Fault location in distribution network using travelling waves

In a multilateral distribution network, faults at different locations can generate the same voltage and current at the substation; hence, the calculated fault location can correspond to several places in the network. To avoid this major problem, a two‐terminal travelling wave‐based fault location method is presented in this article, which at first identifies the faulted lateral in the distribution network and then estimates the exact fault location. The proposed fault location scheme uses wavelet energy entropy of the recorded three‐phase current signals and the magnitude of ground mode component wavelet modulus maxima (WMM) for fault detection and fault type identification in the network. After that, the faulted lateral identification followed by the exact fault location is performed using the aerial mode component WMM of the fault‐generated current transients. Since the integration of electric vehicle (EV) charging load is increasing day by day to the distribution network, the performance of the proposed algorithm is tested with EV charging load along with distributed generation integrated into the distribution network. Modeling and simulation of the distribution network and EV load are performed in MATLAB/SIMULINK. The simulation results show that the proposed method can accurately locate fault under different operating conditions.

The research on fast and accurate fault location technology in distribution networks is of great significance. Currently, many methods for fault location in distribution networks have been proposed, but most theories are difficult to solve the problem of fault location in multi branch distribution networks. Therefore, this paper analyzed the characteristics of traveling wave transmission and proposed a discrimination algorithm that uses the polarity of traveling waves to determine the source of fault traveling waves; Then, using the idea of first locating the fault section and then locating the fault point, a multi branch distribution network traveling wave fault location algorithm is proposed based on the configuration of micro PMU (Phasor Measurement Units) devices in the distribution network by combining the two end method and single end method of traveling wave distance measurement. A multi branch distribution network simulation model based on IEEE14 node standard topology was built using MATLAB/Simulink software, the experimental results also showed the effectiveness and the efficiency of the proposed algorithm.

This paper proposed a new electrical synaptic transmission-based Spiking Neural P system (SNP system) based on SNP systems. Some new elements are added into the original definition of SNP systems, such as new synapses, bidirectional model, two types of neurons and cancelling the delay of axon. Because SNP system is easy to express the logical relationship between graphics and has strong ability to process information in parallel, the bidirectional characteristics of electrical synaptic transmission is effectively combined with the electrical quantity (direction of current) for fault location of distribution network with distributed generations (DGs) in this paper. The fault location model and reasoning algorithm of the electrical synaptic transmission-based SNP system are studied with the advantages of high accuracy, less computation, simple and intuitive model and reasoning. Furthermore, the algorithm is applied reasonably in the bidirectional power flow characteristics of a distribution network with DGs. Finally, this paper verifies the effectiveness, accuracy and reliability of the method through two cases which involve the single fault, multiple fault and misinformation fault. With the large-scale DGs (distributed generation) access to the distribution network, which changes the power flow structure and operation mode, the traditional protection strategy of the passive distribution network is no longer applicable. The fault location problem of distribution network with DGs is carried out. Firstly, Many fault location methods in the existing literatures have been anaylsised in this paper, then the electrical synaptic transmission-based spiking neural P system (ESSNP) has been proposed to solve the fault location problem. Foremore, the fault diagnosis mode for the power outage section with ESSNP has been established, which construct with Network description matrix and Fault current matrix. In order to verify the accuracy of the method in this paper, three cases have been studied, which the single fault, multiple faults and misinformation faults in each case. Finally, conclusions have been discussed.

The addition of distributed generation sources into conventional distribution networks results in several technical challenges for successful operation of distribution network. As far as physical integration is concerned, finding the exact location of fault is a key issue. The coordination between the protection devices existing in the distribution network gets disrupted due to presence of distributed generation (DG). Therefore existing fault location techniques for distribution system will not work properly with penetration of DG. Therefore new fault location schemes for distribution networks with distributed generations (DG) have been developed in the recent times, but there are still problems whose solution needs to be found out. This paper investigates the issues and current state regarding fault location in distribution network with DG. A comparative analysis is carried out in which the merit and demerit of each technique is assessed and some conclusion and suggestion for fault location in distribution system with DG is put forward.

The precise fault location is still an unsolved problem in distribution networks. The application of distributed generation (DG) increases the difficulty of fault location. The fault location in distribution network with DG has been becoming a hot and difficult subject. This paper proposes an impedance-based fault location method for distribution network with DG. First, the impedance models are built. The fault characteristics of the distribution network with DG are analyzed and extracted based on the impedance model. Then the fault section location technology is realized by using the impedance model and the fault characteristics. At last, the differential evolution algorithm is used to precisely locate fault in distribution network with DG. In the algorithm, the variables are the fault distance and the grounded resistance, and the fitness function is the value of the fault characteristic. The differential evolution algorithm can quickly search the precise fault location. The simulation results show that the impedance model of the system, the fault section location method and the fault location method are all effective.

In this paper the one possibility of single phase fault location in unearthed MV distribution network is presented. This method is based on transients which appear in the case of charge redistribution in the instance of fault occurrence. The issues of fault location in distribution networks was emphasized through influence of inhomogeneity, distributed loads, considerable fault resistance and numerous branches on distribution feeders. On the extracted transients of currents and voltages of faulty phase, method based on solving differential equations is applied. The low frequency charge transients, with minimum sample frequency of several kHz is used. This method was examined by computer simulations on the modeled network as well as on the real network and fault. In the case of real fault, it was used data registered by power quality analyzer.

This paper studies the influence of inverter-type distributed power generation including photovoltaic, wind and other clean energy generation on the fault location of the distribution network, analyzes the control characteristics of distributed power, and studies its grid-connected characteristics. Secondly, when the short-circuit fault occurs in the grid-connected state, the influence of the access of distributed generation on the changes of electrical parameters such as voltage and current in the distribution network is studied, and then the interference source caused by the fault location is clarified. At the same time, according to the influence of PV on various parameters of distribution network, the fault characteristics of distribution network are analyzed, and the location scheme of active distribution network section is studied.

When the distribution network fails, the operation and maintenance personnel need to quickly determine the fault location and minimize the scope of the inspection line so that the fault repair personnel can accurately reach the vicinity of the fault point to carry out work. Whether the fault location method is advanced and reliable directly affects the power failure time of the power supply user, and further affects the social, economic, and life aspects. Therefore, the fault location of the distribution network needs to satisfy both reliability and accuracy. It is the basis and premise for troubleshooting, isolating and restoring the power supply. The automation level of China’s distribution network is relatively backward, and the reliability of power supply equipment is relatively low, making it difficult to find fault points. If we find out the intelligent algorithms that can meet the requirements of rapid positioning, accuracy and fault tolerance through theoretical research, we can Improve the fault location efficiency very well.

A fault location method based on traveling wave principle is presented in this paper for a multi-lateral distribution network with Distributed Generation (DG). Fault detection and faulted phase selection is performed using Wavelet Energy Entropy (WEE) of three-phase currents and the involvement of ground in the fault is detected by observing the magnitude of Wavelet Modulus Maxima (WMM) of ground mode component of the modal transformation matrix. The WMM of aerial mode component is used for identification of faulted lateral and the exact fault point location for different types of fault. Effectiveness of the proposed method is tested with the Distributed Generation (DG) connected in the distribution network. The results obtained show that the proposed fault location scheme is robust, more accurate and reliable under various fault condition.

Although single phase to ground fault location in non-solid grounded networks has been studied for many years and a lot of research has been done, yet adequate solution for direct fault location of radial distribution network hasn't been made, especially for the distribution network with the neutral point grounded via arc suppression coil. Involvement of the arc suppression coil may decrease short-circuit current, but the difficulty of finding fault location is increased. The key problem of non-solid single-phase to ground fault location is to solve the fault location of distribution network with the neutral point grounding via arc suppression coil. This paper will analyse line capacitive current distribution of isolated neutral point and neutral point grounded via arc suppression coil and propose the concept of per-unit zero sequence current method. Equipartition principle of zero sequence current is utilized to locate fault section of the distribution system. Simulation tests to verify the effectiveness of this method have been made as well.

When the distribution network fails, the operation and maintenance personnel need to quickly determine the fault location and minimize the scope of the inspection line so that the fault repair personnel can accurately reach the vicinity of the fault point to carry out work. Whether the fault location method is advanced and reliable directly affects the power failure time of the power supply user, and further affects the social, economic, and life aspects. Therefore, the fault location of the distribution network needs to satisfy both reliability and accuracy. It is the basis and premise for troubleshooting, isolating and restoring the power supply. Fault location of distribution network has important research significance. The universal gravitation search algorithm is used to locate faults in the non-measurement and control area of the distribution network, and the intelligent algorithm that meets the requirements of rapid positioning, accuracy and fault tolerance can improve the fault location efficiency.

Precise fault location in distribution network is one of the most important applications among intelligent monitoring and outage management tasks used for realization of self-healing networks. The data gathered from various intelligent sensors installed throughout the power system could be utilized for smart approaches to locating faults, helping the system restoration, reducing outage time and improving system reliability. Since the distribution network is radial, with multiple laterals connected to the main feeder, faults at various locations may lead to the same voltages and currents observed at the substation. In other words, using the substation measurements to calculate the fault location, multiple failure states are possible. In this paper, Markov decision process is used as a tool for the determination of the faulted feeder section and its isolation from the grid. The algorithm is based on transition probabilities among states obtained from intelligent sensors and tested on a radial distribution network with 3 sectionalizers.

Over the last 50 years, fault location in transmission systems has been a subject of interest to utility engineers and researchers. Nevertheless, it has not been until the last decades that fault location in distribution networks has started to gain prominence. Traditionally, fault location techniques for distribution networks have been classified in three different groups: fundamental frequency measurements, high frequency measurements and the use of artificial intelligence (AI). Yet despite this rigid classification, a new approach has started to be developed over the last years based on the injection of a discernible signal into the distribution systems, mainly in non-effectively grounded networks. However, even when recent developments of new grounding systems reinforce the possibility of using this kind of techniques, these are not usually cited by general reviews and overviews of fault location systems in distribution networks. Accordingly, this paper aims to provide a general but clear overview on the existing techniques for fault location in distribution networks based on signal injection. Apart from describing the different options presented to date, the most important aspects that characterize them and the injected signal are briefly outlined, as well as a comparative performance analysis.

Fault location in distribution networks is a major challenge that needs to be addressed in power distribution systems. Currently, fault location methods based on matrix algorithms, genetic algorithms, deep learning, and other algorithms have received wide attention from the industry. However, such methods have some drawbacks: (1) they require high accuracy in fault information uploads, which can lead to low fault tolerance; (2) they tend to converge early and get stuck in local optimal solutions; (3) they involve high computational complexity, leading to location delays. In this study, we propose a fault location framework based on recurrent neural network (RNN) and transfer learning. In this method, we first encode the information data collected from distribution terminals, and then use RNN to establish a nonlinear mapping relationship between fault features and fault location intervals, which effectively improves fault tolerance and reduces misjudgment issues. We then use transfer learning to load the pre-trained model onto the target task to address the problem of insufficient data for fault location in distribution networks. Experimental results show that after 15 rounds of training, our T-RNN model has achieved over 80% accuracy. Benefiting from Glorot weight initialization adopted after transfer learning, the model achieves good performance early on compared to the BP model, converges faster, and ultimately achieves a prediction accuracy of 96.5%.

With the large-scale integration of distributed generations (DGs) and the expansion of distribution networks, the complexity of fault location has significantly increased. Traditional fault location methods struggle to meet the demands of modern power systems. This paper explores the impact of distributed generation access on fault location in distribution networks and constructs switching functions and evaluation functions suitable for multi-state distributed generation based on fault characteristic information from automated monitoring devices. To augment the optimization performance of fault localization algorithms, this paper proposes an Improved Black Kite Algorithm (IBKA) that incorporates an Elite Learning Strategy along with Lens Imaging Reverse Learning Strategy and Golden Sine Strategy. This enhances the ability to escape local optima effectively. Simulation results demonstrate that the IBKA exhibits high localization accuracy and fault tolerance in complex scenarios, including single-section faults, multiple-section faults, and Feeder Terminal Unit (FTU) information distortion in active distribution networks, significantly improvs convergence speed and solution efficiency.