High Voltage Transmission Line Fault Research Articles

Automated monitoring of high-voltage transmission lines based on machine vision

Abstract This paper takes the automated monitoring of high-voltage transmission lines as the entry point and constructs an automated monitoring model of high-voltage transmission lines based on machine vision. Through the transmission equipment recognition algorithm to identify the type and location of the equipment in the inspection image, using image processing methods for the collected high-voltage transmission line image color image grayscaling and grayscale image stretching, and then grayscale image smoothing and segmentation, so as to achieve the identification of the location of high-voltage transmission line fault location. Simulation test for image processing and transmission equipment identification methods, and then carry out automated monitoring experiments with high-voltage transmission line conductor stranding as an example to verify the feasibility and reliability of the model in this paper. The results show that for the automatic detection of individual conductor strand breakage, the method of this paper detects the number of strand breakage is only 1-2 less or more than the actual number of strand breakage; there is a certain difference, but basically in line with the actual situation, and the method of this paper, on average, detects the efficiency of the method is faster than the traditional method by 5.69~7.18 s/m. The research to enhance the quality of automated monitoring of high-voltage power transmission lines has a certain application value.

Transmission line fault location: Simulation of real faults using wavelet transform based travelling wave methods

In this study, High Voltage Transmission Line fault location accuracy of distance relays running impedance algorithm are compared with Travelling Wave (TW) method. Line faults in 154 kV Tatvan – Muş and 154 kV Patnos-Erciş lines in Turkish Electrical Transmission System are analyzed. Real faults in both lines are simulated in MATLAB-SIMULINK. Tower configuration and conductor properties of the lines and the source impedances are included in the simulation to comply with real system. Simulations show that both single-end and double-end Wavelet Transform (WT) based TW methods have better accuracy then the distance relays computing fault location by impedance methods.

Fault location on high voltage transmission line by applying support vector regression with fault signal amplitudes

This paper proposes a novel high voltage transmission line fault location scheme based on application of support vector regression (SVR). The proposed scheme just uses the amplitudes of the fault voltage waveforms, measured at a single end of the line. Various types of faults at different locations with different fault impedances and a variety of fault inception angles are studied on a 400kV–300km high-voltage transmission line power system. The fault voltages are obtained from 1/8 cycle post-fault signals after the noise has been eliminated using a low-pass filter. The amplitudes of the fault voltage signals are used as features to train the SVR. After training, the SVR is used in the exact location of the fault on the transmission line. When compared with other fault location schemes, the proposed scheme requires less information and a smaller time data window to estimate the fault locations. However, the proposed scheme provides more accurate estimations, irrespective of the fault types, fault inception angles and fault impedances.

Design of power cable grounding wire anti-theft monitoring system

In order to prevent the serious consequences of the power grid failure caused by the power cable grounding wire theft, this paper presents a GPRS based power cable grounding wire anti-theft monitoring device system, which includes a camera module, a sensor module, a micro processing system module, and a data monitoring center module, a mobile terminal module. Our design utilize two kinds of methods for detecting and reporting comprehensive image, it can effectively solve the problem of power and cable grounding wire box theft problem, timely follow-up grounded cable theft events, prevent the occurrence of electric field of high voltage transmission line fault, improve the reliability of the safe operation of power grid.

Detection and classification of faults in transmission lines using the maximum wavelet singular value and Euclidean norm

In this study, a novel algorithm for detecting and classifying faults in high-voltage transmission lines is proposed. The algorithm is based on the discrete wavelet transform (DWT) and singular value decomposition (SVD). The DWT is used for extracting the currents’ high-frequency components under fault conditions. Signals under each fault condition are scaled in frequency, in order to build a wavelet matrix. By means of the SVD, the maximum singular value is calculated and employed in this proposal. The attained results exhibit that the maximum singular value represents a good indicator for the issue. This novel approach for detecting and classifying faults in power systems is called maximum wavelet singular value. Phase-to-ground, two-phase to ground, and three-phase faults’ simulations under different fault impedances are carried out by DIgSILENT Power Factory. The analysed fault conditions are evaluated demonstrating that the proposal reduces the computational burden and the time detection.