Transmission Line Fault Location Research Articles

Traveling Wave-based Algorithm for Fault Detection, Classification, and Location in STATCOM-Compensated Parallel Transmission Lines

The injection or absorption of reactive power by the static synchronous compensator (STATCOM) may lead to the misoperation of protective relays and single-phase-tripping systems that operate based on impedance measurement. Also, high-frequency harmonic components caused by switching the internal circuitry of a STATCOM lead to unintended tripping of relays that work based on traveling waves. This paper proposes a single-terminal approach to detect, locate, and identify the faulty line(s) and phase(s) in parallel transmission lines equipped with STATCOMs using traveling waves. To that end, these processes were designed so that adding a STATCOM or different operating modes does not degrade their efficiency and accuracy. The faults and faulty phases were simultaneously detected using the first set of traveling waves received at the sending end of the parallel lines at a sampling frequency of 200 kHz. Furthermore, a sampling frequency of 1 MHz was used briefly to improve the fault location accuracy. The discrete wavelet transform (with BD4 mother wavelet) was adopted to extract the traveling waves. All simulations and analyses were conducted in the PSCAD environment. The results obtained from numerous simulations at different places and states of the networks verified the high accuracy and validity of the proposed methods.

An Approach to Assessing Spatial Coherence of Current and Voltage Signals in Electrical Networks

In the context of energy industry decentralization, electrical networks encounter deviations of power quality indices (PQI), including violations of the sinusoidality of current and voltage signals, which increase errors in the joint digital processing of spatially separated signals in digital devices. This paper addresses specific features of using the concept of spatial coherence in the measurement and digital processing of current and voltage signals. Methods for assessing the coherence of current and voltage signals during synchronized measurements are considered for the case of PQI deviation. The example of a double-ended transmission line fault location (hereafter, DTLFL) demonstrates that the lower the cross-correlation coefficient, the higher the error and the lower the accuracy of calculating the distance to the fault site. The nature of the influence of spatial coherence violations on errors in DTLFL depends on the expression used to calculate the distance to the fault point. The application of a normalized cross-correlation coefficient for finding errors in the digital processing of current and voltage signals, in the case of spatial coherence violation, was substantiated. The influence of interharmonics and noise on errors in DTLFL, in the case of violations of spatial coherence of signals, was investigated. The magnitude of distortions and error in estimating the current and voltage amplitude depends on the ratio between the amplitudes and phases of the fundamental and distorting interharmonics. Filtration of the original and decimated signals based on the discrete Fourier transform eliminates the noise components of the power frequency harmonics.

A single-ended traveling-wave-based fault location for a hybrid transmission line using detected arrival times and TW′s polarity

This paper proposes a single-ended traveling-wave-based fault location scheme for transmission systems consisting of an overhead line combined with an underground cable. In the first step, the proposed algorithm uses the three-phase voltages measured through optical sensors at the fault locator installation bus to extract the traveling wave arrival times using two consecutive sliding windows and curve fitting. Then, using the arrival times of three consecutive collisions and changes of their polarity, the faulty section is identified. Finally, the exact location of the fault is determined. To evaluate the performance of the proposed algorithm, transient state simulations were performed in EMTP-ATP for various conditions of fault and system parameters. The transient signals are processed and the results prove the high accuracy of the proposed method.

Design and Implementation of Hybrid Transmission Line Protection Scheme Using Signal Processing Techniques

A hybrid scheme for transmission line protection (HSTLP) using the Stockwell transform (ST), Wigner distribution function (WDF), and alienation coefficient (ACF) is designed. Current signals are analyzed using the ST, WDF, and ACF to compute the Stockwell fault index (SFI), Wigner fault index (WFI), and alienation coefficient fault index (ACFI), respectively. These fault indexes are used to derive a hybrid signal processing fault index (HSPFI), which is implemented for the detection of transmission line fault events. The peak magnitude of HSPFI is compared with a preset threshold magnitude (TH) to identify the fault. The statistical formulation is proposed for fault location on the power transmission line. Fault classification is achieved using the number of faulty phases. A hybrid ground fault index (HGFI) is used to recognize the involvement of the ground during the fault event. This HGFI is determined by processing zero sequence current using ST and WDF. The performance of algorithm is tested by various case studies for fault impedance variation, variable sampling frequency, fault incidence angle variation, reverse power flow on transmission line, highly loaded line, different fault locations online, and noisy conditions. The algorithm is also validated to detect a fault on a practical transmission line of large area utility grid of Rajasthan Rajya Vidyut Prasaran Nigam Limited (RVPN) in India. The algorithm performs better than the Hilbert–Huang transform (HHT)-based protection scheme and wavelet transform (WT)-based protection scheme available in the literature in terms of mean error of fault location, fault location accuracy, and noise level. The proposed protection scheme efficiently detected, classified, and located the faulty events such as single-phase-to-ground fault (SPGF), two-phase fault (TPF), two-phase-to-ground fault (TPGF), three-line fault (TLF), and three-line-to-ground fault (TLGF). Transmission line fault location accuracy of 99.031% is achieved. The algorithm performs well even with a high noise level of 10 dB SNR.

New Algorithm for 2-terminal Transmission Line Fault Location Integrating Voltage Phasor Feature and Phase Angle Jump Checking

The low precision and instability of fault location results of power system transmission lines is a major problem that affects the safe operation of power systems, which needs to be solved more effectively. With the increasing coverage of the synchronic Phasor Measurement Unit (PMU) in power systems, it has laid a good foundation for the research and application of high-precision fault location method based on 2-termnal synchronous measurement of phasor. Based on this, a new high-precision fault location algorithm integrating voltage phasor feature and phase-angle jump checking is proposed in this paper. Firstly, the synchronous fundamental positive sequence voltage and current phasors of the fault line are extracted; and then all the roots(including real and virtual roots) are calculated by using the condition that the fundamental positive sequence voltage phasor at the fault point is equal; finally the unique real root represents the actual fault point can be determined by using the feature that the check function of phase-angle will step-jump when crossing the fault point from left to right, and then the purpose of high precision fault location is realized. This algorithm has the characteristics of strong versatility, high precision and immunity to transition resistance. The results of simulation and example show the feasibility and effectiveness of the fault location algorithm the fault location algorithm proposed in this paper.

Fault location in series-compensated transmission lines using adaptive network-based fuzzy inference system

In this paper a new and accurate method for fault location in series-compensated transmission lines (SCTLs) is presented using adaptive network-based fuzzy inference system (ANFIS). In the proposed approach, the desired features are obtained using the Least-Squares Estimation (LSE) from two cycles of voltage and current data in only one line terminal. After that, extracted features, including the decaying DC offset component of the current, the fundamental components of current and voltage, and the phase difference between current and voltage for three-phase current and voltage signals, are normalized and applied as inputs to the fuzzy neural network for fault location. The subtractive clustering technique has been utilized to design the basic ANFIS. This study has scrutinized different cases, including two different ANFIS arrangements, implementing a single network to perform fault location on the entire line and a separate network for each line segment. Moreover, the efficiency of feature selection has been analyzed using the RReliefF algorithm. Various training patterns and tests have been provided in a test transmission system for different system conditions, such as different fault inception angles, fault locations, fault resistances, and structural conditions. The results validate that the proposed approach has accurately located the fault under a wide range of system variations.

Fault location of transmission line based on CNN-LSTM double-ended combined model

In the study of transmission line fault location, most of the previous artificial intelligence-based location methods rely heavily on feature extraction of fault signals, which depend on the researcher’s level of analytical understanding of fault characteristics and require some experience. In addition, previous location methods are more sensitive to line parameters, and the machine learning model obtained based on a specific line is not applicable to other lines, which restricts the application of the method. To solve the above problems, this paper proposes a double-ended combined fault location model based on Maximum Mean Discrepancy (MMD), which combined Convolutional Neural Network(CNN) and Long Short-Term Memory(LSTM). First, different transmission lines are categorized by MMD. Second, a double-ended CNN-LSTM combination model is built for similar lines, which autonomously extracts fault features in an end-to-end form, and then the weights of combination model are determined by the Q-learning algorithm. Finally, we obtain the fault distance prediction. Simulation studies show that the CNN-LSTM double-ended combined model based on MMD has good generalization performance for lines with different parameters, cracking the problem of specialized modeling of different lines while meeting the requirement of fault location accuracy.

Fault Identification on Electrical Transmission Lines Using Artificial Neural Networks

Transmission lines are built to span over long distances, to which they are frequently exposed to many different situations that can cause abnormal conditions known as electrical faults. Electrical faults, when isolated, can cripple the transmission system as power flows are directed around these faults therefore leading to other numerous potential issues such as thermal and voltage violations, customer interruptions, or cascading events. Accurate fault classification and location is essential in reducing outage times and enhancing system reliability. Diverse methods exist and have different strengths and weaknesses. This paper aims to investigate the use of an intelligent technique based on artificial neural networks. The neural networks will attempt to determine the fault classification and precise fault location. Different fault cases are analyzed on multiple transmission line configurations using various phasor measurement arrangements from the two substations connecting the transmission line. The results can provide guidance on choosing the most efficient neural network structure and input measurements for transmission line fault classification and location.

A robust and accurate discrete Fourier transform‐based phasor estimation method for frequency domain fault location of power transmission lines

Frequency domain methods had been commonly used in power transmission line fault location. To improve the accuracy of frequency domain fault location methods, this paper studies a robust and accurate discrete Fourier transform (DFT)-based phasor estimation method. First, this paper analyses the deviation characteristics of DFT output phasors caused by decaying DC components with data window sliding. Based on these characteristics, this paper employs rotation factor computation to construct linear equations for the purpose of estimating the accurate fundamental frequency phasor during fault transient process. In this way, the accurate fundamental frequency phasor can be calculated by a two-step linear operation. Furthermore, to eliminate the effect of off-nominal frequency, the proposed method adjusts frequency deviation by using interpolation method. To further enhance the robustness for frequency domain fault location, the PauTa criterion is used to exclude the anomalous equations in the phasor estimation process. Finally, electro-magnetic fault simulation is used to evaluate the proposed method. The test results demonstrate that the proposed method improve the accuracy of fault location during the fault transient process.

A novel strategy for fault location in shunt-compensated double circuit transmission lines equipped by wind farms based on long short-term memory

Parallel lines are one of the main parts of the power systems due to their capability of increasing the transmitted power and reliability of the power network. However, due to their complexity, fault location in these transmission lines has always been a potential problem. Furthermore, when the wind farms are connected to the power networks, a new challenge is created for the fault location algorithms. The reason is that the impedance changes continuously in these wind power plants. Moreover, the Static Var Compensator (SVC), which is used for compensation in transmission lines, can cause problems in accurate calculation of the fault location in power transmission lines. Accordingly, this paper presents a new method based on Long Short-Term Memory (LSTM) networks for source impedance and other network parameters estimation, which are key parameters to calculate the fault location accurately. The simulations are accomplished using PSCAD and Python software on a sample two-circuit network. This network consists of two parallel lines, a wind farm, and a synchronous generator to supply the network's power. The double-fed induction generator (DFIG) model is considered as the wind farm in the studied network. The results obtained from the tests clearly illustrate the applicability of the proposed method to estimate fault location and source impedance with high accuracy. • A fast and accurate fault location algorithm is achieved using Long Short-Term Memory (LSTM) networks. • Determining the location of different fault types in two circuit transmission lines. • Accurate performance for the location of different fault types under nosy conditions. • Estimation of the source impedance with a much smaller error value.

Stability Control of Flexible High Voltage Direct Current (HVDC) Transmission Based on DC Circuit Breaker Protection

In order to control the stable operation of flexible DC transmission system and ensure the uninterrupted power supply of flexible DC transmission system, the stability control method of flexible DC transmission system based on DC circuit breaker protection is studied. Taking support vector machine as the basic classifier, the two parameters of support vector machine classifier and support vector machine classifier are optimized by bird swarm algorithm, The sample weight is adjusted in real time according to the classification error of support vector machine classifier; The corresponding kernel function is selected and the bird swarm algorithm is used to find the optimal parameters; Through the fault location method of flexible DC transmission system based on wemtr, the fault location of flexible DC transmission line is realized; According to the fault location of flexible DC transmission system, the optimal coordination strategy of DC circuit breaker based on protection line is adopted to realize the stability control of flexible DC transmission system. The simulation results show that this method can realize the stability control of flexible DC transmission in a short time. Under the control of this method, the fluctuation amplitude of voltage and current of flexible DC transmission system becomes smaller, which has application value.

New Approach for Fault Location in Transmission Lines Using Artificial Neural

New Approach for Fault Location in Transmission Lines Using Artificial Neural

Economical Setting-Free Double-Ended Fault Locator for Transmission Lines: Experiences From Recent Pilot Installations

Locating fault precisely on power transmission line is highly beneficial to utilities and accurate fault location can expedite the repair of the faulted components, speed-up restoration, and reduce outage time. In this paper, a setting-free double ended fault location method for power transmission line is proposed using both end voltage and current measurements. This algorithm estimates the required setting parameters using pre-fault data and fault location is calculated using estimated parameters and during fault data. The proposed method is verified using the EMTDC simulations for lines connected with conventional and inverter-based renewable resources. The method is not affected by the error in line parameters and renewable integration. The method is implemented in Intelligent Electronic Device (IED) using 1kHz sampling rate and successfully installed on a 400 kV, 233.07 km line from Power Grid Corporation of India (POWERGRID), India and on a 220 kV, 265.6 km line from Svenska Kraftnat (SVK), Sweden. This paper presents laboratory test results as well as field experimental results in which line patrolling crews found the actual location. Pilot installation results match the performance demonstrated with laboratory experimental results. The method gives average fault location error of ~ 0.1 %. The method can locate the fault within two-tower span distance (~300m) which is comparable with traveling wave-based method that requires 1000 times higher sampling rate, high-cost hardware, more complex commissioning, and settings. These geographically diverse pilot installation results stand as testimony to the fault location accuracy of the proposed setting-free fault location solution.

HVDC Transmission Line Fault Identification: A Learning Based UAV Control Strategy

Electricity Transmission plays an imperative role in smooth provision of power to the consumers. High voltage direct current (HVDC) system has a lead over high voltage alternate current (HVAC) system in various aspects. As DC transmissions lines transmit electricity over long distance, it is crucial to find the malfunctioning part of the line in case of faults occurrence. In this work, a decision-making based unmanned aerial vehicle (UAV) control strategy is presented for identifying fault location in HVDC transmission lines. The technique is developed on two layered control systems, i.e., command station (Leader Agent) and UAV agents (Local Agents) control. The Markov decision process (MDP) based reward policy for both agents is defined mathematically and has been implemented in MATLAB to depict their behavior. The resulting policy is optimized through the value iteration algorithm based on reward functions and transition probabilities.

Transmission Line Fault Location Based on Improved Algorithm of Electromagnetic Time Reversal

For most traditional fault location methods, the fault type needs to be known in advance or there may be dead zones using the decoupled modulus. To solve the problems, an improved algorithm based on electromagnetic time reversal is proposed. The improved algorithm can realize fault location by using the coupling signal in the non-fault phase of the transmission line, so fault location can be realized effectively even when the fault phase is unknown. The feasibility of using non-fault phase coupled signals to locate faults is theoretically verified. A 750kV overhead transmission line model is established by ATP-EMTP to obtain the fault signal at the observation point. The fault signal is time reversed and then connected to the observation point as an injection source. Each hypothetical fault location is traversed and its current is calculated by the BLT super-matrix equation. The 2-norm based on current energy is proposed as the criterion, and the position with the largest norm is the fault location. The simulation results show that the algorithm is not affected by the fault types, transition resistance and the initial phase angles of the power sources on both sides, and has high accuracy.

T-Shaped Transmission Line Fault Location Based on Phase-Angle Jump燙hecking

In order to effectively solve the dead-zone and low-precision of T-shaped transmission line fault location, a new T-shaped transmission line fault location algorithm based on phase-angle jump checking is proposed in this paper. Firstly, the 3-terminal synchronous fundamental positive sequence voltage and current phasors are extracted and substituted into the fault branch distance function to realize the selection of fault branch when the fault occurs; Secondly, use the condition of the fundamental positive sequence voltage phasor at the fault point is equal to calculate all roots (including real root and virtual roots); Finally, the phase-angle jump check function is used for checking calculation, and then the only real root can be determined as the actual fault distance, thereby achieving the purpose of high-precision fault location. MATLAB simulation results show that the proposed new algorithm is feasible and effective with high fault location accuracy and good versatility.

Traveling wave arrival time detection for two-terminal non-contact measurement based on short time matrix pencil scheme

This paper presents an accurate/efficient scheme to distinguish the first and successive time of arrival signals from the fault points of the transmission lines based on non-contact measurement of traveling wave dataset and short time matrix pencil method. In multiple reflection and refraction of traveling waves at characteristic impedance, the first and successive waves overlap at the local and remote terminals, introducing some difficulties in detecting the reflected wave accurately. In such a situation, the detection of the first reflected wave from the second successive wave becomes a challenge, which leads to difficulties in the detection process. Therefore, with the use of a non-contact measurement signal of the overhead transmission line, and with the short-time matrix pencil method of the non-contact dataset, the waves corresponding to the first and successive time reflected signals are distinguished. The simulation results are discussed, and the validity measurement results from the traveling wave generator have been evaluated and analyzed effectively. This indicates that the proposed scheme is robust and accurate for the time of arrival detection for fault location in overhead transmission lines using a non-contact traveling wave dataset with a short time matrix pencil scheme.

A hybrid artificial neural network and wavelet packet transform approach for fault location in hybrid transmission lines

This paper presents a single-ended traveling-wave-based fault location (F.L.) method in a hybrid transmission line (HTL) with an overhead section combined with a cable section. For this, the software has been developed in a MATLAB programming environment. Wavelet packet transform is used to extract transient information of the aerial mode current and voltage signals. The normalized current and voltage wavelet entropy (features) are fed to the feature selection part of the software. Regarding the HTL construction, the optimal features are obtained using the support vector machine and particle swarm optimization. A three-layer artificial neural network is trained to identify the faulty section and half using the optimal features of post fault signals. The square of the aerial mode voltage wavelet coefficients is applied to locate the fault using Bewley's diagram. The proposed approach is applied for F.L. in HTL. Transient simulations are obtained through EMTP-RV software for various fault scenarios, including fault types, resistances, inception angles, and locations. The post fault signals are fed to the developed software. The results illustrate the high accuracy of the proposed method in comparison to previous works.

Research on a New Single-End Fault Location Method for Single-Phase Grounding Faults of Transmission Lines Through Transition Resistance

A single-end fault location method for single-phase nonmetallic grounding faults of transmission lines in a double terminal system is studied and proposed. First, the reason for the poor accuracy of the single-end fault location method in case of single-phase nonmetallic grounding faults is analyzed theoretically, and the necessary conditions for the single-end accurate fault location are put forward. Second, under the necessary conditions of the single-end accurate fault location, according to the topology of fault component networks, the calculation method of the single-end accurate fault location of transmission lines in a double terminal system is studied. Moreover, the influence of line capacitance is considered in this fault location method, and a simple expression for calculating the fault distance is obtained. Finally, the transmission line with a single-phase nonmetallic grounding fault is modeled in PSCAD; therefore, the correctness and the ability against transition resistance of the new single-end fault location method are verified by simulation.

Fault simulation in networks with isolated neutral to find the fault location in power transmission lines

The paper deals with an urgent problem - determining the location of damage to an overhead power transmission line. In particular, the application of the wavelet transform is considered, which makes it possible to localize the temporal position of the frequencies and to determine the time interval of the presence of the frequency in the event of damage to the power line. The paper presents a mathematical model that makes it possible to determine the amplitude-frequency spectrum, by which it is possible to determine the presence of a certain frequency in the signal under study, by which it is possible to determine the fault location. Based on the wavelet transform, the spectra of the current and voltage in the damaged phase in the isolated neutral mode are obtained. It is shown that when the neutral mode is switched, there are no dangerous overvoltage or current surges in the network, and the overvoltage level is reduced.