A data-driven optimization method for petrochemical enterprise planning

Abstract

The invention relates to a data-driven petrochemical enterprise plan optimization method, which can automatically optimize a cutting temperature point by limiting MILP constraint construction of a special sequence set, and solves the problem that the cutting temperature point of an atmospheric and vacuum distillation device cannot be accurately optimized in the prior art. Combining chemical engineering and statistical knowledge, an auxiliary modeling technology based on a data driving modeling mode is constructed. An optimal data combination mode can be automatically obtained by utilizing historical data and laboratory data, and model parameters of a plan optimization machining device are calculated. A problem that in the prior art, data modeling depends on manpower is solved. A blending component interaction coefficient needed by the blending module is automatically updated, planned, and optimized on the basis of a oil blending component library and a oil blending model, and the defect that a linear blending mode is adopted in the prior art is overcome.

Description

technical field [0001] The invention relates to the technical fields of petroleum refining and chemical production, in particular to a data-driven petrochemical enterprise plan optimization method. Background technique [0002] In recent years, as the competition in the petrochemical market has become more and more fierce, facing the new situation of heavy and inferior processing resources, continuous upgrading of product quality and continuous improvement of environmental protection requirements, petrochemical enterprises rely on refining to bring more and more profits. less. The increasingly thin profit margins drive petrochemical companies to improve their planning and operation capabilities. In the past ten years, various optimization techniques have been fully applied in the daily production planning and scheduling of petrochemical enterprises. The existing technology can help enterprises to optimize crude oil suitable for their own processing by establishing accurate...

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Problems solved by technology

[0009] In order to overcome the above disadvantages, the present invention aims to provide a data-driven petrochemical enterprise plan optimization method. The present invention can automatically optimize the cutting temperature point and solve the problem that the prior art cannot accurately optimize the cutting temperature point of the atmospheric and vacuum device. In addition, combined with chemical engineering and statistical knowledge, an auxiliary modeling technology based on data-driven modeling is constructed. The technology of the present invention can use historical data and laboratory data to automatically obtain the best data combination method and calculate the model of the planned optimized processing device. parameter, which solves the dependence of data modeling on labor in the prior art; at the same time, it solves the problem of using the linear harmonic mode in the prior art.

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