Complex System Theory Based Power System Cascading Failure Model And Self-organized Criticality Recognition Method

Large-scale interconnectedness of power system makes its complexity growing daily. While optimizing the layout of resources, it also increases the uncertainty of system operation, and makes cascading blackouts due to a chain reaction triggered by single fault occur frequently. Complex system theory can analyze dynamic characteristics of the interconnected power system from a holistic view, and has become an important way to analyze the mechanism of cascading blackouts. On the basis of complex system theory, this paper established in the research of power system cascading failure model and self-organized criticality recognition, and its mainly contents are as follows:①Corrective control methods of the existing complex network theory based cascading failure model have great differences with real power system. To conquer the limitation, a corrective control method combining power flow tracing based proportional load-shedding and optimal power flow of active power loss least is proposed. The load-shedding area is determined based on transferred loads in islanded subsystem formed after node failure by adopting power flow tracing technique, and the corresponding load is curtailed in the method. Based on complex network theory, a cascading failure model of power system taking into account the corrective control method is proposed. The model could overcome the shortage of existing models that only describe cascading failure in the topology aspect, and reflect the impact of load distribution variation on cascading failure, as well as be more adaptive to the physical background of the actual power network. The results show that the proposed corrective control method can significantly reduce nodes number violates betweenness limits. The scale of a cascading failure can be reduced when load is uniformly distributed and corrective control is implemented. Besides, the scale of a cascading failure doesn’t decrease strictly as threshold of node increase. Therefore, rely solely on improving threshold of node can’t reduce cascading failure scale strictly.②After self-organized criticality described in detail, it is pointed out that In addition to the inhomogeneity of load rate distribution of transmission lines, power transmission mission of nodes also have great influence upon power system self-organized criticality. On the aspect of inhomogeneity of load rate distribution, weighted semi-variance is proposed to recognize power system self-organized criticality for the failings of power flow entropy and weighted power flow entropy, which may have the same value in different load rate distributions and can’t reflect importance and operation state of each line to power system self-organized criticality. On the aspect of inhomogeneity of power transmission mission of nodes, because power transmission mission undertaken by a few nodes heavy will lead to self-organized criticality and make power flow betweenness of node present feature power law, distribution of power flow betweenness of node is proposed to described this inhomogeneity and recognize power system self-organized criticality. Hidden failure model based on self-organized criticality is used to simulate cascading failure of standard system and the effectiveness of the proposed index is validated.