Simulation And Operating Optimization Of Atmospheric Distillation Unit

The important feature of modern chemical process is to be large-scaleand intelligent. The chemical process intelligent is the basic conditions and theimportant guarantee of the chemical process's safety, sustainable, high quality,and high efficiency. Owing to the industry process's complexity, materialshortages, and the increasingly fierce market competition, improving theproduct quality, reducing the production cost and strengthening therequirements of environment protection is much more important. Theoptimization of equipment operating conditions gets more and more attention.Atmospheric distillation is the first step of the oil refining processing and playa crucial role in the economic benefit of enterprise.In this paper, by the analysis of the current research status, we do aresearch on simulation and operating optimization of ADU. The main contentsare listed as follows:(1) The article describes some key technologies of the steady state modelof ADU, including characterization, process model and strategy. The steadystate model of ADU is established and the plant data is simulated in theestablished model. The result shows that the simulated data is similar to the plant data and the model is effective.(2) Chen et al.(1998) presents a design of experiment method usingartificial neural network and information analysis(AIDOE). This article isimproving the experimental design algorithm developed by Chen, which touse a supporting vector regression (SVR), instead of artificial neural network.The effectiveness of the proposed procedure (SIDOE) in searching optimal isdemonstrated by a bench-mark problem which is the modified Himmelblaufunction. The result shows that SIDOE is better than AIDOE.(3) We bulit the optimization model of ADU and used SIDOE andAIDOE to search for the best operation conditions of ADU.The result showsthat SIDOE is much better than AIDOE to find the optimal point and theeconomic benefit of ADU could be increased. Significant profit incrementsshow that operational optimization is meaningful and practical for thesimulated atmospheric distillation unit.