Distribution Line Fault Research Articles

A new fault location method for high‐voltage transmission lines based on ICEEMDAN‐MSA‐ConvGRU model

AbstractGiven the complex form of distribution line faults, the accuracy of fault location using traditional artificial intelligence networks needs to be further improved. Here, a combined fault location method is proposed for a 110 kV distribution line based on the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), mantis search algorithm (MSA), and convolutional gate recurrent unit (ConvGRU). Firstly, the study used the ICEEMDAN algorithm to decompose the signals and discard the high‐frequency signals with low correlation so as to achieve the purpose of noise cancellation. Then, the study used the root mean square error (RMSE) of the ConvGRU model training as the adaptation value, optimized the internal parameters of the model using the MSA algorithm, and obtained a combined fault locating model. By using the proposed model, the effects of the fault form and transition impedance changes on the location accuracy were analysed, and the location accuracy was compared with other artificial intelligence methods. The location accuracy index showed that the proposed model had a better convergence speed of training error than the traditional model. Also, the RMSE of the localization results was reduced by 50%, with a higher fault location accuracy.

Evaluation of fault location algorithm in distribution power system lines using differential equation method with fault indicator approach

A malfunction in any electrical system network will eventually happen. Damage and minor problems are less likely to develop if a problem can be resolved quickly. As a general rule, fault location is a procedure of aiming the location fault at the maximum feasible accuracy. In order to locate faults in distribution lines for multi-ended power systems, this work provides a single line to ground (SLG) fault location algorithm employing a differential equation (DE) with a fault indication approach. The overall distribution lines model combines the generalized compact models of all homogenous line sections. Furthermore, this study approached fault indicator equipment as an indicator during every section fault. Hence, the ATP Draw has simulated the medium voltage distribution lines consisting of overhead lines (OHL) and multiple underground cable lines (UCL). The evaluation of the method considered the parameter of fault resistance, fault distance, and fault inception angle. The results show that the fault location algorithm using DE fault location algorithm with fault indicator information produced the most accurate result.

High-impedance fault location method of three-phase distribution lines based on electromagnetic time reversal

• Expanding the application scenario of the criterion of the minimum mirrored FCSE. • Accurately locating the single-phase HIF and identifying the fault phase. • Not affected by noise, GPS time synchronization, and the time delay of the device. • Location and diagnosis of single-phase HIF, phase to phase HIF, and three-phase HIF. Accurate location of high-resistance grounding faults in distribution lines is of great significance for improving the power supply reliability of power systems. In this study, a simulation model of a 10 kV three-phase distribution line is built using a numerical simulation platform. Further, a fault location method of three-phase distribution lines is proposed on the basis of the criterion of the minimum mirrored fault current signal energy (FCSE). The positioning accuracy of the high-impedance fault (HIF) is studied under different influencing factors. The results show that the proposed method can accurately locate the single-phase HIF of the three-phase distribution line, and the positioning error is within 50 m. However, it can only locate the fault when the fault resistance is 5 kΩ and below. In addition, the positioning accuracy of the proposed method for the HIF is not affected by noise and the sampling frequency, although the location accuracy under different fault inception angles is affected by fault resistance. Further, when the GPS time synchronization error is within 2 μs or the time delay of the transient signal device is within 2 ms, accurate positioning of the single-phase HIF can be realized. Moreover, by analyzing the three-phase FCSE distribution calculated in the reversed time, positioning and diagnosis of three HIF types, namely the single-phase grounding fault, phase-to-phase fault, and three-phase grounding fault, can be realized. Finally, fault phase identification of the single-phase HIF can also be achieved.

Detection and Classification of Fault Types in Distribution Lines by Applying Contrastive Learning to GAN Encoded Time-Series of Pulse Reflectometry Signals

This study proposes a new method for detecting and classifying faults in distribution lines. The physical principle of classification is based on time-domain pulse reflectometry (TDR). These high-frequency pulses are injected into the line, propagate through all of its bifurcations, and are reflected back to the injection point. According to the impedances encountered along the way, these signals carry information regarding the state of the line. In the present work, an initial signal database was obtained using the TDR technique, simulating a real distribution line using (PSCAD™). By transforming these signals into images and reducing their dimensionality, these signals are processed using convolutional neural networks (CNN). In particular, in this study, contrastive learning in Siamese networks was used for the classification of different types of faults (ToF). In addition, to avoid the problem of overfitting owing to the scarcity of examples, generative adversarial neural networks (GAN) have been used to synthesise new examples, enlarging the initial database. The combination of Siamese neural networks and GAN allows the classification of this type of signal using only synthesised examples to train and validate and only the original examples to test the network. This solves the problem of the lack of original examples in this type of signal of natural phenomena which are difficult to obtain and simulate.

Distribution Line Fault Location With Unknown Fault Impedance Based on Electromagnetic Time Reversal

Rapid and accurate location of power distribution line faults is essential for power system reliability improvement. Based on the electromagnetic time reversal (EMTR), an improved expression of fault current considering the influence of both sides of the transverse branch in the reversed time was derived in this research. In the reversed time, the transient voltage signals were injected into both ends of the line and multiplied one signal by −1, as suggested in An <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> 's work, and an assumed impedance of the transverse branch was set to 1000 Ω. A new criterion of the mirrored minimum fault current signal energy was proposed to determine the fault location. In the direct time, by setting different ground fault impedances, the distribution of the fault current signal energy in the frequency domain was calculated. Furthermore, the time-domain simulation verification was performed in the power systems computer-aided design software. The results indicate that when the actual fault impedance was unknown, the accurate fault location of the distribution line can be achieved by the proposed EMTR-based method, and it is less affected by time synchronization.

A PCA‐NPOGBDT strategy‐based protection scheme to differentiate between inverter and distribution line faults plus detection and identification of faulty section in microgrid

An effective hybrid strategy-based protection scheme to differentiate between inverter faults and symmetric/unsymmetric faults on distribution line, in addition to detect and identify that faulty section in a microgrid. The proposed hybrid strategy is combined execution of principal component analysis (PCA) and nomadic people optimizer (NPO) learning process-based gradient boosting decision tree (GBDT). Hence it is commonly named as PCA-NPOGBDT strategy. Here, three stages are occupied using fault analysis on microgrid to differentiate among inverter faults on microgrid and symmetric/unsymmetric faults on distribution line, in addition to detect/classify that faults and recognize that faulty section. They are: data set generation, feature removal and training process. In this paper, the first procedure of the proposed strategy is the microgrid parameters such as voltage and current signals at usual and unusual condition data set preparation with PCA technique. The data set based on PCA preparation process has feature removal of the power flow parameters and describes that characteristics nature of the various signals happened with microgrid system. The removed data set is evaluated with the NPO-based GBDT system to classify that sort of fault happened at microgrid system. The proposed model is performed at MATLAB/Simulink working stage and compared with various existing techniques. Computation time of fault detection using proposed and existing system is analyzed and likened to other existing systems like RF, DT, SVM and DBN under 100, 150, 200, 250, and 500 trails. The computation time under 100, 150, 200, 250 and 500 trails of proposed technique is 48.1740, 51.2133, 71.0483, 60.00126, and 57.80132.

Analysis and Solutions of 10kV Distribution Line Fault

Analysis and Solutions of 10kV Distribution Line Fault

Research on Fault Waveform Recording Testing of Single Phase to Earth for Distribution Line Fault Indicator

To evaluate the recognitional capacity of single-phase grounding fault based on transient recording method in distribution system, the corresponding test method about fault waveform recording is presented for distribution line fault indication. The principle and implementation process of transient recording method is introduced. Ten 10 key indexes are selected from typical characteristic signals of earth fault, and a similarity comparison method of fault waveforms is designed. The proposed method is verified by laboratory tests, which shows its feasibility and effectiveness for test of the recognitional capacity of single phase to earth fault.

Intelligent Diagnosis of Incipient Fault in Power Distribution Lines Based on Corona Detection in UV-Visible Videos

As one of the non-contact methods for incipient fault diagnosis of power distribution lines, UV-Visible imaging has become popular due to its good performance and robustness against environmental parameters. This paper presents a deep learning-based method for UV-Visible video processing. First, for preparing the dataset, some videos are acquired from distribution lines using CoroCam 6D2 considering observation distance, the imager's gain, air pressure, and humidity as effective parameters on the discharge area in the images. Then, based on the logged information of unplanned power outages in the system and also planned inspections over a year, the incipient fault type and the severity level of the incipient fault are determined for each video. For processing each video, frames are extracted with the rate according to the nominal voltage of the line. Power devices are detected in each frame using Faster R-CNN and are tracked through the whole video frames to compensate the camera movement. Then, color thresholding is used for each device to identify corona discharges in the frames. In-depth median filtering is also used through the video to eliminate noises in the UV channel. Finally, based on the ratio of the detected discharge area to the area of the equipment, the severity level of the incipient fault is determined. The proposed method not only performs better than the state-of-the-art but also is a practical method, and with the least dependence on environmental conditions, can automatically identify incipient faults in distribution lines, even in videos containing several possible defective devices.

Wide-Band Current Transformers for Traveling-Waves-Based Protection Applications

Owing to its system independence and unmatched speed, Traveling-wave (TW)-based relaying has become a top contender for transmission and distribution systems. However, existing measurement devices, such as Current Transformers (CTs), are incapable of capturing the full frequency content of TWs, as their bandwidths are limited. Consequently, existing TW-based schemes rely on distorted waveforms and partial-frequency spectra, i.e., low-frequency content, of TWs to perform protection tasks. Such incomplete information can lead to misoperation of protection schemes. This article investigates the impacts of the limited bandwidth of CTs on the shape and frequency content of TWs under faults in transmission and distribution lines. Additionally, it proposes a compensation technique, which utilizes an Unknown Input Kalman Filter (UIKF), to accurately estimate the primary current of a CT from the measured secondary one, i.e., to capture the waveshape and full frequency-content of TWs. The proposed method removes the bandwidth barrier from the measurement of current-TWs, and thus allows relays to access the High-Frequency (HF) spectra of TWs in order to devise more-effective TW-based schemes. Simulation results corroborate that the proposed method accurately compensates for low frequency-content and distorted waveform of TWs in the secondary currents of CTs under various fault types, resistances, inception angles, and locations.

Research on the principle of distribution network fault handling

Compared with the transmission network, the distribution network has a wide distribution area, a large number of electrical equipments, a complex operating environment and a high probability of fault. According to the operation characteristics and common fault types of distribution network, this paper first describes the main task and basic mentality of distribution network fault handling, and then puts forward the handling principles of distribution line fault, single phase-to-ground fault and voltage transformer fault, which provides technical support for dispatchers to deal with distribution network fault reasonably.

A System for Detection of Overhead Distribution Line Fault

— The presented paper is related to fault detection of an overhead distribution line. The fault is detected by the installation of device at homes or any other buildings when occurs on overhead distribution lines. Correspondingly the signal is received by the substation coming from the homes and switch off the line when fault is detected. A system model is developed which is working in good situation. Radio frequency technique for communication is used in the system.

Enhancing resilience of PV-fed microgrid by improved relaying and differentiating between inverter faults and distribution line faults

The present load demand and intermittency in the operation of photovoltaic (PV) sources has led to the wide usage of power electronic converters in PV integrated microgrids. A resilient microgrid operation requires early restoration to the healthy state post occurrence of faults in the converter or distribution line. The reported microgrid protection schemes aim at fast and accurate detection and classification of faults. Alongwith the intended protection task of fault detection and classification, the protection scheme designed for the distribution system should be selective to faults in the line only. However, imparting selectivity is quite often challenging because of the similar voltage-current profile during converter switching faults and symmetrical/unsymmetrical line faults. The similarity leads to nuisance tripping and unreliable operation of microgrid with classical protection schemes. In this regard, a Convolutional neural network (ConvNet) based protection scheme has been proposed for islanded microgrids to discriminate between inverter faults in the PV system and symmetrical/unsymmetrical faults in the distribution line, in addition to detecting/classifying the faults and identifying the faulty section. The voltage and current signals recorded at the relaying buses are converted into grayscale images to form the input dataset, which is utilized by ConvNet to derive the required relaying action. The performance of the proposed scheme has been examined and compared with Decision tree (DT) and Support vector machine (SVM) based microgrid protection schemes in terms of reliability indices i.e., dependability, security and accuracy for different scenarios. The proposed scheme has also been substantiated on OPAL-RT digital simulator to examine its feasibility for real-time field applications.

Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms

Accurate recognition of distribution line fault types can provide directional guidance for line operation and maintenance personnel. Based on the analysis of time-frequency features of fault waveform, a recognized method of distribution line fault type was proposed in this paper. Through modeling and theoretical analysis of waveforms of different fault types, characteristic parameters, which could characterize waveforms of different fault types from three aspects, time domain, frequency domain, and electric arc, were put forward. Calculation formula for extracting characteristic parameters according to fault waveform data was proposed, recognition logic was established by taking multi-parameter fusion as a basis, and then,automatic recognition of distribution line fault types caused by different factors was realized through detection and classification of characteristic parameters of input waveform data. Finally, 136 groups of field fault waveform data provided by the Electric Power Research Institute were used to do closed-loop control and verification of the algorithm, and results indicated that recognition success rate reached 90%, which verified the feasibility of using time-frequency characteristics of fault waveform to realize recognition of distribution line fault types.

Main Line Fault Localization Methodology (MLFLM) in Smart Grid – The Underground Medium- and Low-Voltage Broadband over Power Lines Networks Case

This paper assesses the performance of the main line fault localization methodology (MLFLM) when its application is extended to underground medium- and low-voltage broadband over power lines (UN MV and UN LV BPL) networks, say UN distribution BPL networks. This paper focuses on the localization of main distribution line faults across UV MV and UN LV BPL networks. By extending the MLFLM procedure, which has successfully been applied to overhead medium-voltage (OV MV) BPL networks, the performance assessment of MLFLM is investigated with respect to the nature of the main distribution line faults, the intensity of the measurement differences and the fault location across the main distribution lines of the underground distribution power grid (either MV or LV grid). Citation: Lazaropoulos, A. G. (2017). Main Line Fault Localization Methodology (MLFLM) in Smart Grid – The Underground Medium- and Low-Voltage Broadband over Power Lines Networks Case. Trends in Renewable Energy, 4, 15-42. DOI: 10.17737/tre.2018.4.1.0045

Main Line Fault Localization Methodology in Smart Grid – Part 2: Extended TM2 Method, Measurement Differences and L1 Piecewise Monotonic Data Approximation for the Overhead Medium-Voltage Broadband over Power Lines Networks Case

Enriching the fault identification methodology of the first paper, this second paper investigates the performance of the identification of main distribution line faults when broadband over power lines (BPL) networks are deployed. The main issue that is concerned in this paper is the impact of measurement differences on the fault identification process performance. The main contribution of this paper, which is focused on the identification of the main distribution line faults when measurement differences occur, is the application of the L1 piecewise monotonic data approximation (l1PMA) in order to cope with the measurement differences that influence the reflection coefficients derived from the extended TM2 method. Through the L1PMA application, measurement differences are confronted in order to prevent the trigger of a false alarm about the existence of a main distribution line fault. The combined operation of the extended TM2 method and L1PMA concludes the introductory phase (fault identification) of the main line fault localization methodology (MLFLM).

Main Line Fault Localization Methodology in Smart Grid – Part 3: Main Line Fault Localization Methodology (MLFLM)

Since the main distribution line faults can be securely identified as outlined in the first and second paper, this third paper presents the methodology of localizing the main distribution line fault when broadband over power lines (BPL) networks have already been deployed across the distribution power grids. The main issue of this paper is the detailed presentation of the main line localization methodology (MLFLM) as well as well as its performance assessment when measurement differences occur. The contribution of this paper, which is focused on the application of MLFLM, is double. First, the procedure, which is followed in order to create the database of faults and is used by MLFLM, is here analytically presented. This database is based on the application of the main distribution line fault identification percentage metric (MDLFI) to coupling reflection coefficients of all possible fault OV MV BPL topologies (modified OV MV BPL topologies). Second, the performance assessment of MLFLM is investigated with respect to the nature of the measurement differences and the location of main distribution line faults across the distribution power grid.

Main Line Fault Localization Methodology in Smart Grid – Part 1: Extended TM2 Method for the Overhead Medium-Voltage Broadband over Power Lines Networks Case

These three papers cover the overall methodology for the identification and localization of faults that occur in main transmission and distribution lines when broadband over power lines (BPL) networks are deployed across the transmission and distribution power grids, respectively. In fact, this fault case is the only one that cannot be handled by the combined operation of Topology Identification Methodology (TIM) and Instability Identification Methodology (FIIM). After the phase of identification of main distribution line faults, which is presented in this paper, the main line fault localization methodology (MLFLM) is applied in order to localize the faults in overhead medium-voltage BPL (OV MV BPL) networks. The main contribution of this paper, which is focused on the identification of the main distribution line faults, is the presentation of TM2 method extension through the adoption of coupling reflection coefficients. Extended TM2 method is analyzed in order to identify a main distribution line fault regardless of its nature (i.e., short- or open-circuit termination). The behavior of the extended TM2 method is assessed in terms of the main line fault nature and, then, its results are compared against the respective ones during the normal operation, which are given by the original TM2 method, when different main distribution line fault scenarios occur. Extended TM2 method acts as the introductory phase (fault identification) of MLFLM.

Modeling of flashover arcs in medium voltage networks due to direct lightning strikes

Abstract Distribution line faults in many cases are caused by direct lightning strokes to overhead lines resulting in a disruption between phase and ground in the form of flashover arc. Therefore, it is important to accurately simulate the lightning behaviour for the protection studies of distribution networks. This paper investigates the influence of considering the dynamic arc model and the actual volt–time characteristics of line insulators in the evaluation of lightning overvoltages. A full-scale experimental set-up was installed in the high voltage laboratory to study the dynamic interaction between fault arc and power system with grounded and ungrounded cross arm configurations. The least square method has been used to extract the arc parameters from the experimental results for modeling purpose. The model of experimental set-up has been implemented in Alternative Transients Program–Electromagnetic Transients Program (ATP–EMTP) software and the experimental results have been reproduced by computer simulations with reasonable accuracy. Based on the comparison of experimental and simulation results, it is concluded that the actual volt–time curves and the arc model that characterize the behaviour of line insulators should be considered during the simulation of the lightning performance of overhead distribution networks.

Research on a Distribution Line Zero Mode Current Traveling Wave Fault Location Method Immune from Wave Velocity Affection

This paper presented a research on zero mode current traveling wave based distribution line fault location method which is not affected by wave velocity. The mathematical expressions of initial distribution line fault current traveling wave, reflection wave of the fault location and the refraction wave of opposite ends are derived. And the directivity relationship and identification method of these three element are fully analyzed. Based on the research process mentioned above, the fault location method introduced in this paper eliminates the error produced both by velocity propagation and clock synchronization. In this way, the veracity and reliability of short distribution line fault location was improved.