Traveling Wave Fault Location Method Research Articles

A Highly Accurate Double-Ended Traveling Wave Fault Location Method Using GWO-VMD and the Hilbert Transform for Offshore MMC-MTDC Grids

Accurate and reliable DC fault location methods can significantly enhance the resilience and reliability of offshore MMC-based multi-terminal direct current (MTDC) grids. This research proposes a novel double-ended DC fault location method using the GWO-VMD and the Hilbert transform. First, the propagation of traveling waves (TWs) in the faulty line-mode network is described, leading to the theoretical expressions for the Backward Line-mode Voltage TWs (BLVTWs). Next, the Grey Wolf Optimizer-Variational Mode Decomposition (GWO-VMD) algorithm is employed to extract the high-frequency components contained in the measured BLVTWs, and the Hilbert transform is used to obtain the Instantaneous Energy Spectrum (IES) of the specific IMFs, allowing for the determination of the arrival times of the TWs. Numerous simulations in the PSCAD/EMTDC and RTDS environments confirm that the fault location method is accurate under various sampling frequencies and for close-in faults. Comparison studies also demonstrate that the proposed method is more accurate than existing classical TW-based methods. Additionally, the RTDS tests show that the method can withstand noise disturbances of at least 30 dB and has the potential to be applied in real projects.

Novel traveling wave fault location method for HVDC transmission line based on wavefront frequency

The key of traveling wave (TW) fault location (FL) method is the calculation of TW velocity and the calibration of TW wave head. In order to achieve high-precision FL, detailed transmission line (TL) parameters are needed to accurately calculate the TW velocity. In view of the problem that the existing high-precision TWFL methods are highly dependent on the calculation of TW velocity, the paper contributes to following aspects: (i) the mapping relationship between wavefront frequency and fault distance/fault pole is constructed; (ii) a neural network model suitable for FL and fault pole identification is designed, which is optimized by Particle Swarm Optimization (PSO) algorithm and Levenberg–Marquardt (L-M) algorithm; (iii) a complete FL scheme is proposed. In order to verify the FL accuracy of proposed method, an ±800 kV bipolar high-voltage direct-current (HVDC) transmission system model is constructed using PSCAD/EMTDC. According to the simulation results, the errors of FL is less than 0.2 km and the accuracy of fault pole identification is 100%. For the problems of fault type, fault resistance and noise, the proposed method shows high robustness.

A non-contact current traveling wave fault location method for multi-terminal overhead power lines based on adaptive mathematical morphology

A non-contact current traveling wave fault location method for multi-terminal overhead power lines based on adaptive mathematical morphology

Study on Traveling Wave Fault Localization of Transmission Line Based on NGO-VMD Algorithm

To address the challenge of inaccurate fault location of variational mode decomposition (VMD) in practical engineering, due to poor choice of mode decomposition number K and quadratic penalty factor α, a traveling wave fault location method using Northern Goshawk optimization algorithm (NGO) to optimize VMD was proposed. First, the NGO algorithm is used to optimize VMD, and the optimal K and α are obtained. Secondly, the optimal parameters are inputted into VMD for fault signal decomposition, and the eigenmode components are obtained. Due to the difficulty of identification of the traveling wave head in the process of traveling wave propagation, Hilbert transform is used to determine the time of initial arrival of the traveling wave head at both ends of the line, and the fault location is precisely calculated by using the two-ended traveling wave fault detection formula. Finally, simulation experiments are carried out to verify the accuracy of the proposed location method, which shows that the proposed location method can locate the fault more accurately and has good engineering application value.

A Fault Location Method for Medium Voltage Distribution Network Based on Ground Fault Transfer Device

The arc suppression device based on ground fault transfer (GFT) has been preliminarily applied in the medium voltage distribution network (MVDN). An accurate travelling wave (TW) fault location method is proposed to extend the use of the ground fault transfer device. D-PMU is used as a travelling wave detection tool to record the transient voltage travelling waves of fault grounding and bus active grounding during arc suppression. Then, the faulty section is identified through the time difference of travelling wave arrival at the upstream and downstream measurement points. On this basis, the fault location equations of the arrival time and distance of the upstream travelling wave are established, and an accurate fault location method based on the arrival time difference of the travelling wave is proposed. The simulation model is established by PSCAD/EMTDC, and the results show that the method has high location accuracy, and the absolute error is less than 30 m. It is not affected by the TW velocity, the fault conditions, or the distributed power sources.

A Single-Ended Fault Location Method for Transmission Line Based on Full Waveform Features Extractions of Traveling Waves

Conventional single-ended traveling wave fault location methods, which commonly depend on partial features of traveling wavefronts, may lead to fault location failure, especially for weak-signal faults such as high impedance or zero-crossing faults and close-in faults. To tackle it, this paper presents a fault location method according to the extracted panoramic features of traveling wave full waveform (TWFW) in time-frequency domains. Firstly, two rules of the TWFW features are probed, that is, the wavefront arrival sequence is varied from fault sections, as well as the frequency distribution of wavefronts is strongly related to the precise fault distance. Ergo, the mapping relationships between the TWFW and fault distance are qualitatively confirmed in order to demonstrate the uniqueness of the TWFW subsequently. Next, a LeNet-5-based convolution neural network (CNN) model is constructed to quantitatively evaluate such mapping relationships. In this model, various TWFW features will be extracted to the convolution channels when the CNN parameters are optimized adaptively, and the mapping relations can be formed in light of these sensitive features to estimate the fault distance. Finally, a Grad-CAM visualization method is deployed in the case study, and the accuracy along with the robustness of the proposed method in various fault conditions can be validated consequently.

Correlation-based single-ended traveling wave fault location methods: A key settings parametric sensitivity analysis

This paper presents a sensitivity analysis of the key parametric settings used to computationally implementing transmission line single-ended correlation-based traveling wave fault location (SEC-TWFL) algorithms. To estimate the short-circuit distance, these techniques compare the signal transient patterns generated by the first incident traveling wave (TW) that reach the monitored terminal with those created by consecutive reflections that come from the fault point. To do so, a diversity of filtering processes, correlation strategies and transient observation windows can be adopted, resulting in different fault location performances. The Alternative Transients Program (ATP) is used to generate a wide variety of fault records, which are then evaluated with different SEC-TWFL methods varying the used correlation functions, filtering techniques and observation window lengths. From the performed studies, the advantages and limitations of the evaluated computational implementation strategies are addressed, and new parametric settings recommendations are proposed, demonstrating that very accurate fault location estimations can be obtained when specific implementation strategies for each of the evaluated methods are considered. • New setting recommendations are proposed to be applied in SEC-TWFL methods. • The transient signal mean value removal, as typically reported, is not suitable. • The observation window length directly affects the fault location performance. • The window length comprising only the first TW as usually reported is not indicated.

Two-terminal traveling wave fault location based on successive variational mode decomposition and frequency-dependent propagation velocity

This paper proposes a two-terminal traveling wave fault location method based on Successive Variational Mode Decomposition (SVMD) and frequency-dependent propagation velocity. Firstly, SVMD is used to extract all Intrinsic Mode Functions (IMFs) and their center frequencies of the aerial mode voltages in a successive manner. The maximum IMF with the highest center frequency is used for further processing. Secondly, The propagation velocity is obtained by frequency–velocity characteristic curve and the arrival time of traveling wavefront is determined by the normalized Teager Energy Operator (TEO). Finally, considering the time-domain and frequency-dependent characteristics of traveling wave, the fault distance is estimated by combining the arrival time, frequency and propagation velocity. PSCAD/EMTDC simulation results show that the proposed method achieves reliable and robust performance under different fault scenarios and outperforms compared existing methods. • SVMD is introduced to adaptively decompose the fault traveling wave signal. • The propagation velocity is treated as a variable and estimated for fault location. • The proposed method is reliable and robust under different fault scenarios.

Two-terminal fault combination location method on MMC-HVDC transmission lines based on ensemble empirical mode decomposition

In the HVDC transmission system, the main factors that affect the accuracy of traditional two-terminal fault traveling wave distance measurement are the selection of appropriate wave velocity and whether the wave head can be identified. The line dispersion and transition resistance of the DC transmission will make it more difficult to determine the time when the wavehead reaches the two ends of the two sides, and the boundary elements of both terminal of the line will cause distortion of the wave head. Based on fault traveling waves characteristics of the time–frequency domain, we propose a method of Two-Terminal Fault Combination Location (TTFCL) on High Voltage Direct Current based on MMC (MMC-HVDC) transmission line. The method combines the natural frequency fault location method and the traveling wave fault location method. The first step of the walking wave natural frequency method is used for rough ranging, so that the approximate time range of the initial traveling wave of fault to reach the busbar can be obtained, and then can be calculated the rough position range of the fault point. Then the second step of accurate ranging is carried out, using the Ensemble Empirical Mode Decomposition (EEMD) algorithm to decompose the processed signal, extract the traveling wave component of the high-frequency, identify the traveling wave of initial head recognition and calibration, obtain the time parameters required for fault ranging, and calculate the more accurate fault point location by the two-ended fault ranging formula. In PSCAD/EMTDC, we built a simulation model of MMC-HVDC system line fault, and the simulation experiments are compared with different fault types and locations, and the results show that the combined fault ranging method eliminate the wave speed influence on accurate positioning and effectively identifies the wave head, which further improves the ranging accuracy.

Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playback TWs using two development boards is also addressed.

Bi-level decision matrix based fault location method for multi-branch offshore wind farm transmission lines

Multi-branch complex structure and harsh maintenance environment directly lead to the high-cost and time-consuming of fault detection in deep-sea offshore wind farms (DOWF). This paper proposes a traveling wave fault location method based on a bi-level decision matrix (BDM) aiming at multi-branch deep-sea offshore wind farm transmission lines. First, the first intrinsic mode function (IMF) signal is extracted by the variational mode decomposition (VMD) from initial traveling wave signals, which is further decomposed into S matrix by Stockwell-Transform (ST). Then based on the energy similarity between E matrix obtained through S matrix at all records, the area decision matrix is built to identify fault area. Second, S matrix recorded at both ends of fault area is extracted and analyzed by kurtosis to determine the traveling wave arrival time. Based on the fault area inherent topology and the traveling wave arrival time, the section decision matrix is built to identify fault section. Finally, the fault location is determined by the corresponding calculation process based on the identification results of BDM. Referring to the actual multi-branch topology of offshore wind farm (OWF), case studies are conducted under various fault conditions. The results show that the proposed method does not need to install recorders at all terminals, has high fault location accuracy, and is immune to noise.

ELECTRICAL NETWORK OF FAULT REGIME MODEL CONSTRUCT FEATURES IN A SINGLE-END TRAVELING WAVE FAULT LOCATION METHOD

In the single-end traveling wave (TW) fault location methods, for determining TW front, the arrival time of which is determined by the place of the short circuit (SC) on the power line, electrical network of fault regime models are constructed. From the electrical network of fault regime models, only one is selected that allows, by the first TW front magnitude and its arrival time, to obtain estimations of the TWs fronts magnitudes and their arrival times which are closest to the corresponding quantities determined from locator measurements. Based on the selected electrical network of fault regime model the used TWs are identified and the fault place is determined. Known implementations of the single-end traveling wave fault location method use simplified electrical network of fault regime model: the influence of the fault type and its resistance, as well as the parameters of the electrical network elements, are not taken into account on the TWs fronts magnitude. These disadvantages can cause both an increased error in determining the fault location and even failure in the operation of the locator. In this article, the theory of constructing electrical network of fault regime model is presented: the influence of fault location and its type on the TWs fronts magnitude are considered. Particular attention is paid to the study of the issue of the TWs generation as a result of the cross-transmission effect. It is shown that in order to correctly determine the used TW front in the electrical network of fault regime model, in addition to the power line length and its characteristic impedance, it is necessary to take into account the short circuit type and its resistance, and the possible TWs generation in one mode under the influence of TWs in another one.

Fault location in overhead transmission line: A novel non-contact measurement approach for traveling wave-based scheme

Traveling wave fault location methods have gained considerable growth over the years, with the anticipation that power systems will be accurate and reliable everywhere. But the performance of classical traveling wave methods has focused only on traditional current transformer measurement in the literature till date. Therefore, in this paper, an innovative non-contact measurement of traveling wave formulation is proposed to achieve accurate fault location and time of arrival detection on a two-terminal overhead transmission line, since power cable naturally generates magnetic and electrical fields in the surrounding atmosphere. The proposed method solitary depends on the first two and successive time differences between the incident and reflective wave from the fault point of the transmission line. Thus, the proposed scheme does not depend on current transformer measurement that stimulates the accuracy and reliability of the conventional traveling wave fault location method. To ensure an accurate time of arrival waves detection, we exploit the magnetic field sensor array on each tower to measure the quality of current traveling waves generated on the transmission line and locate the transient disturbances as a result of a short circuit. By analyzing the line energization, a comprehensive fault analysis on a 500-kV line was simulated with PSCAD/MATLAB toolbox compared to the two-terminal classical method. The sensitivity analysis demonstrated that the proposed method is much accurate and reliable to be deployed and cost-effective, making it highly useful and efficient in comparison to the classical two terminals traveling wave method with an average error of 0.014%. The effectiveness of the proposed method was verified by laboratory experimental setup.

A multi-terminal traveling wave fault location method for active distribution network based on residual clustering

Since distribution networks have multiple branches, complex topologies and increasing penetration of the distributed energy resources (DERs), the accurate fault location is difficult to realize. The existing traveling wave fault location methods are strongly affected by the arrival time errors. To overcome the problems mentioned above, a multi-terminal traveling wave fault location method is proposed for active distribution networks based on residual clustering. Firstly, the traveling wave arrival times are utilized to construct a minimized optimization model for each section. The objective optimization function represents the minimization of the sum of squared errors (MSSE), and the global optimal solutions reflect the wave velocity and the fault distance. Subsequently, the particle swarm optimization algorithm (PSO) is used to solve the above optimization models, and the section with the minimum MSSE is judged as the faulty section. Finally, the density-based spatial clustering of applications with noise (DBSCAN) algorithm is utilized to group the residuals of the faulty section to identify the bad data, which are affected by the arrival time errors. And the normal data remained are applied to reconstruct the optimization model and calculate the optimal solution of the fault distance. Thus, the fault location results can be corrected. Simulation results and field tests indicate that the proposed method has high fault location accuracy, strong robustness to time errors and high adaptability for active distribution networks.

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 traveling wave fault location method for transmission network based on time linear dependence

Transmission network faults may not be located accurately in some abnormal conditions, such as traveling wave location device faults, startup failure and time recording error. In order to improve them, a novel traveling wave fault location method based on time linear dependence is proposed. The proximal point optimization algorithm (PPOA) is used to find the shortest transmission path of fault traveling wave. The linear fitting between the arrival time of the traveling wave head recorded by each substation and the transmission distance is made on the Cartesian coordinate plane, according to the characteristic that the length of the shortest path is directly proportional to the traveling wave transmission time. The information fusion for the traveling wave arrival time at each substation is achieved by linear regression analysis to correct the error information. The accurate fault location is obtained direct by coordinate information of the intersection of the fitted line and the coordinate axis. Finally, the traveling wave location system based on this method has been successfully tested in Hunan Power Grid. PSCAD simulation and field test results prove that the proposed method can effectively reduce the recording error in the arrival time of the fault traveling wave at each substation while improving the reliability and accuracy of fault location.

Traveling-Wave-Based Fault Location Method for Hybrid Distribution Network Mixed with Three-Phase and Phase to Phase Supply Lines

In China, a hybrid distribution network mixed with three-phase main lines and phase to phase supply lines can be found in many MV distribution networks due to lower cost of using two lines from three-phase main lines as well as lower cost of phase to phase transformer. For such a hybrid distribution network it is a challenge for traditional fault location techniques. This paper presents a traveling wave fault location method based on double-terminal measurement techniques. The proposed method analyses the traveling wave propagation mechanism of both aerial mode and zero mode components for a fault. The method then determines which mode component is used for the fault location according to fault types. The method has been developed and assessed on a typical distribution network using ATP power network simulation tool. The tests were conducted under various fault scenarios. The results show that zero mode component is more effective for a fault on the phase of three-phase main lines which is not linked to the phase to phase supply lines. However for a phase-to-phase fault, aerial mode component is more effective. For the remaining fault types, either aerial or zero mode component can be used.

Research on the Fault Location Method of Double-terminal MMC-HVDC Transmission Line without the Influence of Wave Velocity

Due to its own advantages, MMC-HVDC transmission system has been widely used in power transmission and grid connection. According to the existing double-terminal traveling wave fault location method of MMC-HVDC transmission lines, a double-terminal traveling wave location method is proposed, which is not affected by wave velocity. The wavelet transform is performed on the voltage traveling wave signals at both ends to determine the time when the traveling wave reaches both ends of the line, and the distance of the fault point is calculated. It effectively reduces the influence of the uncertainty of traveling wave velocity on the positioning results and improves the positioning accuracy. The simulation of PSCAD and Matlab software proves the effectiveness and correctness of the method.

Single-phase ground fault location method for distribution network based on traveling wave time-frequency characteristics

The traditional traveling wave fault location methods only consider the information about time domain or frequency domain characteristics, so it is difficult to ensure the location accuracy. Through the research of relationship between traveling wave characteristic parameters and frequency, this paper proposes a single-phase grounding fault location method based on traveling wave time-frequency characteristics. Firstly, determine the time during which the traveling wave reaches the busbar by using the quadratic B-spline wavelet analysis modulus maximum detection algorithm with denoising factor.. Then, according to the improved matrix pencil algorithm, extracte the frequency of traveling wave arriving at the bus measuring point, and the corresponding velocity of incident wave is obtained. Finally, the fault distance can be calculated using the location equation of modulus wave velocity difference. The simulation results show that this method proposed in this paper has higher accuracy than the traditional method, and in the terms of different grounding resistance, fault initial angle and fault distance, the error of fault location is smaller.

A high frequency reflected current signals-based fault type identification method

The main objective of this paper is to identify fault type and faulted phase focus on the time delay values of reflected phase and modal current signals. The proposed method identifies fault type with the help of amplitude maxima of detail wavelet coefficient of residual current. The time delay values of phase and modal current reflected signals are used to detect faulty phase instead of using threshold values. Using time delay as a fault type identification parameter is achieved to save the overall protection system operating time because time delay is also the main feature of traveling wave fault location method. Moreover, to ensure the applied wavelet filter, the proposed algorithm is tested with the detail information of the three mother wavelets, such as db4, db6 and db8 and chosen the highest classification accuracy. Various disturbance events were tested with changing different possible fault types, faulted-feeders, fault resistances, fault locations and fault inception times on a loop distribution system. The robustness of the proposed faulted phase selection algorithm is performed through MATLAB Simulation.