Distribution Network Fault Research Articles

The Analysis of Particle Swarm Optimization Used for Distribution Network Fault Location

In view of their own limitations of GA[1] and ACA[2][3] in the fault location of distribution network, this paper presents a new group intelligent optimization method which is simple and easy to implement, fast convergence rate, more global optimization ability, etc, and this is the PSO. Then the basic principles of the PSO algorithm and the Standard algorithm of PSO are discussed in details, on the base of that, this paper continues to introduce the principle of PSO algorithm which is used in the fault location of distribution network. This section mainly introduces the structure of distribution network, then makes a brief introduction of the fault location algorithm, finally writes out the detailed steps of PSO algorithm. When already understood the principles and algorithms, a detailed analysis of the distribution network. This paper makes use of this method in the process of the location of transformer combined with the high accuracy of fault location which avoid the possibility of local convergence. Finally this paper gives the analysis of case, the result shows that the proposed method of distribution network fault location is feasible.

Research on Earth Fault Location for Distribution Network Based on Zero Sequence Current Ratio

Due to the large amount of branches and high grounding resistance of distribution networks, the grounding fault location has not been solved effectively. The matrix based live location method is proposed for single-phase-to-earth fault section in ungrounded distribution networks with radial lines. The method is based on on-line distributed detectors installed in the main branch of the distribution network. The distributed detectors measure the zero sequence current value and send them to the monitor center via the GPRS. Then according to the topological structure of distribution network, the software in the monitor center analyzes zero sequence current value and the feeder length, and extracts the zero sequence current ratio, detects the earth fault based on signal singularity. Route matrix T and fault information matrix G are multiplied to locate the earth fault section. An artificial earth fault test confirmed that the system could accurately locate faults in distribution networks with radial lines.

Distribution Network Fault Location and Isolation Based On Matrix Topology Algorithm

Distribution Network Fault Location and Isolation Based On Matrix Topology Algorithm

Fault Detection in Complex Distribution Network Based on Hilbert-Huang Transform

Traditional distribution network fault location methods often cannot be effectively applied for the structure of the branch in complex distribution network. A new accurate fault location for the single-phase-ground fault in complex distribution network with structure of the branch based on Hilbert-Huang transform was proposed in this paper. First, the distribution network was modeled. The faults on each branch were simulated. The energy characteristics under the branch in a particular frequency band were identified by HHT. Then these energy characteristics were used to train artificial neural networks (ANN).When the energy characteristics of actual fault are inputted, the trained neural network can output the malfunction branch. When the fault branch was determined, using the online fault feature matching method, combined with the genetic algorithm, the precise determination of the distance to fault location in the fault branch can be completed. With combinations of signal processing-Hilbert-Huang transform, artificial neural network and genetic algorithm, the entirely new method was proposed to deal with the problem of fault location in distribution network in this article. The results showed that the method has a good precision and apply to the small current grounding system. DOI: http://dx.doi.org/10.11591/telkomnika.v11i3.2220 Full Text: PDF

Distribution Network Fault Diagnosis Method Based on Granular Computing-BP

To deal with the complexity and uncertainty of distribution network fault information, a method of fault diagnosis based on granular computing and BP is proposed. This method uses attribute reduction advantages of granular computing theory and self-learning and knowledge acquisition ability of BP neural network. It put granular computing theory as the front-end processor of the BP neural network, namely simplify primitive information making use of granular computing reduction, and according to the concepts of relative granularity and significance of attributes based on binary granular computing are proposed to select input of BP, thereby reducing solving scale, and then construct neural network based on the minimum attribute sets, using BP neural network to model and parameter identify, reduce the BP study training time, improve the accuracy of the fault diagnosis. The distribution network example verifies the rationality and effectiveness of the proposed method. DOI: http://dx.doi.org/10.11591/telkomnika.v11i3.2184

Researching on Distribution Network Fault Location System

In this study, we propose the method using rough set theory to realize the distribution network fault positioning in WEBGIS environment. According to the distribution network tree structure, using of the area user s’ fault complain information as condition attributes, fault elements as decision attribute, form the decision table automatically. By using rough set method reduce the decision table, the minimal reduction of decision table for fault diagnosis is derived, the minimal diagnostic rules are obtained, guarantee the objectivity of the rule. When the fault complain call information is imperfect, it can still achieve rapid, accurate fault location on purpose, has good fault tolerance performance. In this study the use of C# language programming to achieve the reduction process for distribution network fault diagnosis decision table, combined with the WEBGIS platform, make full use of internal network database resources, to realize fault diagnosis simple and rapid operation and fault location visualization. The results show that the method is feasible and effective.

Fault Type Identification in Distribution System based on HHT and Neural Network

In order to accurately and reliably identify the type of distribution network fault, the fault type was divided into two types with the characteristics of the zero-sequence current. The two fault types are asymmetric ground fault and other faults. Then, by using the Hilbert-huang transform, the energy distribution of the fault current in different frequency bands was extracted. The fault type was encoded with binary code. The energy distribution of the fault current and the codes of the fault type were used as the samples of the two neural networks. The two neural networks were trained. Finally, when the fault occurred, the energy distribution of the current was extracted and imported into the corresponding BP network. And the outputs of the BP network are the codes of the fault type. The specific type of fault was identified. A number of simulations prove that this identification method accurately and reliably identify the type of distribution network fault. It improves the accuracy of the identification of various fault types to a large extent. Moreover, the method is free from the fault distance, fault time, the grounding resistance and the system operation mode.

The Design and Implementation of an Integrated Distribution Automation Scheme

According to the statistic of the distribution network operation, distribution network fault is generally located on line branch, rather than the main line. In view of the structure and characteristics of the current distribution automation system, combining the distribution network reformation and construction practice, this paper puts a comprehensive distribution automation solution that the branch line is equipped with distribution automation terminal which integrates protection and reactive power compensation function. It can achieve the rapid isolation of the distribution network failures and the power supply reliability, and dynamically improve the quality of power supply.

Enhanced Protection Scheme for Smart Grids Using Power Line Communications Techniques—Part I: Detection of High Impedance Fault Occurrence

Occurrence of high impedance faults (HIFs) in rural overhead power distribution networks may cause safety and economic issues for both public and the utility. Such faults may not be detected by the conventional protection schemes, so the development of a more sophisticated method is necessary. The forthcoming evolution of power networks to smart grids creates opportunities for new technologies to be implemented to that purpose. Utilities may transmit data that are necessary for the system operation using specific frequency ranges. A novel method utilizing these is proposed in this work. The monitoring of the network's input impedance in these frequency ranges can be used for detection of HIF occurrence, because such faults impose significant changes in its value. The proposed method is applied to single branch topologies, as well as to an existing topology of a Greek rural distribution system. Significant conclusions are derived in both cases. Moreover, the influence of several parameters, such as fault impedance and location and earth's electromagnetic properties on the method's efficacy is examined. Also, it is shown that the implementation of the proposed method may be drastically simplified by focusing on the monitoring of specific frequencies rather than the entire frequency range under study.

An Application of Heuristic-Search Based Tree Model in Fault Analysis of Distribution Network

Along with the increase of need for high reliability of the power system security, it is important to build up a distribution fault analysis network and processing system, which can provide decision-making help for dispatching personnel. This paper introduced framework of the distribution network fault analysis and processing system, and analyze the fault location, isolation, generation and evaluation of power supply reconfiguration strategy. Tree model and Heuristic search were used for fault location and power supply route switching strategy.

A Fully Decentralized Multi-Agent System for Intelligent Restoration of Power Distribution Network Incorporating Distributed Generations [Application Notes

In the distribution network fault management, service restoration is a very important component. When a fault occurs, it is necessary to restore power to these deenergized loads as soon as possible. The restoration problem could be formulated as a multilevel, multi-objective optimization problem with constraints [1].

Prediction of Incipient Faults in Underground Power Cables Utilizing S-Transform and Support Vector Regression

Incipient faults usually emerge from partial discharges which eventually cause insulation degradation between two insulated cable cores. Early detection of incipient faults is of particular importance because insulation defects caused by incipient faults may lead to permanent faults in underground distribution networks. This paper presents a novel approach using S-transform and support vector regression to predict the occurrence of incipient faults in underground cable networks. The results of this study proved that the new approach is capable to predict the existence of partial discharges in underground power cable systems in Malaysia.

High Impedance Fault Identification Method of Distribution Networks

Abstract. High impedance fault has always been difficult for distribution network fault identification due to its unobvious fault signature and difficult detection. This paper decomposed the transient signal in multi-scale by utilizing the good localization performance of the wavelet in both time domain and frequency domain, reconstructed the wavelet coefficients under each scale, took the wavelet reconstruction coefficient which was under the scale 3, calculated the size spectrum of each feeder line in timing floating window and identified the circuits in which the faults lined according to the value of the size spectrum. The high impedance fault simulation system was built based upon the study of the various transient signals in power systems, and the high impedance fault simulation analysis of the distribution feeder was undertaken through PSCAD simulation platform using high impedance fault model. Simulation analysis showed that the method could effectively extract the feature of high impedance fault on high impedance fault identification.

2-Staged Reconstruction Optimization for High Voltage Distribution Network Based PSO Algorithm

High voltage distribution network is an important link between transmission and middle voltage distribution network. If a high voltage distribution network fault occurs, the economy and reliability of the whole city distribution system will be seriously affected. To solve this problem, a traditional reconstruction optimization model is improved and a 2-staged reconstruction optimization model is proposed based on an improved particle swarm optimization (PSO) algorithm. The first stage reconstruction only considers the economic goal and the second stage reconstruction needs consider the boundary constrains. The 2-staged method considers the economic benefit and the voltage quality simultaneously. It can achieve the multi goals: meeting actual boundary operation conditions, optimizing the combination of network losses and the number of operation switching. The fault isolation and reconfiguration of an actual distribution network system in Dezhou power grid were simulated. Simulation results validate the rationality and feasibility of the proposed method

Line Selection Analysis of Ground Fault in Distribution Network Based on Chief Half-Wave and Remnant Current

Abstract：This paper analyses characteristics of single-phase ground fault in distribution system. Now, most of the line selection methods have some limitations, which leads to the low accuracy of the fault line selection. In order to solve above problems, make use of the matlab software in this article to simulate and analyze the isolated neutral system and resonance neutral earthing system when they occur single-phase ground fault. Finally, the new method based on first half wave method and increment of residual current to improve the accuracy of fault line selection is proposed.

The Method of Precise Timing of Grounding Fault in Power System Based on Wavelet Theory

The probability of single phase grounding is very high among the faults in distribution network of our country, according to statistics it has reaching at 80 percents. Therefore, the fault selecting line of low current grounding system becomes a thorny problem, it is very often that we can’t accurately locate the fault happening time, thus couldn’t choose effective information of fault happening time. This paper puts forward the method which uses the advantage that signal singularity detection of wavelet transform of presicing timing for single phase grounding in distribution network, to pick-up detailed transient information when single phase grounding fault happening in distribution network, then the relay protection device takes action timely and accurately. Because the current signal is smaller when low current grounding happens in distribution network,it is very easier to be interfered by other devices outside, so , time orientation by singularity of zero sequence voltage signal at the fault happening time is adopted in this paper.

Distribution Network Based on Heuristic Search to Achieve Fault Recovery System

Structural features for the distribution network and distribution network fault recovery needs, connectivity analysis of distribution network into the global connectivity analysis and line analysis of two local dynamic statement. Distribution network run by the characteristics of radiation, the problem tree into power stratification. Powered by hierarchical tree to reduce the search space, to improve the speed of recovery and effective power supply to meet the real-time recovery. Using VC + +6. 0-mode integrated programming and technology plans, the development of distribution network reconfiguration system.

Impact of distributed generators on arcing faults in distribution networks

Increased fault level is one of the main concerns connected to the integration of distributed generation (DG) into distribution networks. To accurately calculate fault currents in distribution systems with a high penetration of DG, a realistic fault model must be developed that includes the electrical arc existing at the fault point. The results of an assessment of the impact of DG on such arcing faults are presented. The significance of the study is that the fault model includes the electrical arc element, which brings additional non-linear resistance into consideration. Since the arc resistance is a non-linear function of the fault current, the problem of simultaneous fault currents and arc resistance calculation has been tackled using a novel iterative algorithm. In this work, a typical medium voltage distribution network is considered. Results of the simultaneous fault analysis and arc resistance calculation in the IEEE-34 distribution network with a distributed generator are presented and discussed.

High impedance fault detection using combination of multi-layer perceptron neural networks based on multi-resolution morphological gradient features of current waveform

In this study a new pattern recognition-based algorithm is presented for detecting high impedance faults (HIFs) in distribution networks with broken or unbroken conductors and distinguishing them from other similar phenomena such as capacitor bank switching, load switching, no-load transformer switching (through feeder switching), fault on adjacent feeders, insulator leakage current (ILC) and harmonic load. The proposed method has employed multi-resolution morphological gradient (MMG) for extraction of the time-based features from three half cycles of the post-disturbance current waveform. Then, according to these features, three multi-layer perceptron neural networks are trained. Finally, the outputs of these classifiers are combined using the average method. Applying the data for HIF, ILC and harmonic load from field tests and for other similar phenomena from simulations has shown high security and dependability of the proposed method. Also, a comparison between the features from the proposed MMG-based procedure and the features from discrete Fourier transform, discrete S-transform, discrete TT-transform and discrete wavelet transform is made in the feature space.

Unbalanced distribution network fault analysis with hybrid compensation

Fault analysis with hybrid compensation for unbalanced distribution systems is proposed. The method employs the unbalanced three-phase model to analyse faults. Two matrices containing information of the topological characteristics of distribution networks were built along with the proposed hybrid-compensation method for analysis. Appropriate boundary conditions can be obtained for a fault to solve various types of single or simultaneous faults. The time-consuming lower upper (LU) decompositions, the Jacobian matrix or the Y admittance matrix, required in the traditional algorithms, are not needed in the new development. Test results show that the proposed method is efficient, easy to program, also with advantages of high speed, robustness, improved accuracy and lower memory requirements.