Research On Power System Complex Fault Diagnosis Methods Based On Flexible SCADA

The issue of fault diagnosis of power system is a kind of research that based on fault comprehensive information and Knowledge-Based System or model, using kind of diagnosis mechanism to determine fault equipments or reason, at the same time appraising the actions of protecting devices, automatic security devices and other such as automatic monitoring and controlling equipments. At present, the fault diagnosis methods still have some problems in overall situation and in practical. There are three main reasons. First, the information is incomplete. Second, the information noise interference is too large. Third, the robustness of diagnostic is too poor while the information is incomplete. To this end, the paper research about complex fault diagnosis method based on the flexible SCADA in power system. A flexible SCADA system that information can exchange is put forward. In the alarm information processing, intelligent alarm system is developed. After that, Petri nets fault diagnosis model based on forward and backward reasoning is put forward, combining the features Petri nets and expert system. The fault information and diagnostic results is verified by using WAMS information.First of all, the paper did a deep research to complete the information and raised to create the flexible SCADA system based on wide area network, which can classify and upload according to importance of fault information, having initiative and waiting two patterns at the same time, in order to provide a flexible and effective platform of data exchange and functions coordination for fault diagnosis. The flexible SCADA system is no longer a fixed point-to-point one-way path of information exchange, but the network can achieve any two (or more) nodes of information exchange in two-way, which can reflect intelligence of information exchange between master- station and the sub-stations. It is the development and expansion of traditional SCADA, expanding the system's data sources for the fault diagnosis model.Secondly, as there are a lot of noise problems of warning messages after large-area complex fault in power system, information processing and intelligent alarm was studied in this paper. Noises of real-time alarm information are removed from historical database using data mining methods. On this basis, forward and backward reasoning is put forward to have priority classification alarm and reduce the number of alarm information and improve the quality and accuracy of alarm. At the same time, the information after the de-noising will be provided to the fault diagnosis system, so that the accuracy of fault diagnosis is improved.Finally, complex fault diagnosis method based on flexible SCADA is brought forward, as to study the fault diagnosis model for the overall hierarchical information. This method takes full advantage of flexible SCADA interactive features to achieve the stratification of transmission and use for alarm information, which meets the requirement of rapid for simple faults and preciseness for complex faults. As for complex faults, the Petri net forward reasoning model is designed to determine the fault components. When the alarm information is not completely correct, application components protecting configuration of delaying Petri nets is used to correct the error alarm information to improve fault tolerance. Besides that, this paper also made a way to test and verify the correcting alarm information and fault diagnosis using WAMS information. The simulation example proved the effectiveness of the method.