Optimization of Blast Furnace through Reducing Coke Consumption and CO2 Emission using HSC Software
نویسندگان
1 School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, Tehran, Iran.
2 School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, Tehran, Iran.
3 School of Metallurgy and Materials Engineering, College of Engineering, University of Tehran, Tehran, Iran.
doi
10.22034/ijissi.2021.540469.1210چکیده
In this paper, a comprehensive evaluation of the charged materials, energy consumption and CO2 emissions of blast furnace (BF) is done by relating the operating data from the Esfahan steel company (ESCO) with the established static process models. The mass and energy balance calculations were performed using the HSC software. This model is capable of predicting 16 independent variables of the 150 total variables at the same time. The model was verified by comparing the results with the ESCO BF No. 3 off gas, slag and dust composition and were found in 8% deviation from the operating data. The model indicated that increasing the hot air blast temperature and CH4 injection, reducing coke ash level and slag volume in the product improved the plant productivity. Compared with a convectional BF, the results of optimization showed that the energy consumption, CO2 emission and coke consumption were reduced by 3% (~183 Gj/THM), 16% (~0.56 kg/THM) and 15% (~79.5 kg/THM), respectively. The energy efficiency was calculated at 81.84% and was increased by about 5% in the optimizing conditions.
