Component Fault Tracing of Power Dispatching Automation System Based on Information Difference Graph Model

As a complex information physical system, the power dispatching automation system is large in scale and difficult to obtain its logical topology. Once a system component fault occurs, the system will appear an avalanche alarm, making the fault tracing difficult. To solve the problem that the typical fault tracing methods rely heavily on the expert experience and the logical topological relations, this paper proposes a fault tracing method of power dispatching automation system based on the information difference graph model. First, the clustering center of each data feature time series collected is obtained through the K-means algorithm, which is taken as the endpoint dividing the discrete intervals and the interval mean is calculated as the discretization result. Second, the information difference matrix is established according to the information measurement rate before and after the alarm. The matrix elements are composed of the information entropy of the system components and the normalized difference ratio of the transfer entropy between the components respectively. Finally, an information difference graph model is established according to the characteristics with high variation alarm information and the interaction information among them. The state and link relationship of the nodes in the graph model are defined; the mapping table between the nodes with their weights and the fault degree is constructed; the components in the table with the highest fault degree are marked; and the interaction relationship between components in the graph model is traced for the fault source. Experimental results on the simulation dataset, an open source distributed system dataset and actual data of a power grid dispatching system show that this method is feasible and effective. © 2021, Power System Technology Press. All right reserved.