Transmission Line Fault Location Research Articles

Deep learning through LSTM classification and regression for transmission line fault detection, diagnosis and location in large-scale multi-machine power systems

Fault detection, diagnosis, identification and location are crucial to improve the sensitivity and reliability of system protection. This maintains power systems continuous proper operation; however, it is challenging in large-scale multi-machine power systems. This paper introduces three novel Deep Learning (DL) classification and regression models based on Deep Recurrent Neural Networks (DRNN) for Fault Region Identification (FRI), Fault Type Classification (FTC), and Fault Location Prediction (FLP). These novel models explore full transient data from pre- and post-fault cycles to make reliable decisions; whereas current and voltage signals are measured through Phasor Measurement Units (PMUs) at different terminals and used as input features to the DRNN models. Sequential Deep Learning (SDL) is employed herein through Long Short-Term Memory (LSTM) to model spatiotemporal sequences of high-dimensional multivariate features to achieve accurate classification and prediction results. The proposed algorithms were tested in a Two-Area Four-Machine Power System. Training and testing data are collected during transmission lines faults of different types introduced at various locations in different regions. The presented algorithms achieved superior detection, classification and location performance with high accuracy and robustness compared to contemporary techniques.

Fault location for overhead and cable hybrid transmission line in VSC-HVDC system

Because the traditional fault location method cannot be applied to overhead and cable hybrid transmission line in the VSC-HVDC system, this paper proposes a novel fault location method, which primarily uses the principle of first determining the fault segment and then locating the fault point in the fault segment. Two voltage symbolic functions are defined, and the fault segment is determined according to the different numerical combinations of the two voltage symbolic functions. Through combining adaptive characteristic scale decomposition with improved general local frequency decomposition to adaptively extract the fault characteristic component, the intra-segment location equation is established based on the characteristic component to locate the fault point. The simulation results verify that the proposed method can accurately locate the fault point for the overhead and cable hybrid transmission line in the VSC-HVDC system.

Research on Transmission Line Fault Location Based on the Fusion of Machine Learning and Artificial Intelligence

After a transmission line fails, quickly and accurately find the fault point and deal with it, which is of great significance to maintaining the normal operation of the power system. Aiming at the problems of low accuracy of traditional traveling wave fault location methods and many affected factors, this paper relies on distributed traveling wave monitoring points arranged on transmission lines to study methods to improve the accuracy of traveling wave fault location on transmission lines. First, when a line fails, a traveling wave signal that moves to both ends will be generated and transmitted along the transmission line. We use the Radon transform algorithm to process the traveling wave signal. Then, this paper uses ant colony algorithm to analyze and verify the location and extent of transmission line faults and then optimizes high-precision collection and processing. Finally, the simulation distance measurement is carried out on double-terminal transmission lines and multiterminal transmission lines (T-shaped lines) with branches. The results show that, for double-ended transmission lines, the algorithm increases the speed of matrix calculations and at the same time makes the fault location error of the transmission grid still maintain the improved effect.

A Novel Transmission Line Fault Location Method Based on Time Frequency Correlation

The fault location method based on the transient traveling wave has been widely used in power grid. The location accuracy and reliability of traveling wave fault location may get affected by some factors including: length error of transmission line, timing error, secondary signal cable in substation. The paper proposes a novel fault location method based on the time-frequency correlation of the fault data collected from two ends of transmission line. It takes advantage of the symmetry and similarity of reflected waves at both ends while the resonance and the reflected waves of adjacent lines are not correlated with each other. Through time-frequency correlation analysis at both ends, the influence of interference and resonance is suppressed, reliability of reflected wave identification and fault location, as well as accuracy of fault location are improved. Effectiveness of the method is verified by simulation and field data.

Equivalent characteristic impedance based hybrid-HVDC transmission line fault location

Aiming at the transmission line fault in Hybrid-HVDC system, this paper divides the fault evolution process into different stages according to the difference of transition resistance at the fault point and the conduction state change of power electronic devices, emphatically analyzes the conversion conditions between different stages, and proposes an adaptive criterion for judging the moment when the fault evolves into AC feed-in stage. Based on the characteristic component of electrical quantities at AC feed-in stage, this paper defines the equivalent characteristic impedance at any point of transmission line, derives the functional relationship between the fault distance and the equivalent characteristic impedance at inverter side DC bus, and locates the fault point according to this relationship. In order to extract the characteristic component of electrical quantities, a characteristic component extraction algorithm is studied, it can effectively eliminate the influence of constant DC component and decaying aperiodic component. This paper builds the Hybrid-HVDC system simulation model and carries out simulation experiments on PSCAD/EMTDC, and compares the proposed fault location principle with the existing methods. The simulation results verify the effectiveness of the adaptive criterion for judging the AC feed-in stage starting moment and the proposed fault location principle.

Fault Location Approach for Teed Transmission Line Independent of Wave Speed

The uncertainty of traveling wave speed always causes big deviations to the fault location. In order to conquer the influence of traveling wave speed on transmission line fault location, a new method of fault location was presented in this paper. The method contains two main parts: the establishment of the identification matrix for the fault section and fault point location. Firstly, the arrival times of the initial fault traveling waves are used to form the identification matrix for the fault section, and the fault section can be identified according to characteristics of element in the formed identification matrix, and the matrix avoids the influence of wave speed; Secondly, a new locating algorithm without influence of wave speed was derived based on the principle of double-node traveling wave fault location. The simulation results show that the arrival time of initial fault traveling wave can be detected accurately, and then the fault section and the fault point can be located exactly by using the method proposed by this paper. And the method is unsusceptible to wave speed, fault type, transition resistance.

A Single-Terminal Fault Location Method for HVDC Transmission Lines Based on a Hybrid Deep Network

High voltage direct current (HVDC) transmission systems play an increasingly important role in long-distance power transmission. Realizing accurate and timely fault location of transmission lines is extremely important for the safe operation of power systems. With the development of modern data acquisition and deep learning technology, deep learning methods have the feasibility of engineering application in fault location. The traditional single-terminal traveling wave method is used for fault location in HVDC systems. However, many challenges exist when a high impedance fault occurs including high sampling frequency dependence and difficulty to determine wave velocity and identify wave heads. In order to resolve these problems, this work proposed a deep hybrid convolutional neural network (CNN) and long short-term memory (LSTM) network model for single-terminal fault location of an HVDC system containing mixed cables and overhead line segments. Simultaneously, a variational mode decomposition–Teager energy operator is used in feature engineering to improve the effect of model training. 2D-CNN was employed as a classifier to identify fault segments, and LSTM as a regressor integrated the fault segment information of the classifier to achieve precise fault location. The experimental results demonstrate that the proposed method has high accuracy of fault location, with the effects of fault types, noise, sampling frequency, and different HVDC topologies in consideration.

Accurate Fault Detection and Location in Power Transmission Line Using Concurrent Neuro Fuzzy Technique

Wydawnictwo SIGMA-NOT wydaje czasopisma fachowe informujące swoich czytelników o najnowszych osiągnięciach naukowych i nowoczesnych rozwiązaniach technicznych w Polsce i na świecie, popularyzuje problemy techniczne oraz poszerza wiedzę i kulturę techniczną.

Research on Transmission Fault Location Based on Scanning Data

Aiming at the problem that the conventional transmission line fault location method has a delay in positioning and cannot be timely feedback, a method for fault location of transmission lines based on 3D scan data matching is proposed. 2D feature points are used to obtain three-dimensional point pairs. Structured light projectors and 3D scanning technology are applied to match image feature points and generate mapping relationships with reconstructed 3D space points. Then use point cloud computing to solve three-dimensional coordinates and use features. Click the interpolation result to complete the data matching process. The simulation experiment applies the 3D scanning data matching technology to the operation process of transmission line fault location. The experimental results show that compared with other methods, the method of this paper has the highest detection stability and the advantage of high accuracy of intelligent fault diagnosis, and can give feedback on transmission line faults in time.

Fault Location in Overhead Transmission Lines Based on Magnetic Signatures and on the Extended Kalman Filter

This paper proposes a non-contact method for fault location in transmission lines, which is based on magnetic fields produced by current signals measured using magnetoresistive sensors installed only at transmission line terminals, under the phase conductors of the first transmission tower at both terminals or at the substations portals. The proposed method uses the Extended Kalman filter to process these measurements and is based on a travelling wave approach in order to perform the fault localization. This paper also describes the implementation and testing of the method, firstly introducing its overview, followed by an analysis of the magnetic fields produced by the current signals, as well as considerations on their measurement; secondly, detailing the Extended Kalman filter and the travelling wave approach; and, finally, presenting the results of the method with regards to simulations built using EMTP/ATP to evaluate its robustness under different conditions varying the fault resistance, fault inception angle, phases involved and fault location. The results indicate that the proposed method is robust and accurate.

Fault Location Using the Natural Frequency of Oscillation of Current Discharge in MTdc Networks

This paper discusses a novel fault location approach using single ended measurement. The natural dissipation of the circuit parameters are considered for fault location. A relationship between the damped natural frequency of oscillation of the transmission line current and fault location is established in this paper. The hybrid dc circuit breaker (dcCB) interrupts the fault current and the line current attenuates under the absence of any driving voltage source. The line capacitance discharges into the fault at a specific frequency of oscillation and rate of attenuation. Utilizing this information, the fault location in a multi-terminal direct current (MTdc) network can be predicted. A three terminal radial model of a MTdc is used for performance evaluation of the proposed method using Power System Computer Aided Design (PSCAD)/Electromagnetic Transients including dc (EMTdc).

COMPARATIVE FAULT LOCATION ESTIMATION BY USING IMAGE PROCESSING IN MIXED TRANSMISSION LINES

Overhead lines are generally used for electrical energy transmission. Also, XLPE underground cable lines are generally used in the city center and the crowded areas to provide electrical safety, so high voltage underground cable lines are used together with overhead line in the transmission lines, and these lines are called as the mixed lines. The distance protection relays are used to determine the impedance based fault location according to the current and voltage magnitudes in the transmission lines. However, the fault location cannot be correctly detected in mixed transmission lines due to different characteristic impedance per unit length because the characteristic impedance of high voltage cable line is significantly different from overhead line. Thus, determinations of the fault section and location with the distance protection relays are difficult in the mixed transmission lines. In this study, 154 kV overhead transmission line and underground cable line are examined as the mixed transmission line for the distance protection relays. Phase to ground faults are created in the mixed transmission line. overhead line section and underground cable section are simulated by using PSCAD/ EMTDC ™. The short circuit fault images are generated in the distance protection relay for the overhead transmission line and underground cable transmission line faults. The images include the R-X impedance diagram of the fault, and the R-X impedance diagram have been detected by applying image processing steps. Artificial neural network (ANN) and the regression methods are used for prediction of the fault location, and the results of image processing are used as the input parameters for the training process of ANN and the regression methods. The results of ANN and regression methods are compared to select the most suitable method at the end of this study for forecasting of the fault location in transmission lines.

Travelling Wave Fault Location of HVAC Transmission Line Based on Frequency-Dependent Characteristic

Travelling wave (TW) fault location has been widely utilized for high-voltage alternating current (HVAC) transmission lines, which is proven to have a higher accuracy than conventionalpower frequency data based fault location. However, as known, the performance of travelling wave-based fault location (TWFL) principles is often challenged by several factors including fault location, fault initial angle, fault resistance as well as frequency dependency of HVAC transmission lines. In this context, this paper proposes a novel off-line TW fault location principle for transposed HVAC transmission lines to address the robustness against those uncertain factors. Firstly, the frequency-dependent characteristic of HVAC transmission lines is analyzed. Then upon that, a novel TW fault location principle is proposed, which consists of two important components: i) arrival time detection of TW and ii) accurate frequency calculation of TW. Eventually, simulations are carried out on a 500 kV AC transmission system using PSCAD/EMTDC to validate the effectiveness of the proposed method and itsrobustness against different fault types, resistances, locations, initial angles and noises.

Single Pole‐to‐Ground Fault Location Method for MMC‐HVDC System Using Wavelet Decomposition and DBN

Accurate and reliable fault location technology is essential to the stable operation of the modular multilevel converter‐high voltage direct current (MMC‐HVDC) system. Aiming at the difficulty of locating high‐resistance ground faults on MMC‐HVDC transmission lines, this paper proposes a method for fault location of transmission lines based on wavelet transform and deep belief network (DBN). First, the wavelet transform is used to decompose the original single pole ground fault voltage waveform, and then the high‐frequency and low‐frequency components obtained are used as training samples to train different DBN models, the final fault location results are obtained by superimposing the outputs of each model at last. The ±250 kV double‐ended MMC‐HVDC system model is established by using PSCAD/EMTDC, which can simulate the faults of different positions and different transition resistances. In order to verify the fault location performance of the proposed method, it is compared with two machine learning fault location methods. The results show that this method can accurately and reliably locate the single pole‐to‐ground fault of the transmission line with transition resistance of up to 10 000 Ω at low sampling frequency of 20 kHz. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Time-Domain Transmission Line Fault Location Method With Full Consideration of Distributed Parameters and Line Asymmetry

Accurate fault location reduces operating cost and outage time. This paper proposes a time-domain method to accurately locate faults in transmission lines, which only requires a very short data window (several milli-seconds) during faults. First, the voltage distribution through the line during faults is accurately obtained by solving the matrix form partial differential equations using the proposed numerical scheme. The proposed numerical scheme is mathematically validated for the transmission line fault location problem, with the optimal selection of time and distance intervals to ensure stability and minimum solution error. Afterwards, the fault location is obtained via the extremum value of the voltage distribution. The method fully considers distributed parameters as well as asymmetry of the line. Extensive numerical experiments validated that (a) the proposed numerical scheme demonstrates advantages towards other numerical schemes; (b) the proposed method presents higher fault location accuracy compared to the existing method, independent of fault types, locations and impedances; and (c) the fault location accuracy is not sensitive towards fault inception angles, loading conditions, measurement errors and parameter errors. The proposed method works with relatively low sampling rates (80 samples per cycle) and is compatible with IEC 61850 standard in present digital substations.

An improved algorithm for fault detection and location in multi-terminal transmission lines based on wavelet correlation modes

This paper proposes a new time-domain method for fault detection and location in alternating current multi-terminal transmission lines based on wavelet analysis called wavelet correlation modes. Power system protection of multi-terminal transmission lines is a complex task because the infeed effect may affect its performance. The proposed algorithm based on one-terminal measurements enhances the detection time and diminishes the error of the fault location. This approach suits the protection scheme to attain reliable and accurate performance when any fault type is presented at different locations along the transmission line. The applicability of this proposal is validated under different fault scenarios and compared against conventional protection algorithms. The proposed algorithm is implemented in MATLAB software, and all simulations are conducted in the Alternative Transients Program of the Electromagnetic Transients Program (ATP/EMTP) software. The presented results confirm the main advantages of this approach. The new introduced method is tested under different mother wavelets to estimate the fault location.

A Signal-Superimposed Technique for Fault Location in Transmission Lines Through IED Measurements Considering Communication Service Failure

This article presents an innovative fault location algorithm utilizing an unsynchronized waveform measured from independent intelligent electronic devices (IEDs) installed in individual power substations without available wired or wireless communication link between the IEDs to establish the common timestamp required for the IEDs to record waveform data synchronously. The proposed idea is developed based on the positive-sequence waveform phasors with the superimposed-signal concept. A novel fault position indicator is proposed to yield an exact solution without being affected by unsynchronized measurement information because the unsynchronized-angle estimation is needless. Besides, the proposed idea does not require any assumptions, such as fault impedance, and is also free from computational complexity in as much as neither iterative operations nor fault type selections are needed. Last but not least, an extensive series of simulations and two field test results from the fault events of Taiwan Power Company have been presented to demonstrate the accuracy and practicality of the suggested technique.

Transmission line fault location by solving line differential equations

The present paper describes a new algorithm for reliably locating the faults that frequently take place on electrical transmission lines. The proposed fault location technique considers a distributed-parameter line model that is given in the form of Partial Differential Equations (PDEs) whose boundary conditions are taken as synchronized time-domain data recorded from both sending and receiving terminals. The Adomian Decomposition Method is employed to spatially solve the sampled-time line model. The obtained solution provides phase voltages and currents profiles at each sample time as a function of line length. This function is expressed as a polynomial whose coefficients are simply determined by an easily-applied recursive procedure. One of the main interesting features of the developed scheme is that it can handle the case of unsymmetrical transmission lines without the need of modal decomposition that decouples the original three-phase system to an equivalent three independent single-phase systems. Simulations and calculations are all proceeded with MATLAB. The obtained results through different simulations show that the new methodology is operational, applicable, and accurate.

Voltage–current technique to identify fault location within long transmission lines

Current industry practice to identify fault location in transmission lines is based on visual inspection, travelling waves, and line impedance measurement. Unfortunately, these techniques are only developed to detect the fault location upon its occurrence without the ability to predict abnormal events that usually precede major faults and issue a timely warning signal to avoid potential consequences for power line failures. Furthermore, the current fault locating techniques exhibit some drawbacks that limit their wide practical implementation. This includes cost, access to required data, and low accuracy when employed for specific power line topologies. This study is aimed at presenting and validating a new cost-effective technique based on the line voltage–current characteristics to predict and identify the location of various abnormal and fault events in real-time. By measuring the currents and voltages at both ends of the line, a unique line fingerprint can be identified. Any change in this fingerprint can be detected and analysed by a software installed in the control centre in real-time to identify the location, type, and level of the abnormal events or emerging faults. Robustness of the proposed technique is assessed through simulation analysis conducted on various case studies along with a practical case study.

Design of Traveling Wave Location Method for Transmission Line Fault Based on EMD-TEO

<p>With the rapid development of the social economy and the continuous extension of Internet technology, China’s power grid has entered the ranks of large-scale, high-voltage, and intelligent. The main purpose of the fault location of the transmission line is to eliminate hidden trouble and restore the fault line in time to ensure the safe and stable operation of the power system. With the advent of the smart grid, higher requirements are put forward for fault location accuracy, while the traditional wavelet transform and Hilbert-Huang transform have larger defects.</p><p>Therefore, this paper extensively analyses the generation and characteristics of fault traveling waves in transmission line fault, which proves that the traveling wave location method has higher location accuracy than the fault analysis method. Among them, the two-terminal traveling wave positioning method only uses the arrival time of the initial traveling wave, avoiding the principled defects and locating the dead zone of the single-terminal traveling wave positioning method, so the two-terminal traveling wave positioning method is generally used. The key of the two-terminal traveling wave location method is that it can accurately detect the arrival time of the initial traveling wave head. Although the Hilbert-Huang Transform (HHT) method can be used to detect the arrival time of the initial traveling wave head, the problem of inaccurate detection or failure of the wave head may arise when the instantaneous frequency of the IMF component decomposed by the Hilbert-Huang transform is used because of the mode aliasing in the empirical mode decomposition algorithm. Based on the above analysis, an empirical mode decomposition (EMD) combined with the Teager energy operator(TEO) is proposed for the traveling wave fault location of transmission lines. A large number of simulations prove that the EMD-TEO method in this paper can solve the problem of inaccuracy or failure of the HHT method using instantaneous frequency to detect the arrival time of wave head, and has higher fault location accuracy.</p>