A New Method to Improve Fault Location Accuracy in Transmission Line Based on Fuzzy Multi-Sensor Data Fusion

作者：Jiao, Zaibin^*; Wu, Rundong

来源：IEEE Transactions on Smart Grid, 2019, 10(4): 4211-4220.

DOI：10.1109/TSG.2018.2853678

• Data fusion
• distance relays
• fault location
• fuzzy inference systems
• weighted covariance fusion

Fast and accurate fault location in transmission lines has great significance for power system stability and power supply reliability. The location results of the various algorithms are diverse. The conflicting results influence the operator's analysis on fault-based quick restoration of power systems. This paper proposes a new method to improve fault location accuracy in transmission lines, relying on the multi-sources fault location results from distance relays of two ends. The location results from two ends and a fault position are related to each other. According to these relationships, a multi-sensor data fusion-based transmission line fault location model is built. In the model, fuzzy inference systems are formed and serve as the initial fusion step to identify fault scenarios. Weighted covariance fusion coefficients are calculated and used to determine the final fusion result. The case study is carried out using PSCAD/EMTDC and field recording data from substations. The performance of the method is tested for different fault types, fault positions, fault resistances, fault inception angles, load How, line parameters and two-terminal unsynchronized angles.

• 出版日期2019-7
• 单位西安交通大学