Multi‐stage intelligent operation optimization for a hydrocracking fractionation system with a multi‐fractionator series‐parallel structure. (1st July 2020)

• Record Type: Journal Article
• Authors: Wang, Yalin; Sun, Jiazhou; Sun, Bei; Xue, Yongfei; Shang, Dandan
• Is Part Of: Canadian journal of chemical engineering. Volume 98:Number 11(2020)
• Page Start: 2342
• Page End: 2359
• Publication Date: 2020-07-01
• Subjects: staged evaluation strategy -- state transition algorithm -- time‐consuming optimization; Chemical engineering -- Periodicals; Technology -- Periodicals; 660.05
• DOI: 10.1002/cjce.23766
• Languages: English
• ISSNs: 0008-4034

Abstract

Abstract: A fractionation system is an essential unit in the hydrocracking process. Its optimal operation is challenging because of the complexity in the structure of the distillation tower and composition of the stream. In addition, the series‐parallel structure between the distillation towers of different techniques aggravates the coupling and complexity of the hydrocracking fractionation system (HFS). This, in turn, increases the time complexity of the optimization problem. In this paper, a rigorous mechanism model of an actual HFS is first applied to describe the operating conditions of the HFS. Then, an improved state transition algorithm (STA) with a staged evaluation strategy is proposed to solve the above problem. To overcome problems caused by the series‐parallel structure of HFS, the model is divided into multiple stages for evaluation by mechanism analysis. Furthermore, several typical convergence estimation criteria are introduced to reduce unnecessary model calculations. To solve time‐consuming problems associated with HFS optimization, the adaptive change operator is used to improve the search function of the original algorithm and two performance criteria are presented to reduce the optimization time. The proposed algorithm is successfully applied to the operational parameter optimization problem of HFS with a multi‐fractionator series‐parallel structure. The experimental results indicated that the staged evaluation strategy improved the fast convergence probability of the HFS mechanism model and reduced unnecessary calculations, whereas the improved algorithm increased accuracy and significantly decreased optimization time.