期刊
COMPUTERS & CHEMICAL ENGINEERING
卷 170, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2022.108060
关键词
Superstructure; Mixed integer linear programming; Indirect heat recovery; Industrial energy systems; Steam systems
This paper presents a new optimization model for utility systems, taking into account the optimum steam level placement. By improving system efficiency and reducing energy consumption, this approach contributes to moving industrial production towards a more sustainable basis.
Moving industrial production to a more sustainable basis requires a step change in the efficiency of site steam and cogeneration systems, coupled with a switch away from fossil fuels to renewable energy sources. This paper presents the first step in the development of an optimization framework capable of identifying a roadmap to move utility systems to a more sustainable basis. Previous approaches to the design and optimization of steam and cogeneration systems have simplified the problem to the extent that many important practical issues have been neglected, restricting the scope of the options included. The use of grossly simplified models has been prompted by the mathematical difficulties of optimizing such complex energy systems. To overcome limitations in previous work and provide a sound basis for future developments, this paper proposes a new superstructure-based optimization model for the optimization of utility systems, accounting for optimum steam level placement. The latter is important for improving systems efficiency and reducing energy consumption. The optimization problem involves the selection of more realistic operating conditions of the steam mains (superheat conditions and pressure). The model accounts for water preheating, as well as superheating and de-superheating for process steam generation and use. Hot oil circuits are also included as hot utility option to overcome potential steam temperature and/or pressure limitations at high temperatures, and with it provide more flexibility in the framework. The general problem requires making several continuous and discrete decisions, where non-linearities and non-convexities from underlying physics and binary decisions exacerbate the complex nature of the problem, yielding a nonconvex Mixed Integer Non-Linear Programming (MINLP) formulation. However, MINLP formulations can become computationally intractable to solve. Thus, to guarantee tractability and fast conversion, the STYLE model develops a novel successive Mixed Integer Linear Programming formulation. The STYLE methodology is applied to two case studies to illustrate the advantages of the synthesis method and the benefits of optimizing steam levels for the reduction of overall energy consumption at industrial sites. The proposed approach addresses major shortcomings inherent in previous research and provides a foundation for future work to explore the next generation of sustainable utility systems.
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