Determination Of Fault Location Research Articles

Single-Ended Fault Location Determination on High-Voltage Overhead Power Lines with the Account for the Reactive Component of Fault Impedance

Single-Ended Fault Location Determination on High-Voltage Overhead Power Lines with the Account for the Reactive Component of Fault Impedance

Kernel-based cumulative sum and differential cumulative sum approaches for resilient fault detection in LVDC microgrids

The energy industry is rapidly shifting from conventional to smart grid systems, involving advancements in microgrids and power management systems. However, achieving desired outcomes with the existing grid setup poses significant challenges. To address the above issues, adopting a Low Voltage Direct Current (LVDC) distribution system provides successful operational advantages. The primary objective of this work is to improve the system's security by developing a more resilient fault detection scheme. The presented work has proposed a Kernel-based Cumulative Sum (K-CUSUM) and Kernel-based Differential Cumulative Sum (K-DCUSUM) technique which is designed to identify changes in data under fewer assumptions. Instead of using the classical Maximum Mean Discrepancy (MMD) technique, the K-CUSUM and K-DCUSUM methods use a non-parametric MMD testing framework to evaluate incoming data by comparing it to reference distribution samples. Further, a comprehensive analysis is undertaken on an LVDC test system, considering fault scenarios involving pole-to-pole and pole-to-ground configurations. This research encompassed the determination of fault location, evaluation of fault resistance, examination of noise introduction, and an exploration of the influence of photovoltaic (PV) penetration. Moreover, the proposed approach is tested for a standard LVDC Microgrid. The results are compared with other contemporary techniques and recent literature.

Gangguan Saluran Transmisi di Deteksi Menggunakan Metode Gelombang Berjalan dan Transformasi Wavelet Diskrit

Determination of fault location using impedance-based methods and the traveling wave method. Many previous studies used the impedance method but found deficiencies; if the fault impedance is high, it affects the accuracy of determining the fault location. Another method uses the global positioning system (GPS), which is less economical because it requires a lot of expensive devices. This research focuses on the traveling wave method popularized by Bewley, which uses high-frequency electromagnetic impulses derived from transient voltage and current faults inside and outside the line. This method ignores the fault type, line resistance, and fault start angle. In analyzing the time difference between the incident and reflected waves, a discrete wavelet transform analysis is used to help determine the location of the disturbance. The Maninjau hydroelectric power plant and the Pauh Limo substation are modeled using an alternative transient program (ATP) with several components and parameters. Modeling is given for one-phase ground disturbance, two-phase ground disturbance, two-phase, three-phase, and lightning surge. Determination of fault locations using single-ended and double-ended methods with a sampling rate of 1 Mhz by varying the type of wavelet (Daubechies 4, Coiflets 4, Symlets 4) The results obtained in determining the location of disturbances based on the type of wavelet, Daubechies 4, have a small error, so the accuracy is high, and the method double ends for all types of interference to obtain a smaller error rate.

An Efficient LoRa-Enabled Smart Fault Detection and Monitoring Platform for the Power Distribution System Using Self-Powered IoT Devices

Transient stability and supply disturbances are common yet unwelcome phenomena in power distribution systems, particularly in sub-Saharan Africa. The growing demand for greater reliability and dependability in power delivery has aroused the interest of researchers and renewed the pursuit of advanced technological solutions for fault detection and location determination at medium and low-voltage levels. The length of the distribution network typically ranges from hundreds to thousands of kilometers. In this regard, the management of distribution networks, including the identification of faulty segments, is a significant recurrent challenge facing power-system operators. With the ever-expanding distribution network and regulatory demands for service reliability, the challenge for network operators is daunting. However, the deployment of IoT technologies in the energy distribution infrastructure would significantly accelerate the detection and location of faults, thus transforming the electricity delivery service into one that is responsive, communicative, attractive, and robust. This study proposes, designs, and implements a reasonably priced LoRaWAN-based IoT platform for monitoring distribution networks. The study was conducted in Nakuru County, Kenya on an actual and active distribution network owned and managed by Kenya Power Company. Experimental results showed that a trigger is generated at the network-monitoring center in about 100 msec of the occurrence of a fault on the distribution network, thus enabling quick, prompt, and immediate commencement of reparative action. Furthermore, practical evaluation has shown that this platform is well adapted for the context of developing countries where budgetary constraints and cost prohibitions hinder the upgrade of the legacy grid into fully-fledged smart entities.

Performance Comparison of Impedance-Based Fault Location Methods for Transmission Line

Electric transmission lines play a very essential role in transmitting power energy from generation centers to consumption regions. They can be exposed to fault occurrences due to various reasons, such as lightning strikes, malfunction of components, and human errors. Since fault is unpredictable, a fast fault location method is required to minimize the impact of fault in power systems. This paper presents a research work for comparing the performance of the impedance-based fault location methods, in which the impedance parameter of the faulted line section is calculated as a measure of the distance to the fault. To evaluate the capability of the methods for correctly detecting and locating the fault locations, comprehensive simulation results are carried out. This computation is based on modeling and simulating a three-phase 220kV overhead transmission line in the Matlab/Simulink software. Short circuits which occur in various fault resistances and locations along the transmission line are emulated to investigate several case studies and the accuracy of fault location determination is calculated to compare the performance among these fault location methods.

Fault location determination in three-terminal transmission lines connected to industrial microgrids without requiring fault classification data and independent of line parameters

The connection of large industrial microgrids to three-terminal transmission lines greatly complicates the protection scheme of the lines due to the uncertainty in generating renewable energy sources, the probability of unintentional islanding, the abrupt switching of sensitive and critical loads, the influence of supply and demand management programs, and bidirectional active and reactive power flow. This paper presents a fault location algorithm for three-terminal transmission lines connected to an industrial microgrid that does not need the detection of faulty section, fault classification, and transmission line parameters. The proposed method uses voltage and current phasors of transmission lines measured by phasor measurement units (PMUs). One of the salient features of the proposed algorithm is that it does not need to determine the faulty section before the fault location operation. Furthermore, since power transmission lines are always exposed to changing climatic conditions and aging, their electrical characteristics vary over time in the long run compared to their rated value. Hence, this leads to the malfunction of protection schemes. This is solved in this study as the proposed fault location algorithm is independent of line impedances. On the other hand, the dependence of conventional fault location algorithms on fault classification data reduces the reliability of fault location schemes, making these algorithms dependent on fault classification data. However, the present study overcomes this problem as the algorithm is independent of the data of the faulty phase(s) detection. The proposed scheme is fully implemented in the MATLAB software environment, and the performance of the algorithm is analyzed for various fault types under different conditions. The validity of the algorithm is shown by various tests and sensitivity analyses.

Determination of fault location in 35 sV electrical networks at transient resistance

Determination of fault location in 35 sV electrical networks at transient resistance

Estimating Fault Location Based on Fault Current in 20 kV Distribution System

The growth of the electric power system is currently taking place rapidly, causing an increase in the number and length of line to provide consumer services. In the line, there are often fault caused by lightning, storms, breakdown insulation, and short circuit caused by birds and other objects. Detection and location determination will speed up the repair process and can avoid more severe damage. Most studies refer to the fault location on the transmission line. But lately the determination of fault location in distribution system has begun to become a concern of researchers for the improvement of the quality of electricity services to consumers. This study discusses the determination of fault locations based on fault currents and the types of disturbances using data from the assumed distribution system model. The estimated fault location by ignoring the fault resistance has the largest error obtained 0.74% and estimated fault location by including fault resistance will cause a very large error, but the error can be reduced by changing the algorithm of the fault resistance assumption. The result for to ground fault error has reached 1.238% and double line to ground error has reached 88.167%.Keywords— Fault location, fault current, fault resistance, distribution system

Wavelet-Alienation-Neural-Based Protection Scheme for STATCOM Compensated Transmission Line

The custom power devices play important role for enhancing the power transfer capacity of transmission system. However, these devices introduce challenges of under reach or over reach, in the protection of transmission system. This article introduces a novel, protection algorithm based on wavelet-alienation-neural technique for STATCOM-compensated transmission system. For detecting and classifying faults, approximate coefficients are computed from the postfault quarter cycle current waveforms. Fault index, which is summation of alienation coefficients (computed by approximate coefficients) of both the buses, is computed and compared with the threshold magnitude for detecting and classifying the different faults. For the determination of fault location, artificial neural network is applied, with input as three-phase approximate coefficients, evaluated from the voltage and current signals over a time duration of a quarter cycle. Robustness of the developed scheme has been validated for various faults at different locations with varying fault impedances and angles of fault incidence.

Fault Location in Radial Distribution Network Based on Fault Current Profile and the Artificial Neural Network

Abstract Electricity distribution systems are subject to a variety of faults such as permanent and transient short circuits due to the extent and multiplicity of equipment. In principle, short circuit fault causes the existing protective equipment to operate and to no electricity the various parts of the distribution network. Rapid and accurate determination of fault location, repair and recovery, it has not prevented the distribution of energy. This will satisfy consumers and prevent the losses of electricity companies. In this paper, the artificial neural network and fault current profiles are used to determine the distance of the fault, determine the type of fault and detect the short circuit. This method provides the information needed to locate the fault by sampling the current before and after the fault occurs from the SCADA system. The effect of connectivity local resistance changes and the effect of load changes on fault location were evaluated. The results show that this method is more accurate than the voltage droop profile variation method in determining the fault distance and short circuit breakdown. If only the net fault current changes profile is used, the effect of the load changes in determining the short-circuit breakdown is much less.

Определение места повреждения в сети 35 кВ с трехобмоточным питающим трансформатором при двухстороннем замере напряжений и токов

Определение места повреждения в сети 35 кВ с трехобмоточным питающим трансформатором при двухстороннем замере напряжений и токов

A Method of Fault Location Detection on Branched Power Transmission Lines

Using a method with different signal-to-noise ratios to search for a location of a fault location in branched power-transmission lines (PTLs) is considered in the work. A simulation model of a branched PTL is developed in the MATLAB software package. The relative error of fault location determination by changing the signal-to-noise ratio on the PTL and simulating different types of faults is studied in the simulation model. Three simulated pulses are used as the location signal: a single rectangular pulse, chirp signal, and Barker code with changing pulse width. It is revealed that choosing the location signal results in the maximum achievable accuracy of fault detection. Using the Barker code provides determination of fault location with an error of 0.2% and signal-to-noise ratio of more than 27 dB.

Assessment of impedance based fault locator for AC micro-grid

This paper proposes an impedance-based fault location determination scheme for the 3-phase micro-grid. The paper describes how voltage and current data during a fault event can be leveraged to accurately locate a fault in the micro-grid including distributed generation (DG). The proposed method uses voltage and current measurements from both ends of the line section in order to determine the fault location. This method is devised in such a way that it evades the requirement of fault type identification by using only one fault location equation. The method is applicable to all types of shunt faults. In the proposed formulation of fault location, the effect of mutual inductance and capacitance of distribution line is also considered. The method is tested on a simulated medium-voltage (MV) micro-grid with doubly fed induction generator (DFIG) and permanent magnet synchronous generator (PMSG) wind turbines connected to specific nodes. The test results indicate that the proposed fault locator can reliably locate faults in the micro-grid with high accuracy.

Determination of Fault Location In Shunt Capacitor Bank Through Compensated Neutral Current

Shunt capacitor bank in power transmission are essential in providing reactive power support and improvement of voltage profile at any required point within the grid system. The failure of shunt capacitor bank due to unbalance capacitance caused reactive power and voltage losses to the power transmission network. The time taken to identify the location of capacitance failure require a lot of time due to no physical indication failure in shunt capacitor bank. This paper is focused on investigating the fault location in shunt capacitor bank in high voltage system mainly at power system transmission through compensated neutral current method.The investigation is focused on the internal failure of capacitor unit in shunt capacitor bank which caused by capacitance element failure. The configuration of shunt capacitor bank applied in this research used the common type of configuration which is ungrounded double wye connection and internally fused type of capacitor unit. This type of shunt capacitor bank configuration will affect the development of mathematical modelling as the algorithm for identifying the location and number of element failure in shunt capacitor bank. The investigation is done by developing the mathematical modelling and simulation through MATLAB software for neutral current at the neutral point of shunt capacitor bank. The output results of neutral current are used to determine and identify the location and number of element failure in shunt capacitor bank. Through neutral current result, the angle of neutral current is compared with corresponding or equivalent phase current to determine the faulty section thus determine the location of element failure in shunt capacitor bank. The ratio between neutral current and equivalent phase current will determine the number and type of element failure occurred in a section of shunt capacitor bank. The comprehensive analysis was done to determine the relationship between number and type of element failure to the number and type of faulty capacitor unit in shunt capacitor bank.

Increase of Accuracy of the Fault Location Methods for Overhead Electrical Power Lines

The high‐voltage power lines are quite often damaged parts of the energy system. Line outage is always accompanied by undersupply of energy and decrease of reliability, cost, and quality of electric supply. That is why one of the important tasks of line maintenance is quick looking for location of the damage and organization of the rehabilitation. The main part of this work includes development and research of the methods and algorithms for fault location based on one‐sided measurement and the ways to increase their accuracy. This type of measurement uses signals from digital current and voltage transformers as input. The influence of the basic distorting factors on the accuracy of the fault location determination methods is also considered.

A Novel Zone Division Approach for Power System Fault Detection Using ANN-Based Pattern Recognition Technique

This paper presents a waveform analysis-based approach for detection and classification of short-circuit faults in large power networks. To reduce the computational burden in dealing with a large volume of waveform data, a novel zone detection method has been used where a large power network is divided into optimal number of zones with manageable number of buses and lines. A first module of the artificial neural network-based classifier has been developed to perform an “exploratory global search” to find the faulty zone, which is then refined to a “local search” within a zone, by a second module of classifier for determination of exact fault location and fault type. The elementary waveform data are being captured by disturbance recorders placed at strategic buses, termed as “monitoring locations.” Feature extraction, which is typically the underlying principle of any waveform analysis-based fault detection approach, is implemented by the extended Kalman filter. The proposed method has been successfully tested on the IEEE 57 bus network with encouraging results.

電力系統における送電線故障点標定に関する技術動向

This article introduces the survey results of fault location technique in power systems. The power transmission line Fault Locator (FL) is an indispensable device for early determination of fault location on power transmission line. Several types of FL have been developed to date, including the pulse radar type, surge type and impedance type. The purpose of this article are to pick up overview of FL of the three types. Furthermore this article introduces about applied FL in field and the research trend of FL.

Fault location determination for transmission lines with different series-compensation levels using transient frequencies

Fault location determination for transmission lines with different series-compensation levels using transient frequencies

Earth fault location determination independent of fault impedance for distribution networks

Summary This article introduces a new earth fault location algorithm for both single and parallel feeders in distribution networks with single end measurements. The proposed algorithm depends on using the equality between the computed sequence components of the current at the fault point. The algorithm is independent of the dynamic arcing or static fault impedances. Then the faulted network can be decomposed into a prefault network and a pure fault network. The different types of connections of load transformer are considered in the study. This is because of their known influence on the direction of earth fault current in the faulty network. Moreover, the existence of distributed generation is considered during formulating the mathematical core of the proposed algorithm. Hence, the sequence current components at the faulty point can be derived without the need to measure the distributed generation current contribution or its terminal voltage with all varieties of load transformer connection. The proposed algorithm is tested via simulating a real 11 kV cascaded parallel-radial earthed distribution feeder from the Egyptian distribution network using Matlab. Different test cases are examined to visualize the performance of the proposed algorithm with a variety of fault conditions, including the fault impedance, loading, load transformer connection, and existence of distributed generations. All applied simulation tests ensure the efficacy of the proposed algorithm for estimating the fault distance in distribution systems with considerable distributed generation insertion and considering all possibilities of load transformer connection.

Radar Determination of Fault Slip and Location in Partially Decorrelated Images

Faced with the challenge of thousands of frames of radar interferometric images, automated feature extraction promises to spur data understanding and highlight geophysically active land regions for further study. We have developed techniques for automatically determining surface fault slip and location using deformation images from the NASA Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), which is similar to satellitebased SAR but has more mission flexibility and higher resolution (pixels are approximately 7 m). This radar interferometry provides a highly sensitive method, clearly indicating faults slipping at levels of 10 mm or less. But interferometric images are subject to decorrelation between revisit times, creating spots of bad data in the image. Our method begins with freely available data products from the UAVSAR mission, chiefly unwrapped interferograms, coherence images, and flight metadata. The computer vision techniques we use assume no data gaps or holes; so a preliminary step detects and removes spots of bad data and fills these holes by interpolation and blurring. Detected and partially validated surface fractures from earthquake main shocks, aftershocks, and aseismicinduced slip are shown for faults in California, including El Mayor-Cucapah (M7.2, 2010), the Ocotillo aftershock (M5.7, 2010), and South Napa (M6.0, 2014). Aseismic slip is detected on the San Andreas Fault from the El Mayor-Cucapah earthquake, in regions of highly patterned partial decorrelation. Validation is performed by comparing slip estimates from two interferograms with published ground truth measurements.