Bi-level heat exchanger network synthesis with evolution method for structure optimization and memetic particle swarm optimization for parameter optimization

Wang, Jinyang; Cui, Guomin; Xiao, Yuan; Luo, Xianglong; Kabelac, Stephan

doi:10.1080/0305215x.2016.1191803

Cited by 22 publications

(1 citation statement)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Reference Units Q hu (kW) Q cu (kW) Area (m 2 ) TAC ($/year) 1 (4SP) Zhu [36] 8 7000 4000 19 690 1 818 031 a Silva et al [23] 8 7260.0 4260.0 1 816 470 a Wang et al [37] Björk and Westerlund [13] 139 083 a Bergamini et al [39] 10 314.5 315.0 1190.3 140 360…”

Section: Case Studymentioning

confidence: 99%

Synthesis of stream‐split heat exchanger networks using non‐structural model considering serial equipment in stream branches and submixing of substreams

Kayange

Cui

et al. 2021

Can J Chem Eng

Self Cite

View full text Add to dashboard Cite

This paper proposes a non‐structural model with stream splits, for heat exchanger network (HEN) synthesis, that allows for submixing of substreams within splits and series connection of exchanger units in a substream. In a submix, one substream totally combines with another non‐isothermally, and by allowing this feature, the designer incurs only piping costs, which are significantly low compared to other HEN costs, and benefits from increased possibility of manipulating substream temperatures. An algorithm employing random walk principles and compulsive evolution is applied for HEN optimization. The method's randomness, which enhances its explorative searching power and efficiency, is an attractive property that matches the proposed model. Four case studies from the literature are solved and annual cost savings of $1800, $7769, and $4771/year are achieved for three of them in comparison with published best solutions, attesting to the effectiveness of the proposed model.

show abstract

Section: Case Studymentioning

confidence: 99%

Synthesis of stream‐split heat exchanger networks using non‐structural model considering serial equipment in stream branches and submixing of substreams

Kayange

Cui

et al. 2021

Can J Chem Eng

Self Cite

View full text Add to dashboard Cite

show abstract

Globally optimal synthesis of heat exchanger networks. Part II: Non‐minimal networks

et al. 2020

View full text Add to dashboard Cite

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.

show abstract

Globally optimal synthesis of heat exchanger networks. Part I: Minimal networks

et al. 2020

View full text Add to dashboard Cite

This article introduces the concept of minimal structure (MSTR) and presents an enumeration algorithm for the synthesis of heat exchanger networks based on MSTR. Minimal Structures refer to a class of heat exchanger networks featuring acyclic heat transfer networks without energy loops. The enumerations used are either exhaustive or smart with a stopping criterion. Without loss of generality we use the isothermal mixing Synheat model, that is, the method applies identically to other superstructures, with likely variations in the optimization models associated to each step. A conjecture is used to state that the algorithm renders solutions that are globally optimal. Literature examples are used to demonstrate the capabilities of the enumeration algorithm. Most of our solutions compare favorably with the best reported ones in literature, with exceptions where the reported solution is not minimal.

show abstract

Bi-level heat exchanger network synthesis with evolution method for structure optimization and memetic particle swarm optimization for parameter optimization

Cited by 22 publications

References 31 publications

Synthesis of stream‐split heat exchanger networks using non‐structural model considering serial equipment in stream branches and submixing of substreams

Synthesis of stream‐split heat exchanger networks using non‐structural model considering serial equipment in stream branches and submixing of substreams

Globally optimal synthesis of heat exchanger networks. Part II: Non‐minimal networks

Globally optimal synthesis of heat exchanger networks. Part I: Minimal networks

Contact Info

Product

Resources

About