Nonlinear Optimization of Hot Metal Profit in Blast Furnace Based on the Decrease of Coke Consumption Rate Case Study: Esfahan Steel Company

Due to the low quality of domestic coking coal, as well as increased restrictions on international trade of importing coking coal from abroad, Iranian steel industry have been faced with the serious challenges of supplying coke as the major source of blast furnaces energy; on the other hand, the vast sources of domestic natural gas and pulverized coal have made it possible to replace coke with these sources of energy in the blast furnaces. High differences in price of coke with natural gas and pulverized coal, the influence of replacing complexity on the cost of ferrous raw materials, coke, and energy consumption, blast furnace productivity, technical constraints, and carbon dioxide emissions level are the main reasons for conducting this research. In this study, a nonlinear optimization model was developed to determine the profit of hot metal in blast furnace. Compared to previous studies, optimal decision making on the supply and replacement of raw materials and energy, along with new constraints were analyzed. The proposed model was implemented in MATLAB and validated by using data of Esfahan Steel Company. The results revealed that the research model can decrease coke consumption by ۲۶% and is strongly effective in attaining economic benefits.

Keywords:

Blast furnace , energy , nonlinear model , Optimization