Modeling And Simulation Of Distribution Network Fault Diagnosis Based On Petri Nets

With the advancement of science and technology and the development of the society, the dependency degree of various industries on the power system is increasing, and the scale of the power grid enlarges.The probability of large-scale blackout accident caused by power grid failure increases because of the man-made damage, natural force and other reasons, which leads to the decline of the quality of power supply, the damagement of the electrical equipment and other problems. So a fairly complete fault diagnosis system is urgent to provide reliable technical support in analysis and decision-making for electricians, and to reduce fault extension and ensure high quality and stable power supply.Firstly, the fault diagnosis method based on the sequential color Petri nets is researched under the precondition of the existing research results and the model is improved. The remote backup protection information can be fully utilized by the temporal formula. The fault diagnosis can still continue to work, even if the main protection information is missing. The diagnostic process is achieved with the software MATLAB to find the fault components. The accuracy of results are ideal.Then, by assimilating the and/or tree elements into the color Petri net, the diagnosis model can combine the fault-tolerance and logic-expression ability of the and/or tree with the folding function of color Petri nets, which not only has simple diagnosis process and better managing incomplete information, but also has advantages in small, simple and clear scale. Besides, it can avoid the combination of explosion and has better adaptability and applicability.At last, the interface of fault diagnosis is designed and achieved with MATLAB GUI, and the results are illustrated by examples. Through the MATLAB GUI,topology diagram of power system and fault diagnosis system are integrated together.It can display the connection between the various components of the power system and allow users to see the fault information clearly and diagnosis results. In addition,it is convenient to operate and analyze and enhance person-machine interactions.