Three-layer design and optimization of CO2 emission reduction in the iron and steel industry based on 'BRL' industrial metabolism

Energy saving and CO2 reduction in the iron and steel industry is a crucial challenge for the realization of the "dual-carbon" goal and sustainable development. Numerous studies have concentrated on optimizing materials, energy, and CO2 emissions, yet there exists a dearth of research on the mechanisms of carbon emissions and comprehensive design and optimization system models. To address this issue, this paper proposes a three-layer design and optimization method for reducing CO2 emissions based on industrial metabolism. First, the concept of "BRL" industrial metabolism is proposed for revealing the mechanism of material-energy metabolism and carbon emission, and novel carbon emission evaluation indexes are proposed. Then, based on the multi-layer structural attributes and multi-objective attributes, a three-layer design and optimization of carbon emissions is constructed: task allocation of plant, material-energy optimization of the process, analysis of carbon emissions. Finally, comparative analysis and optimization solutions are conducted using GA (Genetic Algorithm) and DPGA (Double Population Genetic Algorithm). The results indicate that carbon emissions can be reduced by 205.31 kg/ t crude steel. The carbon emissions generated by the mechanism of material-energy metabolism are deeply analyzed using the "BRL" industrial metabolism. This paper provides a foundation basis for decision-makers to achieve low-carbon task production.