Research on Fault Detection of 110 kV Transmission and Distribution Lines Based on Deep Learning
In order to optimize the fault detection effect of 110 kV transmission and distribution lines,improve the fault detection rate,and ensure the safe and reliable operation of transmission and distribution lines,the principle of deep learning was introduced to carry out research on 110 kV transmission and distribution line operation fault detection based on deep learning.Firstly,establish a mathematical model for the 110 kV transmission and distribution line to better obtain the operating conditions and power parameters of the line.Secondly,the effective value method is used to calculate the ratio of the effective value of zero sequence current in each section of the line to the average effective value of zero sequence current in all sections.Based on the calculation results,the faulty section of the line operation is determined.On this basis,using the principle of deep learning,a deep learning network structure is constructed to extract the fault components of the fault section,calculate the fault distance of the line,and then determine the fault point within the fault section based on the fault distance,achieving the goal of fault detection and positioning.The results show that after the application of the proposed detection method,the fault detection rate of 6 110 kV transmission and distribution lines has reached over 98％,which can more accurately detect potential fault hazards in the operation of transmission and distribution lines.
deep learning110 kVtransmission and distribution linesfaultoperationdetection
NETL
NSTL
万方数据
