Optimal heat exchanger network synthesis by sequential splitting of process streams

Ziyatdinov, N. N.; Emelyanov, I.I.; Chen, Qi; Grossmann, Ignacio E.

doi:10.1016/j.compchemeng.2020.107042

Cited by 16 publications

(5 citation statements)

References 20 publications

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“…In this case, we solve Example 8SP.1 introduced by Ziyatdinov et al . Data are given in the Supporting Information.…”

Section: Resultsmentioning

confidence: 99%

“…By adding new variables and using a partitioning methodology to linearize bilinear terms, a convexified MINLP model is obtained to provide lower bounds to the original problem. Ziyatdinov et al introduced an iterative sequential method for the optimal synthesis of HENs based on an assignment problem that considers the splitting of hot and cold process streams and uses decomposition to fix the split fractions for process streams at each subproblem. Chang et al present an enumeration algorithm for the synthesis of a class of HENs with minimal structures, i.e., acyclic networks without energy loops.…”

Section: Previous Workmentioning

confidence: 99%

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Novel Mathematical Approaches for the Structural Synthesis of Heat Exchanger Networks

Cerdá

Cafaro

2022

Ind. Eng. Chem. Res.

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This work presents new systematic approaches for the synthesis of heat exchanger networks (HENs) relying on efficient optimization models. The basic idea consists of partitioning the process streams into a set of nonoverlapping substreams with variable temperatures ranges and exchanging heat among such hot and cold substreams. The problem objective is to synthesize the configuration of the HEN featuring either minimum utility usage or minimum total cost, even if stream splitting is required. First, a mixed-integer linear programming (MILP) model is introduced to systematically find the detailed structure of HENs reaching the minimum utility usage (MUU) target with the minimum number of units. Isothermal mixing of the stream branches is assumed, and a fixed minimum approach temperature (ΔT min ) is arbitrarily chosen. The model is then generalized to minimize the HEN total cost, including the capital cost, by considering the minimum approach temperature as a new problem variable. As a result, nonlinearities arise in the objective function, leading to a mixed-integer nonlinear (MINLP) formulation. The MINLP also includes nonlinear constraints when nonisothermal mixing is allowed. Both simultaneous approaches have been validated by efficiently solving 45 benchmark examples from the literature. Compared to previous contributions, savings of up to 37% in the total costs have been achieved.

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“…In this case, we solve Example 8SP.1 introduced by Ziyatdinov et al . Data are given in the Supporting Information.…”

Section: Resultsmentioning

confidence: 99%

Section: Previous Workmentioning

confidence: 99%

Novel Mathematical Approaches for the Structural Synthesis of Heat Exchanger Networks

Cerdá

Cafaro

2022

Ind. Eng. Chem. Res.

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“…Recent works on HEN synthesis using mathematical programming have improved the quality of solutions [5][6][7][8] and considered retrofits [9,10], multiple plants [11][12][13] and multiperiod operations [14,15]. Huang and Karimi [5] proposed a multistage, matchcentric superstructure and a stage-less, exchanger-centric superstructure for HEN synthesis; the corresponding mixed integer nonlinear programming (MINLP) models consider a wider range of network configurations and allow solutions with lower total annualized costs (TACs) to be obtained.…”

Section: Introductionmentioning

confidence: 99%

“…Beck and Hofmann [6] proposed the use of convex linear approximations to reformulate the original MINLP problem for HEN synthesis into a mixed integer linear programming (MILP) problem. Ziyatdinov et al [7] introduced an iterative sequential method for optimal HEN synthesis. Liu et al [8] presented an extended stage-wise superstructure with intermediate placement of utilities; the resulting complex mathematical model was solved using a genetic algorithm-based solution approach.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Heat Recovery Networks for Energy Savings in Industrial Processes

Lee

Chen

2023

Processes

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

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“…Numerous design technologies and methods have been developed with extensive application to industrial practice, as stated in review articles 1,2 and research publications, 3,4 to name a few. Of all the previous works on HEN synthesis, the approach that gains dominance is the one where a superstructure is proposed together with the formulation of a mixed‐integer nonlinear model (MINLM), which can be solved using mixed‐integer nonlinear programming (MINLP) procedures, 5,6 many times using decompositions, 7,8 or stochastic‐based methods (metaheuristics‐based methods), such as genetic algorithms, 9,10 simulated algorithms, 11,12 particle swarm optimization, 13,14 hybridization between different algorithms, 15,16 etc. We do not elaborate further on the literature review of the stochastic‐based methods, which cannot guarantee optimality, much less global optimality, and in general need specialized parameter tuning for a good computational performance.…”

Section: Introductionmentioning

confidence: 99%

Globally optimal synthesis of heat exchanger networks. Part III: Non‐isothermal mixing in minimal and non‐minimal networks

et al. 2021

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In this work, the enumeration algorithms presented in Parts I and II for the globally optimal synthesis of minimal and non‐minimal heat exchanger networks are extended to consider non‐isothermal mixing. New mathematical models, including non‐isothermal mixing constraints, are proposed to target the bounds of energy consumption and the binding exchanger minimum approximation temperature. These models are solved using the algorithms, which involve solving systems of equations instead of mathematical programming. Three global optimization strategies are proposed to optimize each enumerated structure, involving the use of a global solver directly, or the use of a Golden Search based on energy consumption and a flowrate optimization model considering non‐isothermal mixing. The flowrate optimization model is reformulated as a convex problem, which is solved by using nonlinear programming or a mathematical programming‐free methodology, that is, solving Karush–Kuhn–Tucker equations. A new Global Optimum Search Algorithm is developed and examples are tested comparing different optimization strategies.

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Optimal heat exchanger network synthesis by sequential splitting of process streams

Cited by 16 publications

References 20 publications

Novel Mathematical Approaches for the Structural Synthesis of Heat Exchanger Networks

Novel Mathematical Approaches for the Structural Synthesis of Heat Exchanger Networks

Optimization of Heat Recovery Networks for Energy Savings in Industrial Processes

Globally optimal synthesis of heat exchanger networks. Part III: Non‐isothermal mixing in minimal and non‐minimal networks

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