An optimization model under interval and fuzzy uncertainties for a by-product gas system of an iron and steel plant

The effective utilization of by-product gas is essential for achieving the targets of energy conservation and emission reduction of iron and steel plants in China. The application of deterministic optimization methods may lead to oversimplification and inaccurate estimation of system parameters, and even to system failure. The major contributions made by this study are the development of a gas scheduling optimization model under fuzzy and interval uncertainties and it application to the gas scheduling system of the Baotai steel plant. The integration of type-1 and type-2 fuzzy sets and interval numbers was first used to describe specific model parameters, and the reduced fuzzy chance-constrained programming algorithm and interactive two-step interval algorithm were used for model solution. Compared with practical allocation patterns, it is shown that the proposed model could offer better solutions with more outstanding performance in rapid response to production fluctuations, as well as increases in system revenue.