Self-organized Critical Characteristics Analysis Based on Complex Network Theory

Abstract

The distribution of line load rate and the node's inhomogeneity to withstand the transmission of power will have an important impact on the self-organized critical state of the system. For the characteristic of load rate distribution of transmission lines, an improved average semi-variance index is used to characterize changes in the self-organized critical state of the power system. Simulation calculations show that under the same nodal power flow distribution, the larger the value of the average semi-variance, the higher the probability of a large-scale power outage. The curve of probability distribution of blackouts obtained by simulation shows that with the increase of variance value, the tail gradually rises, and the system tends to evolve in the self-organized critical state. The improvement of the average semi-variance index has a good identification effect on the system state after the cascading failure.