Multi-objective optimization scheduling model of oxygen system in steel enterprises

Jun Fu; Longhui Mo

doi:10.1117/12.3024541

13 May 2024 Multi-objective optimization scheduling model of oxygen system in steel enterprises

Jun Fu, Longhui Mo

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 1315928 (2024) https://doi.org/10.1117/12.3024541
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

Abstract

With the development of industrial production, product demands are gradually changing from simple static demands to complex dynamic demands. The steel industry is a high-energy-consuming industry, which is usually accompanied by intensive energy consumption and emissions. Gas systems are an indispensable component of the steel industry, and almost all steel enterprises are equipped with gas systems to meet the demand for gases in the steel production process. In the gas supply and demand system, if the supply of gas is imbalanced with the consumption, it will cause the phenomenon of gas leakage or even device alarms, thereby affecting the normal production of the steel industry and causing a waste of resources. Therefore, enterprises urgently need to reasonably arrange equipment operations through scheduling and timely response to demand changes with the goal of cost reduction and efficiency improvement, to reduce leakage while reducing production energy consumption and improving economic benefits. In order to facilitate modeling and calculation, this paper ignores the nitrogen and argon parts and only considers the oxygen gas system. This paper takes the actual industrial air separation unit as an example to instantiate the scheduling model and establishes a nonlinear optimization problem of multi-product joint scheduling with minimum oxygen leakage amount and maximum economic benefits as the goal. By comparing the artificial scheduling results with the optimization problem-solving results, the feasibility of the decision is verified. This model can provide a theoretical reference for the optimization problem of multi-gas system scheduling in steel enterprises.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jun Fu and Longhui Mo "Multi-objective optimization scheduling model of oxygen system in steel enterprises", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 1315928 (13 May 2024); https://doi.org/10.1117/12.3024541

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KEYWORDS

Oxygen

Liquids

Power consumption

Mathematical optimization

Systems modeling

Industry

Genetic algorithms

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