Faults In Distribution Systems Research Articles

The Differential Protection Scheme for Microgrid Using S-Transform

The micro-grids with distributed generators enhance the aggregate power supply to the increasing load demand. However, the conventional over current relay protection may fail to operate when magnitude and direction of current differs significantly in grid connected mode and islanded mode depending upon DGs types and generating capacity. This paper presents a differential protection scheme using S-transform for detection and phase identification of faults in distribution systems integrated with different types of DGs. A radial distribution system with photovoltaic and synchronous distributed generators is simulated for data generation in PSCAD/EMTDC software. The proposed technique is tested on various fault cases and confirms accurate detection of faults and correct identification of faulty phases within a cycle for a 50 Hz grid nominal frequency.

Development of a new methodology for detection of high impedance faults for using in distribution automatic reclosers

This paper presents the preliminary results of a new methodology for detecting high impedance faults in distribution systems based on interharmonic signatures. The methodology involves incorporation of an interharmonic current analysis system into a conventional protection system, such as automatic reclosers. To check the functionality of the proposed methodology, the authors carried out field tests on different types of soil, involving instantaneous current waveform measurements during the occurrence of faults. The results suggest that the methodology, based on interharmonic currents produced by variations in electric arc length during the occurrence of high-impedance faults, shows great promise when it comes to detection of the disturbance.

Application of Optimized Technique for Identification of Location and Recognition of Fault in Distribution System

Distribution network is the group of connected loads with number of buses and feeders. The different facial appearance is present in distribution system which makes it somewhat arduous and dissimilar to examine as estimated to a transmission system. Due to load uncertainties, the system effected with losses, faults, quality and discrepancies in power supply at distribution level. Now a days the identification of fault and its type as of conventional approaches is very complicated and calibrated dynamically is proposed in this work. This work narrates impedance-based fault calculation for its location and its type based on feeder distance between bus to bus for 3-phase 4-wire distribution system. The paper mix faults section detection with impedance-based method in order to address non-homogeneity of feeder parameters and power quality issues in distribution system. The 15-Bus and 33-Bus distribution test system is examined and estimated the fault and its type using Fuzzy logic using MATLAB.

Numerical method for islanding the location of ground fault in the material based distribution system

Nowadays the location of a ground fault and separating the fault segments are very complicated in the material based distribution networks because the reality to facilitate the fault current is really minute to be calculated. Considering the smart digital meters are installed in the distribution side voltage (11 kV) of the radial distribution systems through the advancement of the smart-grid. This paper presented an identification of fault location and islanding of fault segments using smart digital metering unit on the distribution network side. Generally, superior method is used to locate the faulted segments and the faulted negative sequence by connecting the association between measurement sets and distance of the fault. The proposed technology is experienced in India, a real-time 40-bus radial distribution system and the results provide that it is appropriate for a system with both inactive load demands. This technology does not need any management methods but it uses the wide-area measured data. Together with the breakers, the proposed methodology can locate and island the fault segments without disrupting the healthy distribution network process.

Temporary Fault Ride-Through Method in Power Distribution Systems with Distributed Generations Based on PCS

The current practice of Distributed Generation (DG) disconnection for every fault in distribution systems has an adverse effect on utility and stable power trading when the penetration level of DGs is high. That is, in the process of fault detecting and Circuit Breaker (CB) reclosing when a temporary fault occurs, DGs should be disconnected from the Point of Common Coupling (PCC) before CB reclosing. Then all DGs should wait at least 5 minutes after restoration for reconnection and cannot supply the pre-bid power in power market during that period. To solve this problem, this paper proposes a control method that can keep operating without disconnection of DG. This control method is verified through modeling and simulation by the PSCAD/EMTDC software package for distribution systems with DGs based on PCS (Power Conditioning Systems) and CB reclosing protection.

THE ANALYSIS ON HYBRID SUPERCONDUCTING FAULT CURRENT LIMITER (SFCL) USAGE TO LIMIT SHORT CIRCUIT FAULT CURRENT OF 20 KV ELECTRIC POWER DISTRIBUTION IN SENGKALING SUBSTATION

Abstract —The occurrence of fault in electrical power system operation is inevitable. The causes of fault in electrical power transmission and distribution system for instances are lighting strikes on transmission canal, tree collapses, or short circuit inter-phases to the ground. In order to protect the equipment and the whole electrical system in Sengkaling Substation and to reduce the short circuit fault current quickly within timeframe of ½ cycle, it requires Superconducting Fault Current Limiter (SFCL) which is going to be placed on the bus that comes close to a critical point. The designing and analysis on the system of before and after hybrid SCFL installment utilize PSCAD software. The simulation result obtained by installing hybrid SFCL in incoming bus 2 (20 kV) was that hybrid SFCL was able to reduce short circuit fault current in ½ initial cycle with L-G fault of 16.77 kA changed to 5.9 kA, L-L-G fault of 35.38 kA changed to 9.15 kA, L-L-L-G fault of 38.36 kA changed to 9.8 kA, and L-L fault of 28.89 kA changed to 4.35 kA. The average percentage of short circuit fault current that was reduced by hybrid SFCL was 74.12%.

Modelling of high impedance faults in distribution systems and validation based on multiresolution techniques

The electric arc phenomenon associated with high impedance faults (HIFs) in distribution systems is an exciting subject that directly impacts over the reliability of electrical utilities, because fault currents are very small and present non-linearity and asymmetrical waveforms. Therefore, HIFs may be an undetectable phenomenon by overcurrent protections like fuses, re-closers, and relays. A HIF entails a challenge for its detection and location. In this sense, more realistic high impedance models, as well as reliable signal processing techniques, are needed to extract all transient characteristics aiming to detect HIFs in distribution networks. In this work, an efficient Resistive-HIF model is proposed and implemented into the Alternative Transients Program of the Electromagnetic Transients Program (ATP/EMTP) software to represent the main characteristics of HIFs. The model is compared against well-prove models by using two multiresolution approaches based on the Hermite transform and the Wavelet transform considering different frequency bands.

Fault detection in smart grids with time-varying distributed generation using wavelet energy and evolving neural networks

Online monitoring systems have been developed for real-time detection of high impedance faults in power distribution networks. Sources of distributed generation are usually ignored in the analyses. Distributed generation imposes great challenges to monitoring systems. This paper proposes a wavelet transform-based feature-extraction method combined with evolving neural networks to detect and locate high impedance faults in time-varying distributed generation systems. Empirically validated IEEE models, simulated in the ATPDraw and Matlab environments, were used to generate data streams containing faulty and normal occurrences. The energy of detail coefficients obtained from different wavelet families such as Symlet, Daubechies, and Biorthogonal are evaluated as feature extraction method. The proposed evolving neural network approach is particularly supplied with a recursive algorithm for learning from online data stream. Online learning allows the neural models to capture novelties and, therefore, deal with nonstationary behavior. This is a unique characteristic of this type of neural network, which differentiate it from other types of neural models. Comparative results considering feed-forward, radial-basis, and recurrent neural networks as well as the proposed hybrid wavelet-evolving neural network approach are shown. The proposed approach has provided encouraging results in terms of accuracy and robustness to changing environment using the energy of detail coefficients of a Symlet-2 wavelet. Robustness to the effect of distributed generation and to transient events is achieved through the ability of the neural model to update parameters, number of hidden neurons, and connection weights recursively. New conditions could be captured on the fly, during the online operation of the system.

Safety impacts of electric potential and electromagnetic fields as result of faults in electric distribution system

ABSTRACTThis article investigates the impacts of electric potential (EP) and electromagnetic fields (EMF) on human health, especially for those living or working near a distribution system, as a consequence of faults inside the distribution system supplied by an outdoor substation. A case study was carried out using a 115/22 kV substation and a 22 kV distribution system of Thailand’s Provincial Electricity Authority (PEA), with simulated faults injected at the top of a pole of distribution lines located at three different locations. Two methods were proposed for EP and EMF reduction: 1) bonding the ground grid of the substation and the ground rod of the riser pole, and 2) connecting the overhead ground wires of the substation and that of the distribution system. The study results confirm that the two proposed methods offer practically effective problem-solving solutions for reducing EP, and they are therefore able to mitigate the risk of equipment damage. The spatial distribution of EMF measured in the vicinity of the distribution system was found to comply with the threshold set by the International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the International Radiation Protection Association (IRPA), indicating that those living or working outside the substation were safe.

High Impedance Fault Detection using Advanced Distortion Detection Technique

A High Impedance Fault (HIF) in the power distribution systems remains mostly undetected by conventional protection schemes due to low fault currents. Apart from degrading the reliability of power supply to customers, HIF can impose a high cost on the utilities due to technical damages. The nonlinear and asymmetric nature of HIF makes its detection and identification very challenging. HIF signatures are in the form of minute-level distortions in the observable AC sinusoidal voltage and current waveforms but these signatures do not follow a clear pattern. In this paper, we present Advanced Distortion Detection Technique (ADDT), based on waveform analytics to distinguish and detect HIF. In addition, the ADDT analysis provides a fair assessment about the location and severity of HIF for efficient decision-making at the DSO level. ADDT is computationally lightweight and can be implemented in actual relays, hence it is enabled to provide an easy and cost-effective solution to HIF detection issues. ADDT robustness is tested in several simulation cases of interest using the IEEE-34 and IEEE-13 distribution test feeder systems in RTDS power system simulator. The test results successfully demonstrate the effectiveness and robustness of ADDT.

One-Class Classifier Based Fault Detection in Distribution Systems With Varying Penetration Levels of Distributed Energy Resources

The integration of Distributed Energy Resources (DERs) into distribution systems greatly increases the system complexity and introduces two-way power flow. Conventional protection schemes are based upon local measurements and simple linear system models, and are thus not capable of handling the new complexity and power flow patterns in systems with high DER penetration. In this paper, we propose a data-driven protection framework to address the challenges introduced by DERs. Firstly, considering the limited available data under fault conditions, we adopt the Support Vector Data Description (SVDD) method, a commonly used one-class classifier, for distribution system fault detection, which only requires the normal data for its training process. Secondly, incremental learning is incorporated into the proposed SVDD-based protection framework to accommodate variations of the integration level of DERs in distribution systems over time. In particular, the artificial uniform-hyperspherical data generation model is incorporated into the incremental SVDD to boost the training speed. Finally, we validate the proposed method under the IEEE 123-node test feeder. Simulation results demonstrate that our proposed SVDD-based fault detection framework significantly improves the robustness and resilience against DERs in comparison with conventional protection systems. Meanwhile, the proposed online updating model outperforms the existing incremental SVDD models in terms of successful training speed.

Transformer for Single-phase Line Break Fault in Low Voltage Three-phase Distribution System

Single-phase line break fault is becoming more and more frequent in low voltage three-phase distribution system. Therefore, once the single-phase line break fault occurs, three-phase loads cannot work, which will cause unnecessary economic loss. This paper proposed a transformer that can transfer power from two-phase to three-phase for single-phase line break fault in low voltage three-phase distribution system. The proposed transformer can solve the problem that these three-phase loads cannot work due to single-phase line break fault. At the same time, the principle that the transformer transfers power from two-phase to three-phase is analyzed. Finally, simulation results verify that the proposed transformer can transfer power from two-phase to three-phase.

Ann based Shortcoming Area in HVDC Transmission Line

This paper is to ponder the use of Neural systems for shortcoming discovery and area in HVDC framework. The proposed Neural system learns examples and relationship on transient information. The Back-propagation algorithm has the ability to match map complex and nonlinear input - output behavior. A MATLAB model was created for the 500kv,1000MW,12 pulse-based converter-based distribution system and various fault events were simulated. The limitations of AC over long transmission lines has led to the use of DC for bulk transmission over long distances. Fault condition like rectifier fault, inverter faults and transmission line faults are discussed in this paper.

Risk early warning method for distribution system with sources-networks-loads-vehicles based on fuzzy C-mean clustering

A risk probability classification model of distribution system with source-network-load-vehicle is established based on fuzzy C-means clustering and fuzzy mathematics in this paper. Monte Carlo simulation method is used to simulate various scenarios of operation and failure of lines, transformers, generators in distribution systems. The data needed for probability classification of voltage fluctuation, line overload, power loss and load loss of distribution system are obtained. For the severity of the accident, the membership functions of voltage fluctuation, line overload, power loss and load loss are constructed by using fuzzy distribution functions based on fuzzy classification method, and the corresponding risk severity classification model is constructed. Mamdani fuzzy reasoning is used to synthesize the risk probability and risk severity for determining the risk level. A risk early warning method for distribution system based on fuzzy C-means clustering is proposed. Taking IEEE-33, IEEE-39 and IEEE-118 systems as studying examples, the risk levels of voltage fluctuation, line overload, power loss and load loss are determined with the cases of normal operation and anticipated fault in distribution system.

Reinforcing Fault Ride Through Capability of Grid Forming Voltage Source Converters Using an Enhanced Voltage Control Scheme

Medium power distributed energy resources (DERs) are commonly connected to medium voltage distribution systems via voltage source converters (VSCs). Several guidelines and standards have been developed to establish the needed criteria and requirements for DERs interconnections. In this respect, it is preferred to reinforce the VSC fault ride through (FRT) capability, which considerably minimizes the DG outage period and reconnection time and results in a resilient system against short circuits. Considering the significant number of asymmetrical faults in distribution systems, the VSC response in such conditions must be investigated, and consequently, its FRT capability must be reinforced. In this paper, first, a comprehensive review on the existing FRT methods has been presented and discussed. Accordingly, an adaptive virtual impedance-based voltage reference generation method is proposed, which enhances the VSC behavior under short circuits and increases the VSC FRT capability. Also, a fast sinusoidal current reference limiter is proposed to improve the performance. To evaluate the performance of the proposed scheme, state-space analysis is presented, and a complete set of simulations is performed in PSCAD/EMTDC environment. Also, a comparison with the conventional method is presented.

Neuro-Fuzzy Access for Detection of Faults in an Underground Cable Distribution System

Nowadays, the interest of power system engineers In Indian Power System has increased towards the use of underground cables with the advent of cross-linked polyethylene (XLPE) insulated cables having high capacity for transmission of power. Underground cables are preferred in the densely populated regions where there is environmental constraint and right of way poses a big problem. The key limitation of underground cable is to locate and detect different types of faults in view of the fact that the cables are lying down under the surface. It is necessary that the fault must be cleared in minimum time on account of protection issues. As conventional methods for detection and classification of faults are time consuming, so, this work uses intelligent techniques for fast and more accurate detection of location and classification of faults in underground cables. Overall work has been performed in three steps, the first step is to develop a MATLAB/Simulink Model of a distribution system using underground cable with a provision to develop fault. In second step, an Artificial Neural Network (ANN) using DWT is used for fault detection & classification. In third step, ANN is hybridized with fuzzy system and discrete wavelet transform (DWT) methods to improve its performance. The training sets of adaptive neuro fuzzy inference system (ANFIS) are energy components of three phases of cable under fault (used as inputs) and fault type or different distances of faults in the cable(used as outputs). All the simulations have been carried out in MATLAB/ SIMULINK environment

Detection and Discrimination of Islanding and Faults in distribution system with Distributed Generation by using Wavelet based Alienation approach

This paper presents a wavelet transform based alienation technique for the protection of a radial 5 bus distribution system integrated with four wind type doubly fed Induction generators (DFIG).This technique is used to detect islanding condition and faults, classification of faults and their discrimination. Islanding is simulated at point of common coupling (PCC) and faults are simulated at each DG bus of the network. Daubechies wavelet transform has been used to decompose the current signals to get approximate coefficients. The Alienation coefficients of these approximate decompositions are termed as islanding and fault indexes. These indexes have been compared with predetermined threshold to detect islanding and faults. The same threshold value is utilized to discriminate transients associated with islanding and fault. Alienation coefficients at each bus over a half cycle window clearly detect both islanding and fault. Testing of the proposed algorithm has been carried out for various angles of incidence. Hence, the proposed algorithm is more effective and successful for finding the islanding condition as well as faults in distribution system with distributed generation.

Detection and Discrimination of Islanding and Faults in distribution system with Distributed Generation by using Wavelet based Alienation approach

This paper presents a wavelet transform based alienation technique for the protection of a radial 5 bus distribution system integrated with four wind type doubly fed Induction generators (DFIG).This technique is used to detect islanding condition and faults, classification of faults and their discrimination. Islanding is simulated at point of common coupling (PCC) and faults are simulated at each DG bus of the network. Daubechies wavelet transform has been used to decompose the current signals to get approximate coefficients. The Alienation coefficients of these approximate decompositions are termed as islanding and fault indexes. These indexes have been compared with predetermined threshold to detect islanding and faults. The same threshold value is utilized to discriminate transients associated with islanding and fault. Alienation coefficients at each bus over a half cycle window clearly detect both islanding and fault. Testing of the proposed algorithm has been carried out for various angles of incidence. Hence, the proposed algorithm is more effective and successful for finding the islanding condition as well as faults in distribution system with distributed generation.

Power distribution system fault monitoring device for supply networks in Nigeria

Electric power is the bedrock of our modern way of life. In Nigeria, power supply availability, sufficiency and reliability are major operational challenges. At the generation and transmission level, effort is made to ensure status monitoring and fault detection on the power network, but at the distribution level, particularly within domestic consumer communities there are no fault monitoring and detection devices except for HRC fuses at the feeder pillar. Unfortunately, these fuses are sometimes replaced by a copper wire bridge at some locations rendering the system unprotected and creating a great potential for transformer destruction on overload. This study is focused on designing an on-site power system monitoring device to be deployed on selected household entry power cables for detecting and indicating when phase off, low voltage, high voltage, over current, and blown fuse occurs on the building’s incomer line. The fault indication will help in reducing troubleshooting time and also ensure quick service restoration. After design implementation, the test result confirms design accuracy, device functionality and suitability as a low-cost solution to power supply system fault monitoring within local communities.

Algorithm for fault detection and localisation in a mesh‐type bipolar DC microgrid network

This study proposes a new method to detect and locate the fault in a DC distribution system in the presence of distributed generators. As the mesh-type network provides good continuity of service during faults and the bipolar system transmits high power at low-voltage level to the end user, the proposed scheme has utilised 1200 V mesh-type bipolar DC microgrid network. The proposed scheme detects a fault by comparing the calculated value of fault current and pole-to-pole voltage with the pre-defined threshold values and then distinguishes internal or external fault based on an estimation of line parameters. In case of an internal fault, the estimated parameters yield the exact location of the fault. The modelling of the aforementioned DC microgrid network has been carried out in PSCAD/EMTDC environment and various faults involving pole and ground have been performed with variable fault resistance and location. The simulation results clearly indicate that the proposed technique is not only capable to detect the fault rapidly but also able to disconnect the faulty section speedily (around 1.25 ms). As the proposed method detects fault by utilising local voltages and currents, its reliability is better than the previous algorithms.