Search

Intelligent electric distribution networks compensated with D-STATCOM are active networks in which data of terminals is important for better distribution of energy. Similar to all electricity network devices, energy distribution lines in such networks are also subject to transient and steady-state AC faults, e.g., short circuit. Sections of the network in which the fault occurs are separated by relays. In such a condition, fault location and restoring the normal status of the network are important. Fault location in these networks is performed based on synchronous data of two terminals because data of all buses are transmitted to the main bus In this paper, a time-domain equation method (TDEM) is proposed for locating faults on smart distribution grid (SDG) using distributed line model based on time-domain equations. The proposed method locates the point of transient and steady-state fault in SDG considering DGs and compensators. In this paper, the D-STATCOM and wind power plant are considered in SDG. The suggested method does not need the D-STATCOM and DGs model for applying the algorithm. It only uses data of less than half of the cycle for executing the algorithm. The numerical simulation confirms that the proposed fault location method is accurate and it provides a reliable solution for automatic fault location problem in distribution networks. [ABSTRACT FROM AUTHOR]

The line parameters of the distribution network (DN) may change because of the atmospheric, structural, and operational conditions. The uncertainty of line parameters can compromise the accuracy of the automatic fault location methods. Besides, arc faults (AFs) may happen in the DN. These faults are difficult to locate in the faulty section because of the nonlinear, asymmetric, and random nature of AF current. In this article, we present a new time-domain fault location (TDFL) method to determine the location of the fault in smart power DN under the line parameters uncertainty. In the suggested method, line parameters' accurate values are determined using a mixed gradient descent particle swarm optimization algorithm. The suggested method's performance is investigated with the help of an IEEE 123-node test feeder in MATLAB (R2018b). The effects of parameter uncertainty, distributed generations operation conditions and modes, different types of AF, various fault distances, resistances, and the fault inception angles are studied. For further evaluation of the proposed method's robustness, two practical tests in the laboratory are carried out. The results confirm that the proposed TDFL method has high accuracy. [ABSTRACT FROM AUTHOR]

Power distribution networks (PDNs) has played a crucial role in expediting transition towards cleaner and better distributed energy sources. Nowadays, more and more distributed generations (DGs) are used in PDNs which complicates the automatic fault location. This article presents an accurate impedance-based method to determine the fault location for smart PDN in the presence of DGs. In addition, phase domain equations of distributed line parameters are used to enhance the accuracy of fault location. Two types of networks are considered. The first type of network is assumed to be fully observable with $\mu PMU$ and in the second type there are only a few $\mu PMU\text{s}$ with data loggers on the rest nodes. Load impedances of all nodes are estimated using pre-fault recorded information by present $\mu PMU\text{s}$ and data loggers. The proposed algorithm might suggest several points as possible fault locations for a PDN. To find out the actual location of fault same fault type is simulated for all suggested points. A matching value which is mathematically defined in the article, is calculated using recorded and simulated voltage to determine the actual fault point among all the suggested candidates. The accuracy of suggested method is analyzed against various conditions. [ABSTRACT FROM AUTHOR]

Summary: Unified power flow controller (UPFC) flexible alternating current transmission system devices affect voltage and current signals at beginning of the feeder when a fault occurs. This indicates importance of fault location in compensated transmission lines. In the proposed method, only voltage signal of one terminal is employed. When a fault occurs, three‐fourth cycle of the voltage signal is received at one side and then the signal is divided into four separate partitions. Then, fast discrete orthonormal stockwell transform is applied to each partition to extract a feature vector. Using 10 first principle component analysis values of the feature vectors and Gaussian process regression, fault location is estimated. The proposed method is evaluated on a 500 kV transmission line of 300 km length with UPFC at different positions of the transmission line. Different conditions including fault inception angle, numerical references of UPFC and its operating modes, load existence, sampling frequency, and presence of noise are investigated. Numerical results under different conditions indicate high accuracy and efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

• Novel fault location technique for power networks is proposed. • The method uses voltage magnitude difference. • D-STATCOM, and line capacitor are considered. • Methods is independent of current data resulting in higher accuracy. Power grids are highly susceptible to various types of faults and their associated consequences. In recent years, numerous fault location methods have been proposed for different types of power networks. Generally, these methods determine the location of a fault by measuring current and voltage data on one or both sides of the line. However, the use of current data can result in calculation errors due to the saturation state of the current transformer and the bidirectional fault current. Moreover, the use of measuring devices in different nodes can lead to increased costs and the need for advanced telecommunication systems and data synchronization. In this paper, we propose a comprehensive technique for fault location in power networks that incorporates the presence of D-STATCOM and considers the effect of line capacitors. Our method estimates the distance and faulty branch by measuring the difference in fault voltage magnitude at the substation and comparing it with simulated faults in other branches. Unlike other methods that rely on current data, our proposed technique is independent of current data, resulting in higher accuracy and faster fault detection. Furthermore, our method offers significant cost savings compared to other fault location methods. To evaluate the performance of our technique, we conducted simulations on a 32-node power network in MATLAB/SIMULINK and an 8-node network in a power system simulator. We tested the sensitivity of our method to various fault locations, resistances, and DG penetration levels. The results of our simulations demonstrate the high accuracy and speed of our proposed technique, making it a promising alternative to other fault location methods in the field. [ABSTRACT FROM AUTHOR]

The power distribution networks (PDN) are spread in different street and Alley. Furthermore, nowadays, the DG is used in PDN, especially photovoltaic (PV). Therefore, fault location in these PDNs is complex. In this paper, an improved impedance based method has been proposed for fault location in power distribution network with presence of photovoltaic distributed generation resources. According that the PV has an uncertain behavior in different conditions, the proposed method is designed to be robust against PV behavior and upstream feeder changes. In the suggested method, detail equations are derived to prove a new quadratic equation for locating fault in PDNs using recorded voltage and current at the beginning of feeder and DG terminals. According to this proved equation is depended on to just voltage and currents of source or substation terminals, consequently dynamic modeling of PV and substation is not important in the proposed method. Within this method, the π line model is used for improving the accuracy of the suggested method. To evaluate the accuracy of the proposed method, the modified 11 node test Feeder is simulated in the MATLAB software and sensitivity of the suggested method was investigated against the different fault distances fault types, fault resistances and fault inception angles. Furthermore, the proposed method is investigated and tested on the real test feeder in power system simulator of power system and protection Lab. in Persian Gulf University. The results indicate the high accuracy of the algorithm. [ABSTRACT FROM AUTHOR]

The distribution network is extended throughout cities, towns, and villages. Because of the increase in loads and the decrease in power passageways and public corridor reduction, double circuit lines are increasingly being used instead of single circuit lines. Fault location in double circuit power networks is very important because it decreases the repair time and consequently the power outage time. In this paper, a new improved method for fault location in double circuit medium power distribution lines is proposed. The suggested impedance-based fault location method takes into account the mutual effect of double circuit lines on each other. To the best of our knowledge, the proposed method is the first of its kind which supports double circuit distribution networks. In the proposed method, a new quadratic equation for locating fault in power distribution networks is obtained using recorded voltage and current at the beginning of feeder. In this method, the π line model is used for improving the accuracy of the suggested method. The proposed method is supported by mathematical proofs and derivation. To evaluate the accuracy of the proposed method, the proposed method is tested on a thirteen-node network in different conditions, such as instrument error, various fault resistances, and different fault inception angles in various distances and fault types. The numerical results confirm the high accuracy and validity of the proposed method. [ABSTRACT FROM AUTHOR]

In this study, a practical method is proposed for determining the distance and the section of fault in power distribution system (PDS). In the suggested method, at first the possible fault points are determined using a novel impedance‐based fault location method. Since the number of these points may be more than one, thus two methods are proposed for determining the real location of fault. In the first method, the measured and recorded samples of voltages at the beginning of feeder for actual fault are compared with the stored samples of voltages which are obtained from simulating of fault at the possible fault points. The one with highest matching is the real location of fault. In the second method, frequency spectrum (FS) of voltage is defined as a suitable criterion for this purpose. Therefore the real fault point is determined by comparing and matching the FS of voltages obtained from the simulated faults and the recorded voltage for actual fault. The performance of the proposed method is evaluated in a real feeder in distribution network of Iran considering different types of faults, fault resistances, fault inception angles, real instrument transformer models and X/R ratio changes of upstream PDS network. The obtained results show that the performance of the proposed method is quite satisfactory and its accuracy is very high. [ABSTRACT FROM AUTHOR]

SUMMARY Power Distribution System (PDS) is spread on different places. Therefore, PDS has many laterals and load taps. Accurate fault locating in PDS causes to improve reliability indices and its efficiency. In this paper, an improved method is suggested for fault location in PDS, which has a high accuracy. In the proposed algorithm, by using phase domain of distributed-parameter line model, a fifth-order algebraic equation of fault distance is obtained, which can improve the accuracy of determined fault distance for all types of faults. The proposed method is tested under different fault resistances in which the results show low sensitivity to this parameter. To evaluate the accuracy of the proposed method, the modified IEEE 34 Node Test Feeder is used, and its efficiency and accuracy is proved. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Precise load modeling and load value estimation at each node of power distribution systems are very important for determining the exact location of fault in impedance-based fault-location algorithms. In this article, a modified impedance-based fault-location algorithm is proposed by applying dynamic load estimation and distributed-parameter line model. The load value at each node is estimated by its load factor and power factor. In the proposed fault-location algorithm, the power distribution system and power factor of each node are estimated first, just before the fault, using the recorded data of voltage and current at the beginning of the main feeder. Then, using this information, the initial location of the fault is obtained by analyzing each section. In this process, multiple positions for the fault can result. Thus, the faulted section is determined by analyzing the operation of protective equipment,i.e., fuses, fault indicators, and reclosers, performed by investigating the current patterns at the beginning of feeder. The performance of the proposed method is evaluated based on a real feeder in an Iranian distribution network under different fault conditions. The obtained results show the efficiency and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

One of the main factors that disrupt reliability and stop energy provision is the fault occurrence in distribution networks. Thus, accurate and fast fault prediction and location in distribution networks are essential for increasing reliability, fast restoration, optimal electrical energy consumption, and customer satisfaction. This study reviews and investigates fault prediction and fault location topics. To this end, the existing methods and views in the context of fault prediction are reviewed first; then, fault location is investigated. This paper investigates various methods, their advantages, disadvantages, technical reports, and patents in conventional distribution networks, smart-grids, and micro-grids. Comparison of this study with other surveys indicates that it is more comprehensive and despite others covers fault prediction. In addition, it includes an up to date review of the methods for distance measurement and fault location considering different network types (AC/DC), presence of DG, communication and automation standards, synchronous and unsynchronous measurement, magnetic measurement, and state estimation-based fault location methods. [ABSTRACT FROM AUTHOR]

Distribution networks transmit electrical energy from an upstream network to customers. Undesirable circumstances such as faults in the distribution networks can cause hazardous conditions, equipment failure, and power outages. Therefore, to avoid financial loss, to maintain customer satisfaction, and network reliability, it is vital to restore the network as fast as possible. In this paper, a new fault location (FL) algorithm that uses the recorded data of smart meters (SMs) and smart feeder meters (SFMs) to locate the actual point of fault, is introduced. The method does not require high-resolution measurements, which is among the main advantages of the method. An impedance-based technique is utilized to detect all possible FL candidates in the distribution network. After the fault occurrence, the protection relay sends a signal to all SFMs, to collect the recorded active power of all connected lines after the fault. The higher value of active power represents the real faulty section due to the high-fault current. The effectiveness of the proposed method was investigated on an IEEE 11-node test feeder in MATLAB SIMULINK 2020b, under several situations, such as different fault resistances, distances, inception angles, and types. In some cases, the algorithm found two or three candidates for FL. In these cases, the section estimation helped to identify the real fault among all candidates. Section estimation method performs well for all simulated cases. The results showed that the proposed method was accurate and was able to precisely detect the real faulty section. To experimentally evaluate the proposed method's powerfulness, a laboratory test and its simulation were carried out. The algorithm was precisely able to distinguish the real faulty section among all candidates in the experiment. The results revealed the robustness and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Power distribution networks are vulnerable to different faults, which compromise the grid performance and need to be managed effectively. Automatic and accurate fault detection and location are key components of effective fault management. This paper proposes a new framework for fault detection and location for smart distribution networks that are equipped with data loggers. The framework supports networks with mixed overhead lines and underground cables. The proposed framework consists of area detection, faulty section identification, and high impedance fault location. Firstly, the faulty zone and section are detected based on the operation of over-current relays and digital fault recorders. Then, by comparing the recorded traveling times at both ends of lines, which are related to the protection zone, the faulty line is identified. In the last step, the location of the fault is estimated based on discrete wavelet transform. The proposed method is tested on a 20 kV 13 node network, which is composed of overhead lines and underground cables. The method is tested in both balanced and unbalanced configurations. The obtained results confirm the advantages of the proposed method compared with the current state-of-the art. [ABSTRACT FROM AUTHOR]

• Fault location in Distribution Networks in the Presence of DGs is addressed. • The proposed method is a novel two-steps approach. • The method improves the state-of-art approaches in terms of accuracy. • The method improves the state-of-art approaches in terms of the success rate. • A good performance is confirmed in simulation and in the laboratory environment. Distributed generation resources are becoming more popular in electric energy distribution networks. As more Distributed generation are integrated into the grid, the system performance is challenged by issues such as manifold power injection to the network or nonlinear behavior when a fault occurs. To address this, fault location in electric energy distribution networks in the presence of distributed generation needs particular attention. This is important to reduce the loss of generated energy, reduce interruptions time, increase the reliability of the network and consequently improve the security of electricity supply. In this paper, a novel fault location method is presented applied to distributed networks with distributed generation. The proposed method is a hybrid two-step method which identifies accurate fault location using information stored in the network at pre- and post-fault time. The proposed method employs voltage and current information at the beginning of the feeder to estimate fault distance in the first step. The estimated distance will be associated with several similar sections considering the topology of the distributed networks. In the second step, the proposed method determines accurate fault location through transient analysis based on the frequency component. In this step, the exact fault location is identified. In order to investigate its performance, a standard IEEE-11 network is simulated in MATLAB. Furthermore, experiments are carried out in a network power simulator, showing good results. [ABSTRACT FROM AUTHOR]

Fault location in electrical energy distribution networks is an important task, as faults in distribution grids are among the main causes of electricity supply disruption. Fault location in the distribution systems, however, is a challenging task because of the topology of the distribution networks, as well as the main and side branches. Therefore, it is necessary to address these challenges through an intelligent approach to fault location. In this paper, fault location in electric energy distribution networks is addressed considering the changes in fault distance and fault resistance in the presence of different fault types. A new method for fault location is developed for conditions where the minimum information is available and only information at the beginning of the feeder is used. This facilitates wide adoption of the technique as it does not require significant investments in instrumentation and measurement. The proposed intelligent method is based on the impedance and transient state estimation. This technique employs a specific impedance analysis for determining possible fault locations considering the unbalanced performance of distribution systems, distances, and different fault resistances. To determine the real faulty section, real fault frequency component analysis and the simulated faults at possible fault locations are used. At this stage of the process, it is possible to eliminate multiple estimations with the help of comparison and identification of the similarities. Therefore, a real faulty section is determined. It is observed that some conditions of electric energy distribution networks affect the accuracy and performance of the proposed method significantly; thus, a detailed investigation is conducted to neutralize these conditions. Simulation results and calculations based on MATLAB along with a practical test of the proposed method in power network simulator confirm a satisfactory performance. [ABSTRACT FROM AUTHOR]

• An automatic deep learning framework is proposed to locate faults in power distribution grids. • The framework requires only limited measurement i. e. the voltage at the substations. • Simulations and laboratory tests demonstrate the proposed technique's exceptional accuracy. Power distribution grids (PDGs) are one of the main parts of electrical logistic chains with the task of transferring electricity to the consumers continually. Adverse weather conditions, equipment failure, and human disruption can bring about the PDGs to faulty situations leading to the inevitable interrupting power consumption which results in financial losses. Therefore, it is vital to locate the faulty spot accurately and quickly. In this paper, an automatic deep learning framework is implemented to locate faults in the PDGs with limited measurement requirements i. e. only the voltage at the substations. The Spectrogram time-frequency analysis is performed on the voltage signal to obtain more informative training data. A convolutional neural network (CNN) model is utilized and trained to identify the location of the fault in the distribution grid. To provide a more precise outcome, the capsule network is used. This approach determines the location of the faulty section using an offline databank and then estimates the exact faulty point using an online databank of multiple fault scenarios in that section. To evaluate the powerfulness of the proposed method, several simulations are performed on the IEEE 34-node feeder in MATLAB (2020b). For further verification of the proposed method's effectiveness, several laboratory tests are done as well. The results demonstrate that the proposed technique performs exceptionally well in terms of accuracy compared to other state-of-art counterparts, even when merely using the recorded voltage at the substations. [ABSTRACT FROM AUTHOR]