Asynchronous Fault Location Algorithm for Two-terminal Transmission Lines Based on Artificial Neural Network and Network Migration

The current algorithms of the two-terminal transmission line fault location rely either on the line models and the line parameters, or on the large amounts of historical fault data. To solve this problem, first by summarizing the fault location principles of the distributed parameter model and the Π-type model, this paper establishes the fault location function of the two-terminal transmission line according to the positive sequence voltage and the positive sequence current before and after a fault. Then, an asynchronous fault location algorithm is proposed for the two-terminal transmission lines based on the artificial neural network and the network migration but without depending on the line model and the line parameters. Finally, a simulation model of the 500kV transmission line is built on the Matlab/Simulink, verifying the correctness and reliability of the proposed algorithm. The theoretical analysis and simulation results show that the proposed algorithm has higher accuracy without being affected by the factors such as the fault locations, the fault types, the transition resistance, the fault initial phase angles, the load current and the asynchronous data. In addition, by making full use of a large amount of normal data and a small amount of fault data of the lines based on the idea of the network migration, the proposed algorithm still has a higher accuracy when the line parameters change within the range of less than ±1%. © 2023 Power System Technology Press. All rights reserved.