Design of intelligent scheduling and optimization decision system for multi-source regional crude oil transportation and distribution system

Abstract

How to apply optimization methods, establish intelligent scheduling systems, ensure safe and efficient transportation of crude oil, and achieve maximum economic benefits is the focus of attention for oil companies. In this paper, first, the difficulties of intelligent decision-making in crude oil transportation and distribution systems were analyzed. Second, the intelligent decision-making framework, simulation and deduction techniques, and decision optimization techniques were explained. Third, combined with the objective function and constraint conditions, a crude oil blending optimization model was established. Third, combined with the objective function and constraint conditions, a production profit maximization model was established. Results show that: (a) After 500 iterations, the average similarity was greater than 95 %. Successfully calculated the optimal blending ratio of crude oil under the corresponding conditions for each target crude oil. (b) under the condition that the upper limit of all crude oil purchases is 3850 tons, when the crude oil processing volume of the blending crude oil scheme W1–W2 is 2000 tons and 1850 tons respectively, the enterprise's production profit reaches the maximum of 705,400 RMB. (c) Model validation shows that the system can achieve upstream and downstream collaborative optimization, with strong effectiveness and feasibility.