Multi-Objective Optimization of Cost Saving and Emission Reduction in Blast Furnace Ironmaking Process

• Main Authors: Shun Yao, Shengli Wu, Bo Song, Mingyin Kou, Heng Zhou, Kai Gu
• Format: Article
• Language: English
• Published: MDPI AG 2018-11-01
• Series: Metals
• Subjects: blast furnace; cost; CO₂ emissions; solution loss; multi-objective optimization
• Online Access: https://www.mdpi.com/2075-4701/8/12/979

Due to the increasing environmental pressures, one of the most direct and effective way to achieve emission reduction is to reduce the CO₂ emissions of the blast furnace process in the iron and steel industry. Based on the substance conservation and energy conservation of ironmaking process and the engineering method, the carbon loss model was firstly established to calculate the amount of solution loss. Based on this model, the blast furnace emission reduction optimization mathematical model with the cost and CO₂ emissions as objective functions was then established using the multiple-objective optimization method. The optimized results were obtained by using the GRG (Generalized Reduced Gradient) nonlinear solving method. The optimization model was applied to the B# blast furnace of BayiSteel in China. The optimization model was verified by comparing the optimized results with the actual production data. The optimization model was then applied to analyze the effects of coke ratio, coal rate, blast temperature and other factors on the cost, CO₂ emission and solution loss, and some measures to save cost, reduce emissions and reduce solution loss have been proposed.