Power system fault diagnosis and evaluation platform
based on multi-source data fusion

HOU Ren-zheng¹, ZHANG Yan¹, ZHANG Xiao-yi², YUAN Yu-bo²

                                                   (1. School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China; 
                                                  2. Electric Power Research Institute, State Grid Jiangsu Electric Power Corporation, Nanjing 211103, China)

Abstract: Aiming at the fault data and information distributed across different security partitions, the data classification, association and fusion techniques, which meet the security requirements, were proposed. The smart diagnosis technique for transmission and distribution networks based on multi-source data fusion was developed. In the diagnosis for the transmission system, different kinds of factors were fully used to analyze the cause of the fault. The factors include the fault status, electric parameters as well as their temporal features and other external factors like meteorology. In the diagnosis for distribution network, massive data was fully used to develop the evaluation technique of the distribution network based on rule reasoning. The data was obtained from power production management system (PMS), operation management system (OMS) and energy management system (EMS). According to the actual situation of Jiangsu power grid in China, the fault diagnosis platform and the fault-assisted analysis system based on multi-source data fusion was developed. The results indicate that the redundancy information of multi-source data can be used to achieve the smart fault diagnosis more quickly and accurately. In this work, the safe and stable operation level of a power system can be improved.
Key words: power system; fault diagnosis; multi-source data fusion; smart diagnosis