Research of methods for design of regression models of oil and gas refinery technological units

International Workshop "Advanced Technologies in Material Science, Mechanical and Automation Engineering – MIP: Engineering – 2019"

材料科学;机械制造;原子能学

Bukhtoyarov, V.V.^1^2 ; Tynchenko, V.S.^1^2 ; Petrovsky, E.A.^1 ; Dokshanin, S.G.^1 ; Kukartsev, V.V.^1^2

Siberian Federal University, Svobodny pr. 79, Krasnoyarsk

660041, Russia^1

Reshetnev Siberian State University of Science and Technology, Krasnoyarsky Rabochy Av. 31, Krasnoyarsk

660037, Russia^2

关键词: Computational model;    Design for control;    Input parameter;    Oil and gas refineries;    Parametric optimization;    Regression model;    Scheduling problem;    Static regression;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/537/4/042078/pdf
DOI  :  10.1088/1757-899X/537/4/042078

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

The problem of efficient computational models design for control and scheduling problems in terms of oil and gas refinery column distillation units is discussed in the paper. Such efficient computational models can be constructed in the form of fast static regression models supplemented with dynamic models of measurement and input channels. The effectiveness of methods for constructing fast static regression models is examined in the paper. The input parameters for such regression models are determined. It is proposed to use parametric optimization methods for such models. A preliminary study showed the possibility of using an evolutionary genetic algorithm. Numerical studies were performed using data from column distillation units. The efficiency of using the methods of additional parametric optimization is shown.