Transmission Line Fault Location Research Articles

SEP Optimization of Power System Location and Timing Module Based on MLE-KNN Synthesis Algorithm

To ensure the safe operation of the power system, it is necessary to monitor and manage all kinds of power facilities. Real-time power monitoring can play a role in the early warning of geographical disasters. At the transmission end, the state detection and fault location of transmission lines are related to the normal operation of the power system. The precise time synchronization of the power system can be guaranteed through the satellite positioning time service, so that the time of various power operation actions is consistent. The accuracy can reach several microseconds, which provides a basis for the analysis of power grid operation. In this paper, by installing BeiDou functional modules in power equipment and developing the BeiDou operation platform for the distribution network, the precise management of power timing and positioning is realized by docking with the geographic information systems platform of the power grid. The three-dimensional sphere error probability (SEP) algorithm is selected to evaluate the positioning error data. Based on the three traditional SEP calculation methods, the maximum likelihood estimation algorithm is optimized and improved, which can achieve nanosecond synchronization accuracy. It can also be applied to other precision of synchronization scenarios of the power system to meet the development needs of the future clock system of the power system. Through the simulation of experimental data and comparison with other algorithms, the accuracy is verified and the reliable estimation of parameters is realized. Considering the information loss caused by dimension reduction evaluation, the simulation analysis in this paper is compared with other methods, and the accuracy is significantly improved. The power system positioning and timing module developed in this paper can not only be used in the power system but also has a certain reference and application value for other devices in the same industry that need timing and positioning services.

Fault location of untransposed double-circuit transmission lines based on an improved Karrenbauer matrix and the QPSO algorithm

Some double-circuit transmission lines are untransposed, which results in complex coupling relations between the parameters of the transmission lines. If the traditional modal transformation matrix is directly used to decouple the parameters, it can lead to large errors in the decoupled modal parameter, errors which will be amplified in the fault location equation. Consequently, it makes the fault location results of the untransposed double-circuit transmission lines less accurate. Therefore, a new modal transformation method is needed to decouple the parameter matrix of untransposed double-circuit transmission lines and realize the fault location according to the decoupled modal parameter. By improving the basis of the Karrenbauer matrix, a modal transformation matrix suitable for decoupling parameters of untransposed double-circuit transmission lines is obtained. To address the difficulties in solving the fault location equation of untransposed double-circuit transmission lines, a new fault location method based on an improved Karrenbauer matrix and the quantum-behaved particle swarm optimization (QPSO) algorithm is proposed. Firstly, the line parameter matrix is decomposed into identical and inverse sequence components using the identical-inverse sequence component transformation. The Karrenbauer matrix is then transformed to obtain the improved Karrenbauer matrix for untransposed double-circuit transmission lines and applied to identical and inverse sequence components to solve the decoupled modal parameter. Secondly, based on the principle that voltage magnitudes at both ends are equal, the fault location equation is expressed using sequence components at each end, and the QPSO algorithm is introduced to solve the equation. Finally, the feasibility and accuracy of the proposed method are verified by PSCAD simulation. The simulation results fully demonstrate that the innovative improvement on the basis of the traditional modal transformation matrix in this paper can realize the modal transformation of the complex coupling parameters of the untransposed double-circuit transmission lines. It causes almost no errors in the decoupling process. The QPSO algorithm can also solve the fault location equation more accurately. The new fault location method can realize the accurate fault location of untransposed double-circuit transmission lines.

Fault location in hybrid transmission lines on the basis of VMD energy entropy and SVM

Finding the head of a traveling wave is challenging because an overhead line-cable hybrid transmission line’s wave impedance is not constant. Because of this, it is difficult to measure the hybrid transmission line precisely. This leads to the proposal of a hybrid transmission line fault location algorithm, which combines VMD energy entropy for training support vector machines and traveling wave law graphs. The VMD energy entropy is first used to train SVM to identify the faulty section. The method of traveling waves with a single end is utilized to precisely fix the fault distance within the faulty segment when the type of traveling wave has been identified. The simulation results demonstrate that the method provides precise measurements and is effective for hybrid transmission lines with a range of fault distances and grounding resistances.

Fault Location Study of Overhead Line–Cable Lines with Branches

A new fault location method based on the three-terminal travelling wave method is proposed for the fault location problem of multi-branch overhead line–cable transmission lines. Firstly, the process of fault travelling wave propagation in overhead transmission lines and the phenomenon of refraction are analysed, and an improved phase-mode transformation is introduced to decouple the electromagnetic coupling and perform fault phase selection. Secondly, the Pearson correlation coefficient is introduced to compare the similarity of the current travelling waveforms at different measurement points in order to implement fault segmentation. To solve the problems of the complexity of the fault travelling wave propagation process and the difficulty of identifying the travelling wavehead, the Hilbert–Huang transform is used to extract the fault signal characteristics, and the travelling wave arrival moment is accurately calculated by the sampling error correction method to determine the fault location. Finally, the accuracy and stability of the method are verified via a simulation test on the MATLAB/Simulink platform. The results show that the proposed positioning method combining the three-terminal travelling wave method with HHT and sampling error correction can locate the fault location more accurately, and it has good potential for application in the engineering field. It provides a new technical means for fault location in overhead transmission lines, which is expected to become one of the most important technologies in the future power system.

Accuracy analysis using the EMD and VMD for two-terminal transmission line fault location based on traveling wave theory

This paper presents an accuracy analysis from the application of techniques for the extraction of characteristic data from current and voltage signals in transmission line fault location based on traveling wave theory. The techniques used were the empirical mode decomposition and the variational mode decomposition associated with Teager energy operator, which helps to identify the instantaneous energy of the first intrinsic mode function. The simulation of the power system was carried out using the MATLAB/Simulink® software, for a test system consisting of a 200 km long transmission line between two Thevenin equivalents. Data is obtained from both terminals. The fault resistance was fixed at 100 Ω, but the incidence angle, the sampling rate and the fault location were varied for all fault types. The numerical and graphical results proved that the techniques can extract the characteristic data of the current and voltage signals and estimate the fault distance to the terminal with high accuracy, depending only on the sampling rate adopted.

Adaptive Fault Locator for High-Voltage Transmission Lines Based on the Estimation of Power System Model Parameters

Abstract This paper presents an adaptive transmission line fault location method, which incorporates fault location devices at both line ends and utilises data import from a supervisory control and data acquisition system without strictly requiring data synchronisation. The developed method aims at achieving a higher degree of robustness, adaptiveness and accuracy. The adaptiveness is achieved by dynamic updating of mathematical models used on the basis of network-wide information, such as data on the state of circuit-breakers and apparent power at load and generation nodes. The robustness and accuracy are enhanced by incorporating two stages of identification of model parameters with the goal of reducing the decision variable space for the stage identifying fault parameters. Furthermore, in addition to utilisation of all measurements available at a particular substation, the developed method partially employs the measurements from the other end of the line by means of result cross-checks, but does not require a full data set, unlike deterministic-model-based methods. An optimisation-based approach, redundancy on the basis of extended measurement set, and cross-checks reduce the risk of fault location errors due to measurement errors or “voids” in the data available. Testing of the developed method demonstrates its accuracy and robustness in a wide range of pre-fault and fault regime scenarios, even when considering various pre-fault contingencies.

Neural Network based Transmission Line Fault Classifier and Locator using Sequence Values

Faults can easily occur at transmission line because the line is exposed to the environment. The fast fault location after a fault occurrence will minimize the time to repair the faulty part thus reduce the stress of power system due to long outage time. This paper demonstrates the development of fault classifier and fault locator using neural network. The positive, negative and zero sequence values of three-phase voltage and current during fault time were used as the inputs to train the neural networks. Various fault conditions which have different fault types, fault resistance values and fault locations have been simulated to generate the training data for both neural network based fault classifier and fault locator. From the results, the fault classifier and locator successfully classified and located all the simulated fault conditions. One of the advantages of using sequence values as the inputs for the neural networks is only one fault type need to be simulated and used as the training data for single line-to-ground fault (RG, YG and BG), line-to-line fault (RY, YB, BR) and double line-to-ground fault (RYG, YBG, BRG).

Improving Traveling Wave-Based Transmission Line Fault Location by Leveraging Classical Functions Available in Off-the-Shelf Devices

This letter presents a practical methodology to improve traveling wave (TW)-based fault location (TWFL) on transmission lines by leveraging classical single- and double-ended TWFL functions available in off-the-shelf relays and digital fault recorders. It eliminates negative effects of uncertainties in line propagation velocity and travel time, being free of time-consuming or complicated procedures. Real TW records are studied to demonstrate that the proposed solution can improve the accuracy and reliability of TWFL estimations when uncertainties about line propagation velocity or travel time exist.

Robust Fault Location Method for Transmission Lines Using PMUs

The random noise and abnormally greater numbers may affect the accuracy of traditional transmission line fault location. A robust fault location method for transmission lines based on PMUs (Phasor Measurement Unit) is proposed in this paper. The node voltage equations based on voltage fault components are adopted to establish the quadratic nonlinear overdetermined equations of fault location, only using limited PMUs adjacent to the faulted line. In order to quantify the impact of measurement errors, the residual errors are introduced into the fault location equations. Levenberg-Marquardt (L-M) algorithm has been used to solve the equations. Then the original fault location data at each time after the occurrence of one cycle is obtained. A filtering method is proposed to filter the possible interference such as noise and abnormally greater numbers in fault location sequence. The abnormal data that deviating from the mean can be detected by the probability distribution and replaced by smooth filtering data. The simulation results on IEEE 39-bus systems show that proposed algorithm can effectively improve the location accuracy, is not affected by the fault location, transition resistance, fault type, and has strong anti-interference ability and good robustness.

DEVELOPMENT OF A COMPREHENSIVE APPROACH TO DIAGNOSING THE OVERHEAD LINE FAULTS LOCATION IN SINGLE-PHASE GROUND FAULTS BASED ON A DIGITAL SUBSTATION DATA PROCESSING ALGORITHM

Link for citation: Sushkov V.V., Sukhachev I.S., Sidorov S.V. Development of a comprehensive approach to diagnosing the overhead line faults location in single-phase ground faults based on a digital substation data processing algorithm. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 7, рр. 66-77. In Rus. Relevance. Emergency of electric complex of outgoing transmission lines is associated with the occurrence of damage to the line isolation and the resulting transients, marked by the presence of higher harmonic components of currents and voltage, which reduce the reliability and energy efficiency of electrical equipment of oil and gas companies: degrade the mechanical characteristics and efficiency of electric motors, accelerate aging of their isolation, disrupt the operation of control systems and emergency automatics, fault diagnostics systems. One of the reasons of high-level emergency situations, outages and emergency repairs in electric complexes of outgoing transmission lines of oil and gas companies is appearance of phase-to-ground faults. A large number of changing factors are known to influence the reliability of phase-to-ground fault location methods: parameters of transmission line operating mode, its structural and electrical parameters, fault type, transient resistance value, ground resistance and others. Inclusion in the transmission line fault location algorithms of averaged values of a number of the factors listed above independent of changes of humidity of soil and air, its temperature and other factors causes an error of methods of fault location up to 30 %. Accordingly, the research to develop a fault location method for overhead transmission lines with isolated neutral points during phase-to-ground faults based on a digital substation data processing algorithm, accounting for tower parameters and natural-climatic factors, is relevant. Objective: improving the reliability of power grids and providing consumers with power of the required standard by applying a digital fault location system to the outgoing transmission lines electrical complex. Methods: mathematical analysis of a power transmission line, taking into account its design features and natural-climatic factors on the basis of the method of mirror images; mathematical analysis of steady-state and transient modes of transmission line operation considering self and mutual parameters terms of wires; transmission line currents and voltages Fourier analysis; validation of developed method of phase-to-ground fault location in power grid of Tyumen region energy company. Results. The authors have developed the phase-to-ground faults location method for transmission lines in power grids with isolated neutral points, which differs in the following – first the faulty overhead line feeder branch is identified by correspondences between the negative sequence voltage values of the phase voltages at the transformer substation inputs, and then the distance to the location of the single-phase ground fault is determined along the branch line based on the resonant frequencies of the line taking into account its design features and natural and climatic factors.

Application of Nonlinear Optimization for Fault Location in Transmission Lines with Series Compensation Protected by Varistors

This paper introduces a novel approach to fault localization in transmission lines with series compensation using nonlinear optimization. The objective function minimization provides information on the fault distance and the current at which the protective varistor starts conducting. Terminal source data, the maximum current capacity of the capacitor, and the operating curve of the metal oxide varistor protection element are not required. The proposed method successfully met the predefined objectives, with a maximum error of 1.13% in simulated scenarios. In validating the method using real cases from a Brazilian energy concessionaire, the errors were below 0.5%.

A new robust approach for fault location in transmission lines using single channel independent component analysis

A new robust approach for fault location in transmission lines using single channel independent component analysis

Principal Component Analysis for Inter Circuit Fault Location in Dual Circuit Transmission Line

Principal Component Analysis for Inter Circuit Fault Location in Dual Circuit Transmission Line

Adaptive single-phase auto-reclosing scheme based on the moving average filter-quadrature signal generator for transmission lines with shunt reactors

An adaptive single-phase auto-reclosing method based on the moving average filter (MAF)-quadrature signal generator (QSG) is developed to determine secondary arc extinction time for high-voltage transmission lines with shunt reactors. Firstly, the difference between permanent and transient faults is derived and analyzed by the equivalent circuit model. Then, MAF-QSG is utilized to extract these features from the fault voltage. During the second arc period, for transient fault, the fundamental component and subharmonic component with around 50 Hz are reserved by MAF-QSG; however, in the case of permanent fault, only the fundamental component is retained. Finally, the identification index and its threshold are designed above the extraction fault features. The performance of the proposed method is evaluated by simulation and field data studies, accounting for different transmission line compensation levels, transition resistances, and fault location conditions.

UAV Aerial Image Generation of Crucial Components of High-Voltage Transmission Lines Based on Multi-Level Generative Adversarial Network

With the aim of improving the image quality of the crucial components of transmission lines taken by unmanned aerial vehicles (UAV), a priori work on the defective fault location of high-voltage transmission lines has attracted great attention from researchers in the UAV field. In recent years, generative adversarial nets (GAN) have achieved good results in image generation tasks. However, the generation of high-resolution images with rich semantic details from complex backgrounds is still challenging. Therefore, we propose a novel GANs-based image generation model to be used for the critical components of power lines. However, to solve the problems related to image backgrounds in public data sets, considering that the image background of the common data set CPLID (Chinese Power Line Insulator Dataset) is simple. However, it cannot fully reflect the complex environments of transmission line images; therefore, we established an image data set named “KCIGD” (The Key Component Image Generation Dataset), which can be used for model training. CFM-GAN (GAN networks based on coarse–fine-grained generators and multiscale discriminators) can generate the images of the critical components of transmission lines with rich semantic details and high resolutions. CFM-GAN can provide high-quality image inputs for transmission line fault detection and line inspection models to guarantee the safe operation of power systems. Additionally, we can use these high-quality images to expand the data set. In addition, CFM-GAN consists of two generators and multiple discriminators, which can be flexibly applied to image generation tasks in other scenarios. We introduce a penalty mechanism-related Monte Carlo search (MCS) approach in the CFM-GAN model to introduce more semantic details in the generated images. Moreover, we presented a multiscale discriminator structure according to the multitask learning mechanisms to effectively enhance the quality of the generated images. Eventually, the experiments using the CFM-GAN model on the KCIGD dataset and the publicly available CPLID indicated that the model used in this work outperformed existing mainstream models in improving image resolution and quality.

Transmission Line Fault Location Using MFCC and LS-SVR

The location of Transmission Line (TL) Faults is a major problem in Electrical Power Systems (EPSs), since precisely identifying the point of occurrence of a fault in a TL it is possible to perform a faster restoration of the operation to the desired normal conditions. In this work we used a Least-Squares Support Vector Regression (LS-SVR) to locate faults in a TL with inputs provided by MFCC (Mel-Frequency Cepstral Coefficients) obtained from voltage signals during the fault. A modelled line based on parameters of a real line was used, with a total of 4008 fault situations being simulated on this Transmission Line. It is important to point out that MFCC are not used in applications involving EPS’s, and, according to the bibliographic research conducted by the team so far, no application of this feature extraction tool has been detected for the TL fault location problem. 3006 faults were used to train the model with cross-validation by the k-fold method, and 1002 faults were used for testing. The proposed methodology presented a good performance in the tests carried out, with a mean relative error of 0.000419 ±0.000640% when models are trained and tested with noiseless voltage signals. For models trained with voltage signals that present SNR ranging from 100 dB to 25 dB, the relative mean error ranged from 0.00334 ±0.00459%, in the first case, to 0.030580±0.043160% in the last.

Fault Location Method of Multi-Terminal Transmission Line Based on Fault Branch Judgment Matrix

Aiming at the difficulty of fault location of multi-source transmission lines, this paper proposes a fault location method for multi-terminal transmission lines based on a fault branch judgment matrix. The fault traveling wave signal is decomposed by Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and the IMFs sensitive components that can characterize the fault characteristics of the target signals are selected by constructing a correlation-rearrangement entropy function. The arrival time of fault signals at the endpoint has been accurately calibrated by combining them with the Teager Energy Operator (TEO). To eliminate the influence of wave velocity and fault time on the location results, this paper proposes a two-terminal location method based on the line mode component to improve the location accuracy. On this basis, combined with the fault branch judgment matrix, the accurate location of multi-terminal transmission line faults is realized. This method has been shown to have high accuracy in detecting traveling wave heads, accurately judging fault branches, and producing a small error in fault location results. Compared with the existing multi-terminal transmission line fault location algorithm, it has obvious advantages and meets the needs of actual working conditions.

Fault location of high voltage overhead transmission line based on ACO-ENN algorithm

Fault location of high voltage overhead transmission line based on ACO-ENN algorithm

Artificial Neural Network-based Fault Location in Terminal-hybrid High Voltage Direct Current Transmission Line

In this article, a fault location technique based on artificial neural networks (ANN) for Terminal-Hybrid LCC-VSC-HVDC has been assessed and scrutinized. As is known, in conventional HVDC systems (LCC-based and VSC-based HVDCs), the same type of filter is used on both sides due to the use of similar converters in both sender and receiver terminals. In this article, it is concluded that due to the use of two different types of converters at the both ends of the utilized Terminal-hybrid LCC-VSC-HVDC system, and the use of different DC filters on both sides, fault location using positive and negative pole currents of the rectifier side has much better results than the rest of input signals. Therefore, it will be finalized that by increasing and designing suitable DC filters on the transmission line of HVDC systems, fault localization matter will be remarkably and surprisingly facilitated. Nowadays, the fault location of HVDC transmission lines with a value of more than 1% is generally discussed in most articles. In this research, the fault location with a value of 0.0045%, i.e., a distance of 22.5 meters from the fault point in the most satisfactory case is obtained, which shows the absolute feasibility of the ANN along with the wavelet transform. To validate the proposed method, a ±100 KV, Terminal-hybrid LCC-VSC-HVDC system is simulated via MATLAB. The outcomes verify that the proposed technique works perfectly under various fault locations, resistances, and fault types.

Setting Free Fault Location for Three-Terminal Hybrid Transmission Lines Connected With Conventional and Renewable Resources

Three-terminal hybrid transmission lines (TTHTLs) are attractive from both environmental and commercial view. Hybrid transmission lines are growing due to urbanization, connecting an industrial load and renewable integration. A TTHTL comprises sections of both overhead lines and underground/subsea cables or overhead lines with different X/R ratios. Faulted section identification (FSI) is key for defining the adaptive/selective auto-reclosing scheme and estimation of the fault location for TTHTLs. In this paper, FSI and fault location algorithms are proposed without using the parameters of any line section. Novelty of the methodology lies in a two-stage approach to the problem. In the first stage, series impedance parameters of all the sections are calculated using closed loop formulae. These parameters are then utilized in identifying the faulted section. In the second stage, the above calculated line section parameters and faulted section are used to estimate complete line parameters including shunt capacitance and subsequently the fault location. The advantage of the proposed method is that it does not require an initial guess of the line section parameters, is non-iterative in the first stage, and provides correct fault section identification for TTHTLs. These features make it suitable for designing the selective auto-reclosing protection scheme for the TTHTLs within traditional protection relaying hardware. More importantly, the series impedance parameters calculated in the first stage constitute good initialization values for the non-linear problem of estimating the complete line parameters. This results in better convergence of the algorithm and accurate parameter estimation. The developed solution is verified using the PSCAD/EMTDC simulations for TTHTLs connected with conventional and different inverter-based renewable resources. The performance of the proposed solution is compared with commercially available solutions, and it is found to be accurate. This solution is amenable for implementation in line differential protection relays without additional infrastructural changes.