Bad data identification and fault diagnosis of smart substation based on secondary system information redundancy

Abstract

Abstract Secondary system is an important link that affects the reliable operation of power system. However, the current improvement measures for accurate data acquisition and reliable operation in secondary systems are mainly concentrated at the equipment level. The solution at the equipment level not only increases the complexity of the system, but also can only optimize a single link or problem, which is difficult to improve the overall system level. In order to enhance the information accuracy, operation and maintenance precision and operation reliability of smart substation secondary system, this paper proposes bad data identification and fault diagnosis methods based on secondary system information redundancy. Firstly, according to the analysis of secondary information redundancy, this paper constructs the data information redundancy model of the smart substation secondary system. Then the data information state estimation method based on the least square method and the bad data identification method based on the information redundancy are proposed. Finally, case analysis is carried out to verify that the proposed method can effectively increase the information accuracy of smart substation, which also provides new research route and foundations for secondary system fault diagnosis.