Use of process models to estimate CO2 emission reduction for top gas recycle furnace

Rajeev Kumar Sahu¹, Prodip Kumar Sen²

¹Tata Steel R & D, Jamshedpur-831007, India.
²Department of Metallurgical and Materials Engineering,Indian Institute of Technology, Kharagpur-721302, India.

DOI:

https://doi.org/10.7494/cmms.2015.2.0540

Abstract:

The blast furnaces contribute to a major part of the CO2 emissions in an integrated steel plant. A top gas recycle (TGR) furnace, which is essentially a modified blast furnace system, has been suggested by ULCOS for consideration of reduction of CO2 emission from a blast furnace type of point source. This furnace is operated with an oxygenated blast and the top gas is passed through vacuum pressure swing adsorption (VPSA) unit to reject the major amount of CO2 and the CO-rich gas is recycled back either through tuyere or, both tuyere and shaft. The predictions made pertain to assumed burden specifications which have been the subject of a recent publication. These describe how attainable carbon rates and CO2 emission can be predicted subject to constraints of Raceway Adiabatic Flame temperature and thermal reserve zone temperature. In this paper, an attempt has been made to construct Pareto Fronts for minimizing carbon rate and net CO2 emissions at given coal rate injection and recycle gas circulation through tuyeres only. The data was categorized by the net downstream energy available. The optimal carbon rates show a variation and need to be governed by choice of input operating conditions of the blast, recycle gas volume and temperature by the plant. It is brought out that when the available downstream energy is to be maximized, it may not be possible to attain the lowest CO2 emissions. An identical trend in productivity is also observed. For attaining high values of downstream energy, the productivity shows a decreasing trend with higher CO2 emissions.

Cite as:

Sahu, R., & Sen, P. (2015). Use of process models to estimate CO2 emission reduction for top gas recycle furnace. Computer Methods in Materials Science, 15(2), 322-326. https://doi.org/10.7494/cmms.2015.2.0540

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