Matrix Non-Structural Model and Its Application in Heat Exchanger Network without Stream Split

Heat integration by a heat exchanger network (HEN) is an important topic in chemical process system synthesis. From the perspective of optimization, the simultaneous synthesis of HEN belongs to a mixed-integer and nonlinear programming problem. Both the stage-wise superstructure (SWS) model and the...

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Bibliographic Details
Published in:Processes Vol. 11; no. 6; p. 1843
Main Authors: Li, Dinghao, Wang, Jingde, Sun, Wei, Zhang, Nan
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.06.2023
Subjects:
Algorithms
Chemical synthesis
Cost control
Design
Energy consumption
Equipment and supplies
Genetic algorithms
Global optimization
Heat
Heat exchangers
Heat recovery systems
Heat transfer
Heating
Linear programming
Matching
Mathematical programming
Mixed integer
Nonlinear programming
Optimization techniques
Structural models
Superstructures
ISSN:2227-9717, 2227-9717
Online Access:Get full text
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Summary:Heat integration by a heat exchanger network (HEN) is an important topic in chemical process system synthesis. From the perspective of optimization, the simultaneous synthesis of HEN belongs to a mixed-integer and nonlinear programming problem. Both the stage-wise superstructure (SWS) model and the chessboard model are the most widely adopted and belong to structural models, in which a framework is assumed for stream matching, and the global optimal solution outside its feasible domain may be defined by the framework. A node-wise non-structural model (NW-NSM) is proposed to find more universal stream matching options, but it requires a mass of structural variables and extra multiple correction strategies. The aim of this paper is to develop a novel matrix non-structural model (M-NSM) for HEN without stream splits from the perspectives of global optimization methods and superstructure models. In the proposed M-NSM, the heat exchanger position order is quantized by matrix elements at each stream, and a HEN structure is initialized by the random generation of matrix elements. An approach for solving HEN problems based on a matrix real-coded genetic algorithm is employed in this model. The results show that M-NSM provides more flexibility to expand the search region for feasible solutions with higher efficiency than previous models.
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ISSN:2227-9717
2227-9717
DOI:10.3390/pr11061843