A Causal Model-Based Scheduling Approach for Coke Oven Gas System in Steel Industry. Issue 21 (2018)

• Record Type: Journal Article
• Authors: Jin, Feng; Lv, Zheng; Li, Maohua; Mou, Lei; Zhao, Jun; Wang, Wei
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 21(2018)
• Page Start: 7
• Page End: 12
• Publication Date: 2018
• Subjects: Coke oven gas system -- Causal model -- Scheduling; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.09.384
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Reasonable scheduling of coke oven gas (COG) in steel industry will save fossil energy resources and increase gas consumption efficiency. In this study, a causal model-based scheduling approach is proposed to provide guidance for the coke oven gas scheduling. The causal relationship of the variables related to the gas tank level is discovered and the causal diagram is established, according to which the training sample is constructed and the predicting model of gas tank level is trained. Then, an objective function that considers the scheduling solution and its result is designed. To calculate the most reasonable solution, a modified particle swarm optimization algorithm is employed. The validation experiments are carried out by using practical data coming from a steel plant in China, where the gas tank level approaching the higher and the lower level zones are both considered. The human experience-based method and a data-based scheduling one are conducted as comparative studies. The results indicate that the proposed method is efficient for COG scheduling.