Implementing fuzzy reasoning spiking neural P system for fault diagnosis of power systems

Fault diagnosis of power systems is of great significance in restoring the outage area as soon as possible. In this paper, fuzzy reasoning spiking neural P system (FRSN P system) is implemented for fault diagnosis of power systems for the first time. As a graphical modeling tool, FRSN P system is able to represent fuzzy knowledge and perform fuzzy reasoning well. When the cause-effect relationships between candidate faulted section and protective devices are represented by the FRSN P system, the faulty conclusion can be drawn by means of a simple parallel matrix-based operation. A 14-bus power system is used to demonstrate the effectiveness of the proposed diagnosis method. The simulations show that FRSN P system has notable characteristics of being easy to implement, rapid parallel reasoning, and handling uncertainty.