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

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.