Showing papers on "Fault indicator published in 2018"

Combined Fault Location and Classification for Power Transmission Lines Fault Diagnosis With Integrated Feature Extraction

Abstract: Accurate and timely diagnosis of transmission line faults is key for reliable operations of power systems. Existing fault-diagnosis methods rely on expert knowledge or extensive feature extraction, which is also highly dependent on expert knowledge. Additionally, most methods for fault diagnosis of transmission lines require multiple separate subalgorithms for fault classification and location performing each function independently and sequentially. In this research, an integrated framework combining fault classification and location is proposed by applying an innovative machine-learning algorithm: the summation-wavelet extreme learning machine (SW-ELM) that integrates feature extraction in the learning process. As a further contribution, an extension of the SW-ELM, i.e., the summation-Gaussian extreme learning machine (SG-ELM), is proposed and successfully applied to transmission line fault diagnosis. SG-ELM is fully self-learning and does not require ad-hoc feature extraction, making it deployable with minimum expert subjectivity. The developed framework is applied to three transmission-line topologies without any prior parameter tuning or ad-hoc feature extraction. Evaluations on a simulated dataset show that the proposed method can diagnose faults within a single cycle, remain immune to fault resistance and inception angle variation, and deliver high accuracy for both tasks of fault diagnosis: fault type classification and fault location estimation.

Fault Analysis of Inverter-Interfaced Distributed Generators With Different Control Schemes

Abstract: Diversification of control schemes adopted by inverter-interfaced distributed generators (IIDGs) leads to difficulties in fault current estimation in a microgrid, which might make preexisting protection systems invalid and threaten the safety of power electronic devices. It is therefore important to study fault characteristics of IIDGs. This paper investigates characteristics of fault current of IIDGs caused by both symmetrical and asymmetrical faults. Two kinds of widely used control modes, current control (constant current control and PQ control) and voltage control (V/F control and droop control), are under investigation to provide an intuitive comparison on fault current. In particular, a novel algorithm is proposed to calculate fault current of droop-controlled IIDGs. It is found that different limiters have great impacts on fault response of IIDGs and detailed research works are carried out to identify the effects in this paper. Simulation results based on PSCAD/EMTDC and calculation results based on MATLAB/Simulink verify the correctness of the proposed fault models.

Tool condition monitoring using spectral subtraction and convolutional neural networks in milling process

Abstract: Process monitoring is necessary in machining operation to increase productivity, improve surface quality, and reduce unscheduled downtime. Tool wear and breakage are important and common source of machining problems due to high temperatures and forces of the machining process. Therefore, it is highly beneficial to develop an online tool condition monitoring (TCM) system. This paper investigates a robust tool wear monitoring system for milling operation. Recent developments in machine learning, in particular deep learning methods, result in significant improvement in automation of different industries. Therefore, in this research, we employed convolutional neural network (CNN) as a well-established and powerful deep learning algorithm for tool wear estimation. Wavelet packet-based features are extracted for tool wear monitoring as a powerful time-frequency fault indicator. Moreover, a hybrid feature extraction method is proposed using wavelet time-frequency transformation and spectral subtraction algorithms to intensify the effect of tool wear in the signal and reduce the effect of other cutting parameters. CNN-based monitoring systems are compared with three other machine learning methods (support vector machine, Bayesian rigid network, and K nearest neighbor method) as the baseline. The research is validated using different datasets. The algorithms are implemented and compared using experimental force and vibration signals from LIPPS lab of ETS university as well as using current signals as the fault indicator from Nasa_Ames dataset.

Fault Location in Ungrounded Photovoltaic System Using Wavelets and ANN

Abstract: Identifying ground faults is a significant problem in ungrounded photovoltaic (PV) systems because such earth faults do not provide sufficient fault currents for their detection and location during system operation. If such ground faults are not cleared quickly, a subsequent ground fault on the healthy phase will create a complete short circuit in the system. This paper proposes a novel fault-location scheme in which high frequency noise patterns are used to identify the fault location. The high-frequency noise is generated due to the switching transients of converters combined with the parasitic capacitance of PV panels and cables. Discrete wavelet transform is used for the decomposition of the monitored signal (midpoint voltage of the converters) and features are extracted. Norm values of the measured waveform at different frequency bands give unique features at different fault locations and are used as the feature vectors for pattern recognition. Then, a three-layer feedforward artificial neural networks classifier, which can automatically classify the fault locations according to the extracted features, is investigated. The proposed fault-location scheme has been primarily developed for fault location in the PV farm (PV panels and dc cables). The method is tested for ground faults as well as line–line faults. These faults are simulated with a real-time digital simulator and the data are then analyzed with wavelets. Finally, the effectiveness of the designed fault locator is tested with varying system parameters. The results demonstrate that the proposed approach has accurate and robust performance even with noisy measurements and changes in operating conditions.

Protection of Smart DC Microgrid With Ring Configuration Using Parameter Estimation Approach

Abstract: In a smart dc microgrid, power electronic devices limit the current during fault and therefore, an overcurrent-based relaying scheme cannot provide required sensitivity and selectivity for such a system. For a dc microgrid with ring configuration having bidirectional power flow, the protection design is further complicated. For reliable supply to customers and to avoid unwanted disconnection of renewable resources, selectivity of a protection scheme is important. In this paper, using local voltage and current data, a least square-based technique estimates the parameter of the fault path, from which the direction of the fault is inferred. Using the direction of fault information of both ends of a line segment in a ring system, internal and external faults are discriminated for network protection. Using PSCAD/EMTDC simulations for a ring system, proposed method is tested for various fault situations including high resistance fault, close-in fault, signals with noise, and considering different modes of distributed generation operations. The proposed algorithm is also validated on a scaled-down hardware setup in the laboratory. The method is found to be more accurate compared to available technique.

An Irradiance-Independent, Robust Ground-Fault Detection Scheme for PV Arrays Based on Spread Spectrum Time-Domain Reflectometry (SSTDR)

Abstract: A healthy photovoltaic (PV) array has a specific impedance between node pairs, and any ground fault changes the impedance values. Reflectometry is a well-known technique in electromagnetics, and it could be exploited to detect fault and aging-related impedance variations in a PV system. A fault detection algorithm using the spread spectrum time-domain reflectometry (SSTDR) method has been introduced in this paper. SSTDR has been successfully used for detecting and locating aircraft wiring faults. However, the wide variation in impedance throughout the entire PV system, which is caused by the use of different materials and interconnections makes PV fault detection more challenging while using reflectometry. Unlike other conventional ground-fault detection techniques specifically developed for PV arrays, SSTDR does not depend on fault-current magnitudes. Therefore, SSTDR can be used even in the absence of the solar irradiation, which makes it a very powerful fault-detection tool. The proposed PV ground-fault detection technique has been tested in a real-world PV system, and it can confidently detect PV ground faults for different configurations of PV arrays (single and double strings) and fault resistances (0.5, 5, and 10- $\Omega$ ). Moreover, it has been experimentally verified that our proposed algorithm works at low irradiance and can detect specific ground faults that may remain undetected using the conventional ground-fault detection and interrupter (GFDI) fuses.

A Submodule Fault Ride-Through Strategy for Modular Multilevel Converters With Nearest Level Modulation

Abstract: The modular multilevel converter (MMC) with nearest level modulation (NLM) is widely used in the high voltage applications for low switching frequency and easy implementation. Existing literature has not provided a complete submodule (SM) fault ride-through scheme for MMC with NLM. In this paper, a strategy including fault detection, localization, redundancy, and recovery is proposed to ensure continuous operation of MMC under IGBT open-circuit faults conditions. It only requires a few hardware and software resources. The features of MMC and SMs with three types of failures are studied, respectively. Based on these, the fault detection method is proposed by using a simple hardware circuit, thus high computation complexity is avoided. Since current fault localization schemes are limited to MMC with carrier phase shifted pulse width modulation, this paper further proposes a strategy for MMC with NLM to locate the faulty SM and identify the fault type. After this, the fault redundancy and the proposed fault recovery method are applied to eliminate the fault and then exit the failure state. Therefore, the ability of SM fault ride-through can be realized. Analysis of failure characteristics are verified in simulation. Experimental results based on a single-phase MMC prototype with 11 SMs per arm are presented to demonstrate the validity of the proposed fault ride-through strategy.

High Frequency Impedance Based Fault Location in Distribution System With DGs

Abstract: Distributed generations (DGs) with power electronic devices and their control loops will cause distortion to the fault currents and result in errors for power frequency measurement based fault locations This might jeopardize the distribution system fault restoration and reduce the grid resilience The proposed method uses high frequency (up to 3 kHz) fault information and short window measurement to avoid the influence of DG control loops Applying the DG high frequency impedance model, faults can be accurately located by measuring the system high frequency line reactance Assisted with the DG side recorded unsynchronized data, this method can be employed to distribution systems with multiple branches and laterals

Fault Detection and Isolation in Medium-Voltage DC Microgrids: Coordination Between Supply Power Converters and Bus Contactors

Abstract: A fast and effective method for detecting and isolating faults in medium-voltage dc microgrids relies on rapid coordination between power supply converters and bus segmentizing contactors to limit currents and isolate faults without any need for fast communication between these active elements. The power converters independently enter current-limiting mode as soon as they recognize a fault condition and the segmentizing contactors autonomously decide whether or not to open based on their local interpretation of time-to-trip curves as functions of apparent circuit resistance. This method allows converters and contactors to use only local measurements when discerning whether or not to trip in order to isolate the faulted section. Simulation and experimental results show that low-impedance short-circuit faults can be isolated within 10–20 ms and the system can be reenergized within 40–60 ms. The method is effective for a wide range of fault and system configurations, and that range can likely be expanded by applying additional discrimination methods.

Evaluation of the Detectability of Electromechanical Faults in Induction Motors Via Transient Analysis of the Stray Flux

Abstract: The stray flux that is present in the vicinity of an induction motor is a very interesting information source to detect several types of failures in these machines. The analysis of this quantity can be employed, in some cases, as a supportive tool to complement the diagnosis provided by other quantities. In other cases, when no other motor quantities are available, stray flux analysis can become one of the few alternatives to evaluate the motor condition. Its noninvasive nature, low cost, and easy implementation makes it a very interesting option that requires further investigation. The aim of this work is to evaluate the suitability of the stray flux analysis under the starting transient as a way to detect certain faults in induction motors (broken rotor bars and misalignments), even when these types of faults coexist in the motor. To this end, advanced signal processing tools will be applied. Several positions of the flux sensors are considered in this study. Also, for the first time, a fault indicator based on the stray flux analysis under the starting is introduced and its sensitivity is compared versus other indicators relying on other quantities. It must be emphasized that, since the capture of the transient and steady-state flux signals can be carried out in the same measurement, the application of the approach presented in this work is straightforward and its derived information may become crucial for the diagnosis of some faults.

DC–AC Converter-Fed Induction Motor Drive With Fault-Tolerant Capability Under Open- and Short-Circuit Switch Failures

Abstract: In this paper, a new fault tolerant dc–ac converter-fed induction motor drive is proposed to maintain motor as close as possible to its desired normal operation under open- and short-circuit switch failures. The operational principles for fault detection and isolation schemes are provided. Two control strategies including predictive control and voltage mode-controlled PWM with integral-double-lead controller for two stage of the converter are presented in conjunction with the elaborated discussion. The control strategy determines appropriate switching states for continuous operation of the drive after a fault. The proposed topology makes it possible to integrate the minimal redundant hardware and full tolerance capability which is an important advantage of the proposed topology. Moreover, the most important advantages of the proposed topology are a fast response in a fault condition and low cost of the converter in comparison with the evaluated topologies. A Joule-integral-based method for selecting an appropriate rating of applied fuses has been presented to provide a reliable fault-isolation operation. Also, a comparison with currently available fault-tolerant dc–ac converters is given to show the merits of the proposed topology. Finally, the experimental results are presented to verify the validity of the theoretical analysis and industrial feasibility of the proposed converter.

An efficient stator inter-Turn fault diagnosis tool for induction motors

Abstract: Induction motors constitute the largest proportion of motors in industry. This type of motor experiences different types of failures, such as broken bars, eccentricity, and inter-turn failure. Stator winding faults account for approximately 36% of these failures. As such, condition monitoring is used to protect motors from sudden breakdowns. This paper proposes the use of neural networks as an efficient diagnostic tool for estimating the percentage of stator winding shorted turns in three-phase induction motors. A MATLAB-based model was developed and simulated under different fault-load combination cases for different sizes of motors. The motor’s developed electromechanical torque was selected as a fault indicator. For the design and training of the neural network, the mean, variance, max, min, and F120 time based on statistical and frequency-related features were found to be very distinct for correlating the captured electromechanical torque with its corresponding percentage of shorted turns. In the training phase of the neural network, five different motors were used and are referred to as seen motors. On the other hand, for testing the efficiency of the developed diagnostic tool, the electromechanical torque under different fault-load combination cases, previously never seen from the first five motors and those of two new motors (referred to as unseen), was used. Testing results revealed accuracy in the range of 88–99%.

Fault Detection and Isolation of the Brake Cylinder System for Electric Multiple Units

Abstract: Air brake systems are crucial systems for safe and stable operation of electric multiple units (EMUs). The brake cylinder system, which includes brake cylinders, corresponding pressure sensors, and connection pipes, plays a vital role in the EMU air brake system. This is because brake cylinder pressures directly affect the brake operation. Currently, brake cylinder pressures are monitored by univariate control charts, i.e., the brake cylinder system will be considered as faulty if a certain pressure goes beyond its allowed range. Besides, serious sensor hardware faults such as open circuit or short circuit can also be detected by system self-inspection circuits. However, three kinds of faults, including brake cylinder component fault, soft sensor fault, as well as gas leakage fault, cannot be well handled by current monitoring methods if these faults are not very serious. In this paper, a fault detection index called intervariable variance (IVV) is first presented to perform fault detection for these faults. Fault detectability analysis is provided, and the IVV statistic is also compared with the univariate control chart approach. Then, a fault isolation strategy is proposed to distinguish different kinds of faults and determine the location of the occurred fault. Finally, the effectiveness of the proposed fault detection and isolation method is demonstrated via extensive experimental studies that are carried out on the EMU brake test bench of Qingdao Sifang Rolling Stock Research Institute Co., Ltd., China.

Fault Location in Distribution Networks Through Graph Marking

Abstract: This paper presents an automatic method for locating faults based on the statuses of fault indicators that are telemetered to the distribution control center. The method constructs an undirected subgraph of the the part of the network that is relevant to the fault event; the vertices of this graph are areas that comprise the possibly faulted electrical equipment, and its edges are the fault indicators. Two graph marking approaches for fault location are discussed: a conventional marking approach that is adopted by the industry and an improved version of it, the downstream marking approach. This paper demonstrates that the downstream marking approach is superior to the conventional one, particularly in terms of immunity to fault indicators that fail to be set. Numerical results and comparisons are presented for unsymmetrical faults and on several networks.

Deployment of Fault Indicator in Distribution Networks: A MIP-Based Approach

Abstract: Fault indicator (FI) plays a crucial rule in enhancing service reliability in distribution systems. This device brings substantial benefits for fault management procedure by speeding up fault location procedure. This paper intends to develop a new optimization model to optimally deploy FI in distribution systems. The proposed model aims to consider a tradeoff between the total customer interruption cost and FI relevant costs, including capital investment, installation, and maintenance costs. As the main contribution of this paper, the problem is formulated in mixed integer programing, which guarantees global optimum solution achieved in an effective runtime. Moreover, the model takes advantages of taking pragmatic fault location procedure into account, which results in more reliable solutions. The effectiveness of the proposed method is scrutinized through various case studies and sensitivity analyses of a test system. In addition, the applicability of the model in practice is appraised by applying it on a real-life distribution network. The resultant outcomes demonstrate the integrity of the proposed model.

Open-Switch Fault-Diagnostic Method for Back-to-Back Converters of a Doubly Fed Wind Power Generation System

Abstract: In order to improve the reliability and availability of the converters of wind turbines, condition monitoring and fault diagnosis are considered crucial means to achieve these goals. In this text, according to the current variation characteristics of the converter, this paper presents a novel approach for real-time diagnostics of open-switch faults in back-to-back converters of a doubly fed wind turbine. The average value of the normalized converter phase currents and the absolute normalized currents are used as principal quantities to formulate the diagnostic variables. The proposed fault-diagnostic variables prove to be carrying information about multiple open-switch faults. In addition to, by the combination of these variables with the average absolute values of the normalized converter phase currents, an adaptive fault-diagnostic threshold is proposed, which ensures the robustness of the diagnosis of single and double open-switch faults. Finally, through the diagnostic variables and the adaptive threshold, the dynamic fault-diagnostic method for open-switch faults in the back-to-back converter of a doubly fed wind turbine is formed. The simulation and experimental results also indicate that the fault-diagnostic method can not only diagnose the multiple open-circuit faults of a back-to-back converter, but also have a better robustness.

High-impedance fault detection in electrical power distribution systems using moving sum approach

Abstract: High-impedance faults (HIFs) in electrical power distribution systems produce a very random, non-linear and low-magnitude fault current. The conventional overcurrent (OC) relaying-based distribution system protection schemes find difficulty in detecting such low-current HIFs. In this study, a simple two criteria-based protection scheme is proposed for detection and isolation of HIFs in multi-feeder radial distribution systems. It utilises one-cycle sum of superimposed components of residual voltage for HIF detection and the maximum value of one-cycle sum of superimposed components of negative-sequence current for faulted feeder identification. The performance of the proposed scheme is evaluated for a wide variety of possible test cases by generating data through power systems computer-aided design/electro-magnetic transient design and control software. Results clearly show that the proposed scheme can assist conventional OC relay for detection and isolation of HIFs in distribution systems with any grounding connections in a more reliable and faster way.

Discrete wavelet transform and energy eigen value for rotor bars fault detection in variable speed field-oriented control of induction motor drive.

Abstract: This paper presents a methodology for the broken rotor bars fault detection is considered when the rotor speed varies continuously and the induction machine is controlled by Field-Oriented Control (FOC). The rotor fault detection is obtained by analyzing a several mechanical and electrical quantities (i.e., rotor speed, stator phase current and output signal of the speed regulator) by the Discrete Wavelet Transform (DWT) in variable speed drives. The severity of the fault is obtained by stored energy calculation for active power signal. Hence, it can be a useful solution as fault indicator. The FOC is implemented in order to preserve a good performance speed control; to compensate the broken rotor bars effect in the mechanical speed and to ensure the operation continuity and to investigate the fault effect in the variable speed. The effectiveness of the technique is evaluated in simulation and in a real-time implementation by using Matlab/Simulink with the real-time interface (RTI) based on dSpace 1104 board.

Impedance-Based Fault Location Algorithm for Ground Faults in Series-Capacitor-Compensated Transmission Lines

Abstract: Locating a fault in a series-capacitor-compensated transmission line (SCCTL) is a challenging task due to the action of a metal-oxide varistor a nonlinear element present as a part of the protection system of the series capacitor. In this paper, an accurate fault-location algorithm that uses synchronized measurements from both ends of the SCCTL is presented which provides fault-location results without using the model of MOV or natural fault loop for single-phase-to-ground, and double-phase-to-ground faults. Another salient feature of the proposed technique is that the subroutines for locating faults in different sections transmission line yield almost identical fault-location results regardless of which section the transmission line is faulted. The proposed technique could also be extended to the double-circuit transmission lines. First, the proposed technique is introduced and its features are elaborated through detailed mathematical analysis. Thereafter, a 500- $\text{kV}$ system with an SCCTL is designed in PSCAD, while the fault-location algorithm is modeled in MATLAB. The proposed algorithm is tested through simulations covering various fault scenarios in an SCCTL. For performance evaluation, the comparative analysis of the proposed technique with a well-known existing technique is performed in this paper.

Experimental Investigation of Inverter Open-Circuit Fault Diagnosis for Biharmonic Five-Phase Permanent Magnet Drive

Abstract: This paper proposes a procedure that is suitable for experimental investigation of real-time open-switch and open-phase faults diagnosis of a five-leg voltage source inverter feeding a five-phase biharmonic permanent magnet synchronous machine (PMSM). The algorithm is based on the specific characteristics of multiphase machines, which allows inverter fault detection with sufficient robustness of the algorithm in the presence of fundamental and third harmonic components. First, the inverter fault effects analysis is achieved in the characteristic subspaces of the five-phase PMSM. Specificities that are interesting for the elaboration of a real-time fault detection and identification (FDI) process are highlighted. Original and particular algorithms are used for an accurate 2-D normalized fault vector extraction in a defined fault reference frame. This frame is dedicated only for FDI. To ensure the high immunity of the FDI process against transient states, a particular normalization procedure is applied. The normalized diagnostic signals are formulated from the defined frame and other variables derived from the reference and measured currents. Simulation and experimental results of open-switch and open-phase faults are provided to validate the proposed algorithm.

Research on Distribution Network Fault Recognition Method Based on Time-Frequency Characteristics of Fault Waveforms

Abstract: Accurate recognition of distribution line fault types can provide directional guidance for line operation and maintenance personnel. Based on the analysis of time-frequency features of fault waveform, a recognized method of distribution line fault type was proposed in this paper. Through modeling and theoretical analysis of waveforms of different fault types, characteristic parameters, which could characterize waveforms of different fault types from three aspects, time domain, frequency domain, and electric arc, were put forward. Calculation formula for extracting characteristic parameters according to fault waveform data was proposed, recognition logic was established by taking multi-parameter fusion as a basis, and then,automatic recognition of distribution line fault types caused by different factors was realized through detection and classification of characteristic parameters of input waveform data. Finally, 136 groups of field fault waveform data provided by the Electric Power Research Institute were used to do closed-loop control and verification of the algorithm, and results indicated that recognition success rate reached 90%, which verified the feasibility of using time-frequency characteristics of fault waveform to realize recognition of distribution line fault types.

A Novel Structure for Bridge-Type Fault Current Limiter: Capacitor-Based Nonsuperconducting FCL

Abstract: Taking into account extension of power systems, their interconnections, and increment of load demand, power capacity of networks is increased and the impedance of sources is decreased Such variations in power systems resulted to occurring high ratings of fault currents Fault current limiter (FCL) can be practically utilized in order to interrupt fault currents to a specified amount without requirement to upgrading protection devices In this paper, a novel simple structure for nonsuperconducting FCL (NSFCL), which is called capacitor-based FCL (CBFCL), is proposed for limiting the high ratings of fault currents in power networks The proposed NSFCL circuit is based on transferring electrical energy to a capacitor during fault occurrence, which can be used after fault removal Simulation of the proposed NSFCL structure is done and the results are provided and analyzed Additionally, the operation of the circuit is experimentally studied, and the similarity between the simulation results and the experimental results is validated The provided simulation and experimental results ensure the practicability and possibility of employment of the proposed CBFCL

Fault-Tolerant Control of Multiarea Power Systems via a Sliding-Mode Observer Technique

Abstract: This paper is focused on solving the problems of fault estimation and fault-tolerant control for multiarea power systems with sensor failures. First, the estimations of the system states and fault vectors are determined using an improved sliding-mode observer technique. Moreover, a derivative gain and a proportional gain are introduced to design the resultant sliding-mode observer more freely, and a discontinuous input is given to reduce the impact of sensor faults and aggregated uncertainties. Then, based on the obtained state estimates, an integral-type sliding-mode control scheme against faults and disturbances is proposed to ensure that the resultant fault system is asymptotically stable, from which each subsystem states in the multiarea power system can be driven onto the designed sliding-mode surfaces in both the state estimation and error estimation spaces. Finally, a three-area power system is simulated to validate the feasibility of the developed fault-tolerant control scheme.

Impedance-Based Fault Location Method for Four-Wire Power Distribution Networks

Abstract: Fault location techniques play an essential role in system recovery and repair. Therefore, numerous methods have been presented for fault location in power transmission and distribution networks. The contribution of this paper is to extend the state-of-art impedance-based fault location methods to support four-wire power distribution. To make this possible an algorithm is developed. The method is obtained using the principles of circuit theory and overcomes the challenges which prevent the use of most fault location methods for distribution networks in practice. This paper presents the detailed equations which are used in the algorithm and how they are obtained. The satisfactory performance of the algorithm is confirmed with numerical examples using MATLAB software.

Wide-Area Fault Location of Transmission Lines by Hybrid Synchronized/Unsynchronized Voltage Measurements

Abstract: Global positioning system (GPS) has been deployed in phasor measurement units and protective relays to provide synchronized measurements across the grid. Synchronized measurements, however, may not be available throughout the network either due to GPS signal loss (GSL) or basically lack of required infrastructure for synchronized sampling. This paper presents a novel method for wide-area fault location incorporating both synchronized and unsynchronized voltage measurements. Complex calculus is utilized to develop a system of equations based on phase angles of synchronized measurements and magnitudes of both synchronized and unsynchronized measurements. The distributed-parameter model of the transmission lines are considered and therefore the obtained results are also valid for long transmission lines. Moreover, the proposed formulation locates the fault irrespective of fault type. Electromagnetic transient simulations for WSCC 9-bus and a 22-bus sub-network of the IEEE 118-bus test system reveal that in the face of GSL, unsynchronized measurements significantly improve fault-location estimation when the synchronized measurements are sparse.