Modeling Method Research On Refinery Process Production Scheduling

As representative of continuous process industry, refinery production enterprises are the mainstay of national economy and act very important role. Production scheduling is the intermediate link of Computer Integrated Processing System and is the core of business operations. Improving quality and efficiency of production scheduling is very important to increase economic and social benefit of refinery companies. So, research on refinery production scheduling has significant meanings.Refinery process not only has large production scale, but also has complex production technology and little cushion, whose logistics operates continuously. There are many salient features of refinery process, such as continuity, stability, and close connection between refining units, etc. Establishing scheduling model is the emphasis of refinery scheduling research, which is also one of the hot topics of combinatorial optimization research. Due to the above features, refinery production scheduling problem presents highly coupling in mathematics, which is hard to describe and solve by traditional mathematic models. By existing scheduling modeling methods, it is difficult to represent the unique natures and heuristic rules of refinery process comprehensively and efficiently. The scheduling models are usually very complex and have strong super structure, poor intuition and weak practical applicability. Due to the current situation of refinery scheduling research, refineries in our nation usually adopt artificial scheduling base on expert experience, which is not only time-consuming and taxing but also hard to guarantee scheduling optimization. So, there have profound academic and realistic meanings to find suitable scheduling modeling methods in view of the unique natures of refinery process based on current scheduling theory and research results. The research and development of such methods is a difficult and hot point in scheduling research area and also is the purpose of our research topic.This paper proposes several new modeling methods and detail models for static and dynamic scheduling of refinery process in view of its features and production scheduling requirements. Based on the proposed methods, a refinery dynamic scheduling system had been developed and utilized in Sinopec Shengli refinery, which had obtained well effects. Detailed research contents and outputs are summarized as follows:(1) In view of the shortcomings of logic-based modeling method on flexible expressing and solving optimality, a heuristic rule-integrated mixed integer programming model is proposed for scheduling optimization problem. Heuristic rules are expressed by logic variables, and their basic logic expressions and corresponding equivalent algebra expressions are presented, by which heuristic rules can be formulated. Combining the algebra expressions with mixed integer programming, integration of heuristic rules is realized. The proposed model can desceibe heuristic rules easily and flexibly to facilitate formulating and simplifying scheduling problem based on mathematical optimization, which can improve solution efficiency and guarantee optimization performance.(2) The refinery static scheduling problem in view of production characteristics is then studied. A heuristic rule-integrated mixed integer programming model is set up based on given definitions of stability, continuity and chronicity as well as their performance criterions which evaluate production characteristics quantitatively. The model describes production characteristics by logic rules of refinery process, and optimizes the trade-off between production profit and characteristic performances. The proposed formulation was used to address scheduling of a certain refinery. Numerical results obtained from the scheduling considering production characteristics whether or not show that schedule of the production characteristic-based scheduling model can improve the performance of production characteristics and is more feasible and practical.(3) Although refinery process mainly runs continuously, but it also has discrete production events such as unit start and stop, scheme switch and equipment failure, so it is a hybrid system in nature. Production events of the system reflect operations of refinery process, which are arranged and handled by scheduling experts to realize production scheduling. Based on the cognition, a prescient event-based modeling method for refinery static scheduling problem is proposed. By defining and describing prescient events of production scheduling, a coupled hybrid automaton is defined, based on which a prescient event-based scheduling model is set up. To realize optimal scheduling, the proposed model is converted to mixed integer programming model equivalently, by which mature optimization algorithms can be utilized conveniently and scheduling optimality is guaranteed. The prescient event-based scheduling model has advantages of intuition, modularization and weak super structure, which provides a new modeling method for refinery static scheduling problem.(4) Based on the prescient event-based modeling method, the scheduling problem considering refinery production characteristics is reformulated, and a prescient event-based scheduling model is set up. The model is easy to build and is more concise in contrast to the heuristic rule-integrated mixed integer programming model. Same schedule was obtained by dealing with refinery scheduling example of the heuristic rule-integrated mixed integer programming scheduling model, which satisfies practical scheduling requirements.(5) To deal with difficulties in satisfying refinery dynamic scheduling requirements of real-time and optimality, an emergency event-based scheduling modeling method is proposed on the grounds of reactive local rescheduling strategy. Emergency event and its event logics are defined, by which expert experience can be chosen flexibly to affect production process. A hierarchical controlled hybrid automaton is given, based on which an emergency event-based refinery dynamic scheduling model is built up. The final dynamic scheduling sub model responding to emergency event can be obtained by a proposed two stage event trigger mechanism, by which dynamic scheduling region can be determined through process simulation. Solving the sub model, dynamic scheme is got. The emergency event-based dynamic scheduling utilizes simulation method, heuristic method and rigorous mathematical optimization effectively, which satisfies scheduling requirements of real-time and optimality. A refinery dynamic scheduling system developed based on the above research had been utilized in Sinopec Shengli refinery and received high praise. Finally, the effectiveness and practicality of the proposed dynamic scheduling model was validated by a realistic scheduling case.