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Processes
Special Issues
Energy Integration and Optimization in the Chemical Process Industry
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Energy Integration and Optimization in the Chemical Process Industry

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: closed (10 January 2024) | Viewed by 4666

Special Issue Editors

Dr. Nan Zhang

E-Mail Website
Guest Editor
Department of Chemical Engineering, The University of Manchester, Oxford Rd, Manchester M13 9PL, UK
Interests: refinery molecular management; refinery hydrogen management; heat integration; modelling and optimisation for industrial utility systems; reliability; availability and maintainability
Prof. Dr. Dominic C. Y. Foo

E-Mail Website
Guest Editor
Department of Chemical and Environmental Engineering/Centre of Excellence for Green Technologies, The University of Nottingham Malaysia, Broga Road, Semenyih 43500, Malaysia
Interests: process design, integration and optimisation; waste minimization; carbon emission reduction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The chemical process industry is facing the significant challenge of reducing carbon emissions in a global effort to achieve carbon neutrality. Energy integration and optimization have played a major role in helping the industry to reduce energy consumption and associated carbon emissions in the past. However, as step changes are needed to reduce carbon emissions in the industry, fundamental changes in industrial energy system configuration and associated technologies become necessary, such as the incorporation of renewable energy, electrification of chemical processes, and energy storage. Systematic methods are needed to help the chemical process industry to shift its energy systems from conventional setup toward low-carbon production.

This Special Issue on “Energy Integration and Optimization in the Chemical Process Industry” seeks high-quality works focusing on the latest novel advances for helping the chemical industry significantly reduce carbon emissions through energy integration. Topics include, but are not limited to:

  • Integration of renewable energy sources in the chemical industry;
  • Integration of energy storage facilities in industrial energy systems;
  • Advanced modeling and optimization techniques for energy integration;
  • Modelling and optimization of novel configurations of industrial energy systems;
  • Advances in heat integration and total site analysis.

Dr. Nan Zhang
Prof. Dr. Dominic C. Y. Foo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • energy integration
  • energy system modelling
  • renewable energy
  • heat integration
  • mathematical programming
  • optimization

Published Papers (2 papers)

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Research

22 pages, 3374 KiB  
Article
Intelligent Optimization Design of Distillation Columns Using Surrogate Models Based on GA-BP
by Lixiao Ye, Nan Zhang, Guanghui Li, Dungang Gu, Jiaqi Lu and Yuhang Lou
Processes 2023, 11(8), 2386; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11082386 - 08 Aug 2023
Cited by 2 | Viewed by 3309
Abstract
The design of distillation columns significantly impacts the economy, energy consumption, and environment of chemical processes. However, optimizing the design of distillation columns is a very challenging problem. In order to develop an intelligent technique to obtain the best design solution, improve design [...] Read more.
The design of distillation columns significantly impacts the economy, energy consumption, and environment of chemical processes. However, optimizing the design of distillation columns is a very challenging problem. In order to develop an intelligent technique to obtain the best design solution, improve design efficiency, and minimize reliance on experience in the design process, a design methodology based on the GA-BP model is proposed in this paper. Firstly, a distillation column surrogate model is established using the back propagation neural network technique based on the training data from the rigorous simulation, which covers all possible changes in feed conditions, operating conditions, and design parameters. The essence of this step is to turn the distillation design process from model-driven to data-driven. Secondly, the model takes the minimum TAC as the objective function and performs the optimization search using a Genetic Algorithm to obtain the design solution with the minimum TAC, in which a life-cycle assessment (LCA) model is incorporated to evaluate the obtained optimized design solution from both economic and environmental aspects. Finally, the feasibility of the proposed method is verified with a propylene distillation column as an example. The results show that the method has advantages in convergence speed without sacrificing accuracy and can obtain an improved design solution with reduced cost and environmental impact. Compared with the original design using rigorous simulation, the TAC is reduced by 6.1% and carbon emission by 27.13 kgCO2/t. Full article
(This article belongs to the Special Issue Energy Integration and Optimization in the Chemical Process Industry)
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20 pages, 7905 KiB  
Article
Matrix Non-Structural Model and Its Application in Heat Exchanger Network without Stream Split
by Dinghao Li, Jingde Wang, Wei Sun and Nan Zhang
Processes 2023, 11(6), 1843; https://0-doi-org.brum.beds.ac.uk/10.3390/pr11061843 - 19 Jun 2023
Cited by 1 | Viewed by 624
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Energy Integration and Optimization in the Chemical Process Industry)
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