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Two-step MILP/MINLP approach for the synthesis of large-scale HENs
Chemical Engineering Science ( IF 4.7 ) Pub Date : 2019-04-01 , DOI: 10.1016/j.ces.2018.06.036
Andreja Nemet , Adeniyi Jide Isafiade , Jiří Jaromír Klemeš , Zdravko Kravanja

Abstract Although different methodologies for the synthesis of heat exchanger network (HEN) problems have been introduced in the last forty years, there are still significant challenges to be addressed, such as solving large-scale problems. This study focuses on synthesizing large-scale HENs using mathematical programming to achieve near globally optimal solutions based on a two-step MILP/MINLP approach. In the first step a mixed-integer linear programming (MILP) model, TransHEN, is used that obtains a globally optimal solution at selected Δ T min . By utilisation of this model, the most promising matches are selected based on feasibility and viability. The second step entails using the matches selected in the TransHEN of Step 1 in a mixed-integer nonlinear programming (MINLP) model, HENsyn, using a reduced superstructure, to generate a feasible HEN. This study presents also a simultaneous Total Site synthesis with direct heat transfer between processes, and is the first step in the wider project of synthesising an entire Total Site with direct and indirect heat transfer; and is the first step in the wider scope of synthesising an entire Total Site with direct and indirect heat transfer; however, in order to attain this goal, a tool capable of an appropriately handling large number of streams is required. The newly developed procedure has been tested on several case studies, two of which are presented in this paper. For Case study 1 the results obtained lie within the range of best solutions obtained by other authors. Case study 2, consisting of 173 process stream and involving multiple hot utilities, shows the applicability of the developed method to handle large-scale HEN problems.

中文翻译:

用于合成大规模 HEN 的两步 MILP/MINLP 方法

摘要 尽管在过去的四十年中已经引入了不同的换热器网络(HEN)问题综合方法,但仍然存在重大挑战需要解决,例如解决大规模问题。本研究侧重于使用数学规划合成大规模 HEN,以基于两步 MILP/MINLP 方法实现近乎全局的最优解。在第一步中,使用混合整数线性规划 (MILP) 模型 TransHEN 在选定的 Δ T min 处获得全局最优解。通过利用该模型,基于可行性和可行性选择最有希望的匹配。第二步需要在混合整数非线性规划 (MINLP) 模型 HENsyn 中使用步骤 1 的 TransHEN 中选择的匹配,使用简化的上层结构,生成可行的 HEN。该研究还提出了在过程之间进行直接传热的同步全场合成,并且是通过直接和间接传热合成整个全场的更广泛项目的第一步;并且是在更广泛的范围内合成具有直接和间接传热的整个总站点的第一步;然而,为了实现这一目标,需要一种能够适当处理大量流的工具。新开发的程序已经在几个案例研究中进行了测试,本文介绍了其中两个。对于案例研究 1,获得的结果在其他作者获得的最佳解决方案范围内。案例研究 2,由 173 个流程组成并涉及多个热公用事业,
更新日期:2019-04-01
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