High Impedance Fault Location Research Articles

A double-ended third harmonic method for vegetation high impedance fault location in overhead distribution systems

Vegetation-related high-impedance faults (VHIFs) on overhead distribution systems can cause damage, maintenance issues, and even wildfires, impacting both utilities and ecosystems. Existing fault location techniques struggle to accurately locate VHIFs. In this paper, we propose a novel double-ended terminal location method based on the third harmonic component of the fault system. The proposed technique determines the distance of the VHIF by approximating the third harmonic voltage at the fault local, utilizing measurements from the remote terminal located at the far-end of the feeder. This method efficiently locates VHIFs with just two measurement terminals, cutting the need and cost of extensive sensor deployment. Moreover, the proposed method overcomes the limitations of traditional fault location techniques by using a third harmonic model of the faulted system, eliminating the need for complex mathematical models to approximate the fault behavior and voltage at the fault local. Simulation tests were conducted to validate the proposed method, demonstrating its effectiveness in accurately locating VHIFs. The technique achieved error rates below 1.6 %, making it a promising solution for real-world applications in power distribution systems. The ability to precisely locate VHIFs meets a proactive protection philosophy and contributes to improved power system protection and ensures uninterrupted power supply.

Detection and location of high impedance faults in delta 13.8kV distribution networks

This article presents the main results obtained in the project “Automated System of Classification, Detection, and Location of High Impedance Faults in Distribution Networks”, carried out for Brazilian utility COPEL, between 2019 and 2021, as part of ANEEL's R&D program. The project developed an automated system with efficient and robust algorithms for the real-time detection, classification, and location of high impedance faults in the distribution networks. The system consisted of computational tools to automatic high impedance faults detection and location in 13.8 kV delta-connected grid. Field tests carried out in a real feeder turned possible the development of a simple and reliable algorithm, related to the amplitude and phase shift of the zero-sequence current monitored in the substation. The fault location was determined by consulting undervoltage at automatic reclosers, and smart energy meters installed along the feeder. A computational tool was developed to provide relevant information to the utility Operation Center to initiate an emergency maintenance.

High Impedance Fault Detection and Location in the Nigerian 330 kV Transmission Network Using Adaptive Neuro-Fuzzy Inference System

Fundamentally, the occurrence of high impedance fault (HIF) can be established when an energy filled conductor contacts a semiconductor. The occurrence of HIF can be described to be subtle and disastrous as it results to low current signal and a signal voltage arc if undetected and without implementation of protective measures, leads to the damage of the power system equipment and in many cases fire outbreak. In this study, the occurrence of HIF on the south-south region of Nigerian 330kV transmission line was studied with the data utilized obtained from the Nigerian control center (NCC) Osogbo. The data obtained was modeled in simulink and the outcome at normal condition was obtained. The transmission line distance was split into 4 points with the current signal at each point generated in simulink and exported to the Matlab file. The data in Matlab file was split to train, test and validate at 70%, 15% and 15% respectively. The data analysis performed was sent to Adaptive Neuro-fuzzy inference system (ANFIS) with the current signal at normal condition and at 3-phase HIF was used as input data while the split distance was implemented as the target data to the model. The effectiveness of the model in detecting and locating HIF was obtained and analyzed in a comparative plot of the location distance. From the results presented, the highest error deviation for fault location with ANFIS was 10%. Hence, it was concluded that ANFIS model had a satisfactory outcome in HIF detection and as such should be utilized for the HIF detection and location.

High impedance fault location in power distribution systems using deep learning and micro phasor measurements units ($$\mu$$PMU)

High impedance fault location in power distribution systems using deep learning and micro phasor measurements units ($$\mu$$PMU)

Wideband Synchronous Measurement-Based Detection and Location of High Impedance Fault for Resonant Distribution Systems With Integration of DERs

The increasing integration of distributed energy resources (DERs) into the distribution system has caused interference with the signals stimulated by high impedance faults (HIFs). Many existing HIF detection or location methods that are only based on the superficial nonlinearity features of signals rather than the deep laws, will become invalid. This paper proposes a detection and location scheme for HIFs by theoretically analyzing the relationships between signals and systems. By establishing the equivalent circuit of a resonant distribution system, an online method to calculate the kernel system parameters is proposed, based on which an adaptive criterion for HIF detection is provided. In this way, the ability to detect HIF is adequately exploited and independent of DER influences. The method is able to detect HIF over 8.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{k}{\Omega }$ </tex-math></inline-formula> under common operating conditions. Furthermore, the nonlinearity of HIF is analyzed by deriving laws about how wideband signals distribute in the system. The <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3^{\mathrm{ rd}}$ </tex-math></inline-formula> harmonic component of zero-sequence signals is proved to be superior in HIF location in terms of signal content and discrimination, which is also demonstrated to be valid under the influence of DER harmonic injection. On this basis, a HIF location method utilizing the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$3^{\mathrm{ rd}}$ </tex-math></inline-formula> harmonic zero-sequence signals is proposed. The effectiveness of the method and its robustness to the DER interference are validated by simulated and field HIFs in 10kV systems.

High impedance fault localization: A comprehensive review

• Review of HIF characteristics and simulation-based models. • Categorization of high impedance fault location studies in terms of finding fault location as exact and approximate location. • Comparison among the HIF location articles by considering the important indices. Locating high impedance faults (HIFs) is one of the biggest challenges in power networks. HIFs draw relatively low currents, so power system operators cannot easily detect them with conventional protection equipment. Therefore, finding the location of HIFs before they create catastrophic events in the network is crucial. Although several studies exist, a detailed evaluation of the proposed localization studies has not been discussed. In this paper, a comprehensive review of HIF localization methods by considering used models and some key indices is done. Furthermore, location techniques are categorized and compared with each other in terms of their pros and cons. Finally, some deduced results from reviewed localization papers are discussed in the study.

High Impedance Fault Location Methods: Review and Harmonic Selection-Based Analysis

High Impedance Faults (HIFs) are recurring events in electrical Distribution Systems (DSs) and occur by the contact between energized conductors and high impedance surfaces. HIFs may pose hazards to living beings and cause bushfires. However, the HIF protection has not been completely solved due to the small fault current and varying impedance, inhibiting traditional protection techniques from functioning correctly. In the literature, researchers have mainly focused on detection techniques. Thus, the development of HIF Location Methods (HIFLMs) is recent, and evidences for conclusive solutions are still lacking. Moreover, to this date, no existing study reviews the main challenges concerning HIFLMs in DSs. This paper proposes a systematic analysis of the common stages to design the main existing HIFLMs. The strategy is evaluating the similar characteristics that pose a common research path regarding challenges faced in real-world conditions. Additionally, this paper proposes a case study to assess the best input signals, metrics, and machine learning-based decision algorithms of a new HIFLM. The results are promising, with high identification rates, even in noisy conditions. The methodology can help to select the datasets for supervised learning-based HIFLM. Highlighting the state-of-art of current methods and support development of HIFLMs are this paper’s main contributions.

High-impedance fault identification and location by using mode decomposition integrated adaptive multi-kernel extreme learning machine technique for distributed generator-based microgrid

High-impedance fault identification and location by using mode decomposition integrated adaptive multi-kernel extreme learning machine technique for distributed generator-based microgrid

High-impedance fault location method of three-phase distribution lines based on electromagnetic time reversal

• Expanding the application scenario of the criterion of the minimum mirrored FCSE. • Accurately locating the single-phase HIF and identifying the fault phase. • Not affected by noise, GPS time synchronization, and the time delay of the device. • Location and diagnosis of single-phase HIF, phase to phase HIF, and three-phase HIF. Accurate location of high-resistance grounding faults in distribution lines is of great significance for improving the power supply reliability of power systems. In this study, a simulation model of a 10 kV three-phase distribution line is built using a numerical simulation platform. Further, a fault location method of three-phase distribution lines is proposed on the basis of the criterion of the minimum mirrored fault current signal energy (FCSE). The positioning accuracy of the high-impedance fault (HIF) is studied under different influencing factors. The results show that the proposed method can accurately locate the single-phase HIF of the three-phase distribution line, and the positioning error is within 50 m. However, it can only locate the fault when the fault resistance is 5 kΩ and below. In addition, the positioning accuracy of the proposed method for the HIF is not affected by noise and the sampling frequency, although the location accuracy under different fault inception angles is affected by fault resistance. Further, when the GPS time synchronization error is within 2 μs or the time delay of the transient signal device is within 2 ms, accurate positioning of the single-phase HIF can be realized. Moreover, by analyzing the three-phase FCSE distribution calculated in the reversed time, positioning and diagnosis of three HIF types, namely the single-phase grounding fault, phase-to-phase fault, and three-phase grounding fault, can be realized. Finally, fault phase identification of the single-phase HIF can also be achieved.

An Analytical Zero Sequence Method to Locate Fault in Distribution Systems Rich in DG

Locating high impedance faults (HIF) in a distribution system increases the system&#x2019;s reliability and improves the service&#x2019;s quality for customers. However, this type of fault produces currents of low magnitude, making it difficult to locate using conventional techniques. Therefore, this paper proposes a method for the location of single-phase high impedance faults in distribution systems with photovoltaic cells in low voltage. The method is based on the use of the sequence component of the current circulating in the medium voltage feeders of the distribution system, which are obtained from synchronized phasorial meters positioned along the feeder. The method considers nonsymmetrical lines, unbalanced loads, capacitors banks, photovoltaic DGs, and load variation. The performance of the proposed method was evaluated and tested on several distribution systems using ATP or PSCAD&#x00AE; and the results show that the method can locate HIFs with high precision. Also, a comparison was made with recently published methods to show the efficiency of the proposed method.

WAMs Based Eigenvalue Space Model for High Impedance Fault Detection

High impedance faults present unique challenges for power system protection engineers. The first challenge is the detection of the fault, given the low current magnitudes. The second challenge is to locate the fault to allow corrective measures to be taken. Corrective actions are essential as they mitigate safety hazards and equipment damage. The problem of high impedance fault detection and location is not a new one, and despite the safety and reliability implications, relatively few efforts have been made to find a general solution. This work presents a hybrid data driven and analytical-based model for high impedance fault detection in distribution systems. The first step is to estimate a state space model of the power line being monitored. From the state space model, eigenvalues are calculated, and their dynamic behavior is used to develop zones of protection. These zones of protection are generated analytically using machine learning tools. High impedance faults are detected as they drive the eigenvalues outside of their zones. A metric called eigenvalue drift coefficient was formulated in this work to facilitate the generalization of this solution. The performance of this technique is evaluated through case studies based on the IEEE 5-Bus system modeled in Matlab. Test results are encouraging indicating potential for real-life applications.

High impedance fault modeling and location for transmission line✰

A fault in a power system generates economic losses, security problems, social problems and can even take human lives. Therefore, it is necessary to have an efficient fault location strategy to reduce the exposure time and recurrence of the fault. This paper presents an impedance-based method to estimate the fault location in transmission lines. The mathematical formulation considers the distributed parameters transmission line model for the estimation of the fault distance, and it is obtained by the application of Gauss-Newton method. Said method considers available voltage and current measurements at both terminals of the transmission line as well as the line parameters. Moreover, the method can be used for locating high and low impedance faults. Additionally, it is proposed an adjustable HIF model to validate its performance, which allows to generate synthetic high impedance faults by setting specific features of a HIF from simple input parameters. The error in fault location accuracy is under 0.1% for more than 90% of the performance test cases. The easy implementation of this method and encouraging test results indicate its potential for real-life applications.

A Method for the Approximate Location of High Impedance Faults using Neural Networks

This paper describes an algorithm for ground to earth high-impedance fault identification and location in medium-voltage of unbalanced distribution systems. The daily variation of the load is considered, the fault resistance variation, inaccuracy in feeders data, and errors from phasor measurement units. The method is based on artificial neural networks associated with phasor measurement units to detecting the faulty area of the distribution system. Three types of neural network structures are proposed, (i) using phasor inputs, (ii) using non-phasor inputs, and (iii) using inputs to sequence components. To test the proposed method, thousands conditions of normal operation and fault operation were simulated to assemble the database. The method uses the current data obtained from meters that can be allocated at different points of the distribution system. The IEEE 123 test system is used to validate the proposed algorithm.

Harmonic Phasor Estimation Based on Frequency-Domain Sampling Theorem

Harmonic phasor estimation can be used both in power system protection and monitoring applications, such as islanding detection, high-impedance fault location, and harmonic state estimation. A key challenge for harmonic phasor estimation is that different harmonics have different harmonic frequency bandwidths. As a result, a harmonic phasor estimator (HPE) that can adapt to such variations is needed. Although the sinc interpolation function-based estimator (SIFE) has such ability, it has disadvantages that: 1) it needs numerous simulations to select the model parameter and 2) it cannot obtain zero-error results under nominal frequency condition. In this article, a novel HPE is proposed based on the frequency-domain sampling theorem, where the harmonic phasor is modeled based on several imaginary exponential functions. The proposed HPE is compared with the SIFE in frequency response, model parameter selection scheme, and simulation tests. The results show that the proposed HPE has the following three advantages: 1) it has an easier scheme for model parameter selection; 2) it has zero-error results under nominal frequency condition; and 3) it has higher accuracy under harmonic frequency deviation and harmonic modulation conditions.

Fault Detection and Isolation Methods in Subsea Observation Networks.

Subsea observation networks have gradually become the main means of deep-sea exploration. The reliability of the observation network is greatly affected by the severe undersea conditions. This study mainly focuses on theoretical research and the experimental platform verification of high-impedance and open-circuit fault detection for an underwater observation network. With the aid of deep learning, we perform the fault detection and prediction of the network operation. For the high-impedance and open-circuit fault detection of submarine cables, the entire system is modeled and simulated, and the voltage and current values of the operating nodes under different fault types are collected. Numerous calibrated data samples are supervised by a deep learning algorithm, and a fault location system model is built in the laboratory to verify the feasibility and superiority of the scheme. This paper also studies the fault isolation of the observation network, focusing on the communication protocol and the design of the fault isolation system. Experimental results verify the effectiveness of the proposed algorithm for the location and prediction of high-impedance and open-circuit faults, and the feasibility of the fault isolation system has also been verified. Moreover, the proposed methods greatly improve the reliability of undersea observation network systems.

Comparative Analysis of Fuzzy Inference System (FIS) And Adaptive Neuro-Fuzzy Inference System (ANFIS) Methods in the Classification and Location of High Impedance Faults on Distribution System

Unlike low impedance faults, which involve relatively large magnitude of fault currents and are easily detected by conventional over-current protection devices, high impedance faults pose a serious challenge to protection engineers because they can remain on the system without the protective relays being able to detect them. This paper presents an improved method for detection and location of high impedance fault using ANFIS model. The study was conducted on the 33 kV Uyo-Ikot Ekpene power distribution line. The case study power distribution system was modeled using MATLAB software. HIFs were introduced at various locations along the distribution line. The data obtained from the MATLAB/Simulink simulated fault using discrete wavelet transform (DWT) were used to train the ANFIS for the location of HIF points along the distribution system as well as for prediction of the distance of the fault location to the nearest injection substation. The results show that ANFIS model gives 52.5 percentage reduction in error compared with FIS in the location of fault points on the case study power distribution system.

Comparative Analysis of Fuzzy Inference System (FIS) And Adaptive Neuro-Fuzzy Inference System (ANFIS) Methods in the Classification and Location of High Impedance Faults on Distribution System

Unlike low impedance faults, which involve relatively large magnitude of fault currents and are easily detected by conventional over-current protection devices, high impedance faults pose a serious challenge to protection engineers because they can remain on the system without the protective relays being able to detect them. This paper presents an improved method for detection and location of high impedance fault using ANFIS model. The study was conducted on the 33 kV Uyo-Ikot Ekpene power distribution line. The case study power distribution system was modeled using MATLAB software. HIFs were introduced at various locations along the distribution line. The data obtained from the MATLAB/Simulink simulated fault using discrete wavelet transform (DWT) were used to train the ANFIS for the location of HIF points along the distribution system as well as for prediction of the distance of the fault location to the nearest injection substation. The results show that ANFIS model gives 52.5 percentage reduction in error compared with FIS in the location of fault points on the case study power distribution system.

Physics-based analytical model for high impedance fault location in distribution networks

This paper presents a physics-based analytical model for high impedance fault location in power distribution systems. The presented analytical solution is composed by two interdependent processes. First, fault distance is estimated through a Weighted Least Square approach applied to solve an overdetermined and nonlinear algebraic system of equations. Second, an analytical method based on the statistical behavior of the estimates obtained from the frequency domain system model solution is presented to address the multiple estimates problem, identifying the faulted section. The presented fault location physics-based analytical model considers the capacitive effect of distribution lines. Furthermore, voltages and currents measured from only one terminal are used. The formulation is evaluated using the IEEE 13-bus and a modified version of the IEEE 34-bus test feeders. Comparative analysis with state-of-the-art methods is presented. Average errors of 1.95% are obtained. Easy to implement analytical model, without hard to derive parameters, built on the weighted least squares state estimator, highlight potential aspects for real-life applications.

An Effective EMTR-Based High-Impedance Fault Location Method for Transmission Lines

This article summarizes the electromagnetic time-reversal (EMTR) technique for fault location, and further numerically validates its effectiveness when the fault impedance is negligible. In addition, a specific EMTR model considering the fault impedance is derived, and the correctness of the model derivation is verified by various calculation methods. Based on this, we found that when the fault impedance is large, the existing EMTR methods might fail to accurately locate the fault. We propose an EMTR method that improves the location effect of high-impedance faults by injecting double-ended signals simultaneously. Theoretical calculations show that this method can achieve an accurate location for high-impedance faults. To further illustrate the effectiveness, the proposed method is compared with the existing EMTR methods and the most commonly used traveling wave-based method using wavelet transform. The simulation results show that the proposed double-ended EMTR method can effectively locate high-impedance faults, and it is more robust against synchronization errors compared with the traveling wave method. In addition, the proposed method does not require the knowledge or a priori guess of the unknown fault impedance.

High Impedance Fault Detection and Location in Combined Overhead Line and Underground Cable Distribution Networks Equipped with Data Loggers

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.