Petri Net-Based Modeling And Simulation Of Oil Refining Process

Due to the hybrid nature of the oil refining process, the existing classical algorithms used for discrete system and continuous systems are not applicable to practical short-term planning and scheduling in refinery. In scheduling a refinery, it needs to meet many complex constraints. Thus, feasibility is the essential requirement in short-term scheduling for refinery. It is the complex constraints that when a schedule is generated it is often infeasible because some of the constraints may be violated. Therefore a "heuristic+simulation+optimization" may be an effective strategy to overcome the short-term planning and scheduling difficulty.Petri nets are not only an intuitive graphic representation, but also have a solid mathematical background, so it is good at describing and analyzing the asynchronous concurrent system with parallelism, synchronization and resource sharing. In this paper, by using hybrid Petri net as modeling and analysis tool, issues such as modeling and analysis method for crude oil discharge, crude oil transportation, and distillation in distiller in crude oil operations are studied. First, Petri net models for tanks and pipeline are developed. Then, based on the equipment PN models, PN model for the entire system is built to analyze the crude oil operations.Based on the observation above, simulation study for short-term scheduling of crude oil operations has been done. With a typical industrial oil refinery plant as a research case problem, this paper analyzes the properties of oil refining production process in detail, simulation objective is established. With the industrial case problem, a simulation experiment model is implemented by using eM-Plant, in which crude oil unloading, transportation, and feeding for distillation in oil refining process are described and simulated. By means of the simulation for the current refinery production procedure, the feasibility of short-term planning and scheduling can be checked, consequently it can guide the planning and scheduling for optimization.