Research On Oil Blending Optimization

Oil blending is a key step of producing refined oil. Oil blending is utilizing the components from the supervising product units to product petroleum products, and the blending process must content the quality demand and production capacity of refineries and market demand. The blending process involves many components mixing, and the character of mixing is nonlinear. Thus oil blending is a complex nonlinear optimization problem. System analysis of the blending process and modem building of blending and proportioning is very important and worth practical significance.In order to better display accuracy and rapidity of optimization recipe of oil blending, the research of this paper begins with the blending model. Compare the existing blending methods and blending technology. Build a new oil blending proportion model for the problems to deal with the problem of inaccuracy proportion model and the slow solution speed. By analyzing the model, propose a new algorithm that a new linear first GA algorithm. First, find out all the extreme points and direction of polyhedron, these extreme points and direction construct the feasible region of the liner constrains. And then deal with the non-liner constrains with GA algorithm in the feasible region. By optimizing convex combination coefficients to achieve searching all linear feasible region. The simulation results present that the search space and constraints of GA can be reduced greatly through the new algorithm. The ideal blending recipes can be found quickly, and get the maximum profit with a little margin of quality index. The result of simulations certifies that the method in this paper is effective and adaptive widely, it also creates conditions for improving economic benefits of refinery.Finally, this thesis propose the online pipeline oil blending solution by applying near infrared spectral analysis and predictive control methods to realize the recipe online optimization.