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Abstract
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.
Highlights
Global anthropogenic CO2 emissions grew by 1.4% in 2017, reaching a historic high of32.5 gigatonnes (Gt), a resumption of growth after three years of global emissions remaining flat [1]
Based on the carbon loss calculation model, the blast furnace emission reduction optimization mathematical model is established by using the multiple-objective optimization method
This optimization model is used to seek the optimal solution of the model in order to obtain the best burden structure, operation parameters and product quality parameters. This optimization model is used to investigate the effects of main operation parameters on the cost, CO2 emission and carbon loss of B# blast furnace in Bayisteel, which provides a theoretical basis for the stable operation of blast furnace, emission reduction and cost savings
Summary
Global anthropogenic CO2 emissions grew by 1.4% in 2017, reaching a historic high of. Based on the carbon loss calculation model, the blast furnace emission reduction optimization mathematical model is established by using the multiple-objective optimization method This optimization model is used to seek the optimal solution of the model in order to obtain the best burden structure, operation parameters and product quality parameters. This optimization model is used to investigate the effects of main operation parameters on the cost, CO2 emission and carbon loss of B# blast furnace in Bayisteel, which provides a theoretical basis for the stable operation of blast furnace, emission reduction and cost savings
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