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Home > Final reports > Use of PCI in blast furnaces, CCC/116 

Use of PCI in blast furnaces, CCC/116

Author(s): Anne M Carpenter

Price: £180.00

Ref: CCC/116 ISBN: 92-9029-4329 Published Date: 01/10/2006

No. of Tables: 10 No. of Figures: 23 No. of Pages: 66

Increasing steel demand and growing competition from scrap-based mini-mills is forcing blast furnace (BF)-based plants to improve their performance in order to reduce operating costs and, at the same time, increase productivity. One way to achieve this is by injecting pulverised coal directly into the BF. Injection of coal causes a number of changes within the BF, some of which can be detrimental. This report begins by outlining some of the technical issues associated with high pulverised coal injection (PCI) rates. It then discusses the effect of coal quality on the performance of BFs, with the emphasis on the properties of coal that influence its selection. The requirements relating to coke quality have become more stringent at high PCI rates, and this is discussed, along with the quality of iron ore. The pulverisation and injection of coal is examined. With high PCI rates the reliability of the injection system and the equal distribution of coal through the tuyeres are important as any interruption can quickly lead to serious problems. Coal combustion is an important parameter as it affects the amount of coal that can be injected. It produces, along with coke combustion, both heat and reducing gases for the ironmaking process. Coal combustion within the raceway and the consumption of unburnt char outside the raceway are discussed. Finally, the transfer of silicon and sulphur from coal to the hot metal (pig iron), which adversely affects its quality, is described. The report concludes that blending offers advantages in improving the performance of coals. Its importance is likely to increase as injection rates approach the theoretical maximum and will provide furnace operators with the flexibility in coal selection to meet their particular needs. With better prediction and improved understanding of the effect of coal properties and how operating conditions can be optimised, there is the potential to identify suitable, as well as cheaper, coals. This could provide significant cost savings whilst maintaining a high productivity.

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