Two-time scale dynamic closed-loop scheduling for gas supply network with multiple air separation units

Abstract

The gas supply network with multiple air separation units (ASUs) in steel enterprises provides the essential gas products for iron- and steel-making processes. Steel enterprises must make scheduling decisions for their gas supply networks to meet the fast-changing downstream demands. Therefore, the dynamic characteristics of the process must be considered during short-interval production scheduling to ensure more reasonable scheduling decisions. A two-scale dynamic scheduling method is first developed in this paper to consider the process dynamics. In this method, scheduling decisions are made in the slow time scale, and the nonlinear dynamic characteristics are described using a varied time constant dynamic model in the fast time scale. Then, an autoregressive moving average (ARMA) model is established to address the unavoidable model mismatch, which explicitly predicts and integrates future mismatches into the scheduling model. Moreover, a moving horizon closed-loop framework is designed to integrate the state feedback, mismatch modeling, and scheduling decision modification so that scheduling decisions can be modified in real time to avoid potential safety hazards. The results of the industrial application indicate that the proposed method can provide better scheduling decisions in case studies of model mismatch and unknown leakage compared with existing methods.