Fault Location In Distribution Networks Research Articles

Single Phase to Ground Fault Location of Distribution Network Based on Combined-GAT

Background: At present, small current grounding system has been widely used in distribution network of China. Affected by the complex topology of the distribution network and other factors, single-phase grounding fault has become the most prone type of electrical short-circuit fault in China. Objective: Considering that the traditional fault selection and location methods are difficult to mine the effective information of fault quantity, a new method is proposed in this paper to achieve accurate fault location on the basis of ensuring timeliness. Methods: In this paper, the physical topology of the distribution network is regarded as a graph, the overhead lines and cables of the main equipment are regarded as the nodes in the graph, and the problem of fault node location is corresponding to the task of graph attention classification. Considering the average degree and homogeneity of the given network topology, an improved graph attention network is built to realize fault node location. Results: This paper verifies the effectiveness of the proposed model for fault location through simulation in PSCADA. In addition, the applicability of the proposed model in the case of changes in the distribution network structure is verified. It verifies that the proposed method achieves high positioning accuracy.

Distribution Network Regionalized Fault Location Based on an Improved Manta Ray Foraging Optimization Algorithm

To address the problem that the accuracy of traditional intelligent algorithms in distribution network fault location decreases with the expansion of distribution network scale, a regionalized fault location method for distribution networks containing distributed power sources based on the improved manta ray foraging optimization (IMRFO) algorithm is proposed. First, the global convergence property of the basic manta ray foraging optimization (MRFO) algorithm is improved by fusing the restart strategy and the opposition-based learning strategy. Then, based on the two-port equivalence principle, a topological model for regionalized fault hierarchical localization in distribution networks is constructed. Finally, the algorithm is improved by binary discretization using the Sigmoid function to output the fault vector and complete the fault location of the distribution network. Simulation experiments are conducted using MATLAB for IEEE-33 node distribution networks and the simulation results show that the IMRFO algorithm combined with the regionalization of complex distribution networks has a better effect of dimensionality reduction. Compared with the traditional distribution network simulation model, the fault location fault tolerance is greatly improved and its accuracy rate is increased by 1.8% and the location speed is improved by 15.537 ms.

Fault location in distribution network by solving the optimization problem using genetic algorithm based on the calculating voltage changes

Fault location in distribution network by solving the optimization problem using genetic algorithm based on the calculating voltage changes

Fault Location Approach for Distribution Network with Dynamic Environment

This paper proposes a continuous tracing framework for fault location in distribution network, which is divided into two stages: parameter correction and fault location. On the stage of parameter correction, it is capable of correcting line parameters based on data in the steady state. On the stage of fault location, it can locate the fault according to the one cycle signal after it occurs based on the corrected parameters in the former stage. The stage of parameter correction is beneficial to the fault location process. The core algorithm of the framework is parameter adaptive group search optimizer (PAGSO), which is a kind of improved metaheuristic optimization algorithm. The adjustment strategy and regulatory mechanism are introduced in exploitation, whereas the adaptive mechanism based on reinforcement learning (RL) is introduced in exploration. Improvements could enhance search capability and help the algorithm converge faster. The proposed framework is tested in IEEE 34-bus model. Other meta-heuristic algorithms are adopted for comparison, including genetic algorithms (GA), particle swarm optimization (PSO), grey wolf optimization (GWO), and the standard group search optimizer (GSO). For fault location, PAGSO has been verified under three cases, including ideal condition, noisy condition, and the system with renewable penetration. For line parameters, experiments are designed to prove the algorithm feasibility and verify the necessity of the correction.

Single-phase disconnection fault location of active distribution network based on negative-sequence differential impedance

Accidents such as overvoltage, personal injury and motor damage caused by singlephase disconnection faults occur frequently in active distribution networks. In response to this problem, firstly, the negative-sequence differential impedance is defined and a protection method based on negative-sequence differential impedance is proposed, the method uses the amplitude of negative-sequence differential impedance as an action quantity and uses its phase to construct an adaptive braking threshold. Secondly, in case of protection failure under overload, the zero-sequence voltage amplitude difference is proposed as an auxiliary criterion, and the influence of different types of distributed generators on the zero-sequence voltage difference on both sides of the fault fracture is analyzed. Finally, it is verified by simulation that the method can be positioned reliably and is not affected by the neutral point grounding method, transition resistance, load and distributed generators.

Multistrategy Improved Whale Optimization Algorithm and Its Application.

To address the shortcomings of the whale optimization algorithm (WOA) in terms of insufficient global search ability and slow convergence speed, a differential evolution chaotic whale optimization algorithm (DECWOA) is proposed in this paper. Firstly, the initial population is generated by introducing the Sine chaos theory at the beginning of the algorithm to increase the population diversity. Secondly, new adaptive inertia weights are introduced into the individual whale position update formula to lay the foundation for the global search and improve the optimization performance of the algorithm. Finally, the differential variance algorithm is fused to improve the global search speed and accuracy of the whale optimization algorithm. The impact of various improvement strategies on the performance of the algorithm is analyzed using different kinds of test functions that are randomly selected. The particle swarm optimization algorithm (PSO), butterfly optimization algorithm (BOA), WOA, chaotic feedback adaptive whale optimization algorithm (CFAWOA), and DECWOA algorithm are compared for the optimal search performance. Experimental simulations are performed using MATLAB software, and the results show that the improved whale optimization algorithm has a better global optimization-seeking capability. The improved whale optimization algorithm is applied to the distribution network fault location of IEEE-33 nodes, and the effectiveness and accuracy of the distribution network fault zone location based on the multistrategy improved whale optimization algorithm is verified.

Research on Fault Location of Distribution Network with Distributed Generation

Research on Fault Location of Distribution Network with Distributed Generation

Research on Distribution Network Fault Location based on Improved Genetic Algorithm

Compared with the traditional recloser fault location without communication channel, feeder automation based on FTU is in line with the development of modern distribution system. FTU plays a key role in the whole system, but the location is inaccurate due to the lack of information caused by FTU itself or communication fault. When using genetic alogrithms for distribution network fault location, the result often converges prematurely or converges to an infeasible solution due to algorithm reasons. Aiming at the above problems, an improved genetic algorithm is proposed for distribution network fault location. Through simulation analysis, it can be found that the improved genetic algorithm has high convergence and good optimal fitness, which can better solve the convergence problems of the unmodified algorithm, which is of great significance for distribution network fault location.

Fault Location Analysis in Active Distribution Network Based on Multi-population Genetic Algorithm

Because the fault location of active distribution network is a complex optimization model, the traditional genetic algorithm has the problems of premature and slow convergence when solving complex optimization problems. The switch function that can adapt to the switching of multiple distributed power sources in real time is proposed. Here, we proposed a novel method to locate the fault of distributed power distribution network based on a multi-group genetic algorithm. When locating the fault zone, The algorithm stipulates that the direction of the generator flowing to the electrical equipment is the forward direction of the transmission line. In this paper, multiple populations are used to search the solution range at the same time to ensure that the final solution is the global optimal solution, and the optimal individual retention algebra is used as the convergence condition to fully improve the solution speed, which is suitable for complex distribution networks with distributed power generation. The fault location model proposed in this paper is simulated by a numerical example, and the results show that the model can accurately find the fault point, and has validity and accuracy.

Method of the Earth Fault Location in Power Distribution Network Besed on Mearing Earth Conductor Current

The copper foil shielding layer and armoring layer of the three-core cable and the grounding electrode of the distribution network constitute the grounding network of the distribution network. When a grounding fault occurs in the power grid, a regular ground current distribution is formed in the grounding network. .This paper analyzes the distribution law of the ground wire current in the arc suppression coil and resistance grounded distribution network: for the distribution network with the neutral point through the arc suppression coil and resistance grounded, the active component of the ground wire current of all cable segments without ground faults is Pass-through, that is, the active components of the ground current at the head and end of the cable are equal in magnitude and in the same direction; the sum of the active components of the ground current at the head and end of the ground fault cable segment is equal to the active component of the fault current at the ground fault point. According to this distribution law, this paper proposes a ground fault location method in which the neutral point is grounded by the arc suppression coil and resistance grounded grid, and its effectiveness is verified by simulation.

Accuracy enhance of fault classification and location in a smart distribution network based on stacked ensemble learning

This paper proposes an ensemble learning-based method to determine the type and location of faults in a smart distribution network. The employed scheme is a stacking based method that consists of two main levels, each of which includes one or more independent classifiers. In the structure of the proposed method for first level, multiclass support vector machine, K-nearest neighbors and random forest models are exploited. Also, for the next (final) level, which is also called meta-classifier, a random forest based model has been used, which itself is a kind of ensemble learning method. In order to supply the data used to feed the model, the voltage and current measurements in some buses and lines have been used. The proposed model is tested using the data related to all different types and location of faults and operating conditions in the IEEE 123-bus network. Besides, the model is implemented on another distribution test system to consider wider range and specs for fault parameters and also to comprise with other methods applied to it; high impedance faults are also regarded in this part. The obtained results show the appropriate accuracy of the proposed model and its better performance than other considered methods.

Accurate fault location method for distribution network in presence of DG using distributed time‐domain line model

In this paper a novel technique is presented for fault location in distribution networks in the presence of distributed generators (DGs). The proposed approach uses recorded voltage and current at the beginning of feeder and DG terminals. This method is based on transient state data, and due to presence of high frequencies in this state, to achieve high accuracy it utilizes the distributed time-domain (DTD) line model. The fault location problem is formulated as an optimization problem and is solved using Genetic Algorithm (GA). Through modal transformation, in addition to locate the symmetrical three-phase to ground (3LG) faults, the location of asymmetrical faults including single line to ground (SLG) and double line (LL) faults can also be determined. The effects of fault distance, fault resistance and fault inception angle on the accuracy of the proposed algorithm have also been investigated. A solution is also proposed to overcome the multi-response problem. The simulations are conducted and the results are obtained via PSCAD and MATLAB softwares, respectively. The effectiveness of the proposed approach has been verified using the modified IEEE 34-node test feeder under different fault conditions. The simulation results demonstrate the high efficiency and accuracy of the proposed method.

Analysis of the influence of three-phase asynchronization recording on fault location of distribution network

In order to improve the practical effect of the fault location technology, it is necessary to analyze the error caused by the three-phase asynchronization of the fault indicator recording. The influence of the three-phase recording asynchronization on the fault location of the distribution network is analyzed from the aspects of the start-up criterion, the error level of the zero-sequence current and the zero-sequence voltage. The simulation results show that fault location devices of different principles are affected differently by the asynchronization recording. In order to avoid mistake start-up of the fault location device, the change value should be used to construct the fault location start-up criterion. Meanwhile, the measurement accuracy of transient fault characteristics will be affected to a certain extent by the asynchronization of the fault indicator recording, but it has little effect on the reliability of fault location, and it can even make the fault characteristics more obvious after the single- phase fault occurs.

Fault location method of active distribution network based on graph theory and matrix algorithm

In view of the large scale distributed power distribution network, distribution network from the traditional single main transformer power supply system becomes more complex broken power supply network, the trend of the distribution network flow and network frame produced change, failure fault feature information of great change, the traditional distribution network fault location method can not accurately obtain the location of the fault zone, the low accuracy of fault location, the error bigger problem a new fault location method of active distribution network combining graph theory and matrix was proposed. According to the knowledge of graph theory, the distribution network is simplified to topology diagram and described in the form of matrix, and then the fault judgment matrix is obtained through a series of matrix addition operation, and the type of fault interval can be identified accurately and quickly by combining the fault criterion table. The simulation results show that this method is simple in principle, fast and effective in criterion, suitable for the flexible operation mode of active distribution network structure, can accurately and quickly determine the fault segment, and can meet the requirements of complex distribution network fault location.

Fault Location for Multi-source Distribution Network Based on Improved Chaotic Jaya Algorithm

Due to the wide access of distributed energy in the distribution network, the structure of the distribution network becomes complex and diverse, and the power flow distribution is flexible and changeable. To optimize the fault location performance of the multisource distribution network, this paper proposes a power grid fault location solution method based on the improved Jaya algorithm. By combining the chaos theory with the Jaya algorithm, the individual position iteration of the algorithm is optimized to improve the algorithm’s global optimization capability and speed up the fault location. Through the example test and comparison with the traditional algorithm, the experimental results verify the effectiveness and superiority of this method.

A fault location method of distribution network based on XGBoost and SVM algorithm

Nowadays, the reliable supply of electric power is vital in all aspects of social life. With the development and participation of distributed generations, not only does an accurate fault location lets repair of a fault line as quickly as possible, but also it is of great significance to ensure the safe and stable economic operation of the power system. This study proposes a method to determine the fault location in distribution networks, which is a combination of Extreme Gradient Boosting and Support Vector Machine. The effectiveness of the proposed method is validated on an IEEE34-bus distribution network under single-phase-to-ground faults, using voltage measurements available at each node in the distribution network. The comparison in accuracy, precision, recall, F1-score and time-cost of the method in this study with K-Nearest Neighbour and Multi-Layer Perceptron demonstrates the feasibility of applying the proposed method in distribution system fault diagnosis.

Fault detection and location in power distribution systems: The usefulness of the HS-OFDM scheme for time-domain reflectometry

This study discusses key characteristics and benefits of using time-domain reflectometry (TDR) systems based on the Hermitian symmetric orthogonal frequency-division multiplexing (HS-OFDM) scheme for fault detection and location in power distribution networks. In this context, a system model with power line modems injecting signals and capturing reflections in a power distribution network is outlined. Next, two reflectogram processing approaches, namely digital pulse compression and channel estimation, are examined. Also, the effects of different parametrizations and multiple access schemes on the performance of the HS-OFDM-based TDR system are addressed. Numerical results confirm that HS-OFDM-based TDR systems making using of channel estimation outperforms their counterparts based on pulse compression. The frequency range for narrowband power line communication provides fair range resolution and maximum unambiguous range values. Also, it is seen that the use of frequency-division multiple access schemes implies different signal-to-interference-plus-noise ratio (SINR) performance among different power line modems (PLMs) connected to a power distribution network. Time-division and code-division multiple access schemes, on the other hand, provide fair SINR performance among the PLMs at the cost of obtaining a small number of reflectograms during a time interval.

A quick fault location and isolation method for distribution network based on adaptive reclosing

Feeder automation is important to improve the reliability of power supply for distribution network. Existing voltage-time feeder automation scheme exists the problems of long fault processing time and the upstream switches of the fault point need to tolerate fault current twice and the upstream sections need to experience two short time power outage. In this paper, a quick fault location and isolation method for distribution network based on adaptive reclosing is proposed. Three key technologies of the strategy are introduced, including a phase segregated switch of the distribution network based on the permanent magnet operating structure, the phase selector based on transient current characteristics, and the temporary fault and permanent fault identification method based on the power frequency voltage characteristics. The proposed strategy can avoid the second impact on upstream switches and power-off of the upstream section in case of the permanent fault and can effectively shorten the fault processing time.

Fault location in distribution networks based on SVM and impedance-based method using online databank generation

Fault location in distribution networks based on SVM and impedance-based method using online databank generation

A multi-agent-based for fault location in distribution networks with wind power generator

The integration of distributed generation (DG) units such as wind power into the distribution network are one of the most viable technique to meet the energy demand increases. But, the integration of these DG units into power systems can change the dynamic performances of the systems and create new challenges that are necessary to be taken care of in the operation of the network. The fault location and diagnosis are the most significant technical challenges that can improve power systems’ reliability and stability. In this paper, a Multi-Agent System (MAS) based on current amplitude and current direction measured proposed for fault location, isolation, and power restoration in a smart distribution system with the presence of a wind power generator. The agents can communicate and collaborate to locate the faulted line, then send trips signal to corresponding circuit breakers accordingly. The simulation results show the performance of the proposed techniques.