage.•A sequential iterative algorithm for the problem solution is devised.•Stream matches, heat transfer areas and bypass ...fractions are optimized.•Results indicate considerable cost (−14.95%) and control performances (+61.83%).•Major advantages found for case studies with multiple disturbances.
Flexible synthesis and control which can be both used to reduce the influences of disturbances on heat exchanger networks are often considered as two separate issues assisting network development at different stages. A proper integration of these separate yet connected tasks carries the promise of achieving superior designs. Currently, the study of integration of heat exchanger networks is still towards a sequential procedure consisting of initial flexible synthesis based on steady-state economic calculations followed by a controller. To overcome this challenge, based on the stage-wise superstructure, an optimization framework in this work is presented to address dynamic flexible synthesis and advanced control simultaneously for maximizing performance in face of disturbances. The framework is based on a sequential iterative procedure that decomposes the overall problem into two stages. The first stage is performed by the dynamic flexibility analysis where the design variables are chosen. In the second stage, the optimization variables are adjusted during the discrete time intervals on the realizations of the control actions and the variation ranges of outlet stream temperatures. The sequential iterative is to map the temperature regulations to the network configuration retrofits. The application to two case studies indicates that the proposed framework returns solutions which are considerably better all in terms of dynamic flexibility, economics and control performance than those published in literature. Compared to previous literature studies, the optimized solutions feature a total annual cost reduction up to 14.95%, a decrease in control action up to 48.58% and an increase in control performance up to 61.83%. Moreover, the application to two case studies indicates that allows solving a real-world problem with up to 26 hot streams and 29 cold streams (leading to models with a size of 523 binary variables and 1655 equations).
•A relatively linear hybrid three-level strategy for retrofitting HENs is presented.•A genetic algorithm produces the structures at the first level.•The total annual cost of each structure is ...optimized at the second and third levels.•These levels consist of LP and ILP formulations with external search loops.•This method can reduce the TAC of retrofitted HENs by about 0.5%-20% compared to others.
This paper proposes a three-level straightforward retrofitting approach for heat exchanger networks (HENs) using a genetic algorithm (GA) coupled with linear programming (LP) and integer linear programming (ILP) formulations. At the first level, the GA produces HEN structures. The local total annual cost (TAC) of these HENs is computed at the second level, consisting of LP, ILP, and an external search loop. LP model is formulated based on the minimum utility consumption, whereas ILP determines the minimum investment cost of implementing potential changes to the existing network to turn it into a GA-generated network. The external search loop is also used to handle the stream splitting ratios. Eventually, the final optimal TAC of the retrofitted network is determined by applying a correction procedure at the third level to the second level results. The results demonstrate that this approach could reduce the retrofitted network's TAC by about 0.5%-20% compared to others.
One challenge in accounting for process safety incidents is that accurate modeling is complex, time-intensive, and requires many inputs. Process safety consequence modeling using first principles can ...be complicated. At the same time, setting up experiments is not always practical. This work proposes an artificial neural network (ANN) framework to predict process safety metrics to prevent overpressure during tube rupture scenarios with reasonable accuracy. Specifically, we apply a feed forward neural network to predict heat exchanger safety rating that is proportional to the heat exchanger pressure normalized with respect to the maximum allowable pressure. By training ANN to a set of tube rupture simulation data, we are able to bypasses the need for solving tedious dynamic and non-smooth system of equations. The ANN-based models yield safety rating predictions that comply with API 521 overpressure standards. We further demonstrate how these predictions can be used to perform real-time monitoring for a network of heat exchangers in a plant setting.
•ANN framework introduced for detecting overpressure severity in heat exchangers.•Detailed algorithm serves as basis for consequence modeling predictions.•Single high fidelity and generalized safety rating predictions models were developed.•ANN models successfully bypassed rigorous dynamic overpressure models.•Real-time overpressure monitoring demonstrated for heat exchanger network.
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