Por: Dabin Wang (cisdi), Kun Hu (cisdi), Chunyan Shi (cisdi), Ke Xu (cisdi)
Resumo:
Gas production and consumption prediction and scheduling is the key to gas optimization in iron and steel plants, which is of great significance to improve the stability of gas system and reduce gas flare. Firstly, the characteristics of gas production and consumption are analyzed according to the process characteristics of each iron and steel production process. Based on the results of the analyses, the dynamic characteristics of gas production and consumption in the ironmaking, steelmaking and steel rolling processes are classified. Then, the dynamic prediction of gas consumption is carried out by combining process mechanism and machine learning. Based on the results of gas production and consumption prediction, and taking into account the interaction between gas, steam and power generation, construct a gas optimization scheduling model to improve the overall gas utilization efficiency. The model has also been applied to the production process of iron and steel plants, and the application results show that the model can effectively improve the stability of the gas system and reduce the gas flare.