关键词: 沥青产品性质, 预测, 全局资源优化模型, 常减压装置

Abstract:

The global resource optimization model typically uses a mathematical model represented by a linear programming model combined with a quadratic nonlinear module to represent the refining process of a refinery, which can solve the optimization problem of super multi-variable in the whole plant. The model has limited expressive power, and the optimization capability for the production of asphalt products from residue components is relatively poor, making it difficult to accurately execute the measurement plan and achieve optimal global resource calculation. This study proposes a modeling optimization method for asphalt production: using asphalt production data to train a linear regression model to represent the key index properties of asphalt products, and integrating it into the resource optimization model as a quadratic nonlinear constraint, to achieve global optimization. The research results can help enterprises to calculate the best crude oil blending formula to produce qualified asphalt products more accurately, and improve the benefit comparison calculation method for residue components. The modeling optimization method proposed in this study was applied to a certain refining enterprise, and the results show that using the asphalt blending modeling method in this study can further optimize the enterprise's crude oil resource allocation and ensure the quality of asphalt products.

Key words: Asphalt Product Property, Prediction, Global Resource Optimization Model, Atmospheric Distillation Unit