Fault Phase Selection Research Articles

Fault Location and Phase Selection Method of Distribution Network Containing IIDG Based on Online Active Detection

This paper proposes a fault location and phase selection method for the distribution network containing IIDG based on online active detection, utilizing online active detection. In this method, the characteristic harmonic current injection control strategy based on d- and q-axis control is obtained by analyzing the structure, control strategy, and short-circuit current of IIDG. During a fault, the distributed power supply injects characteristic harmonic current into line, adapting its magnitude with the short-circuit current’s size. By detecting the difference in harmonic current content rate for both ends of the fault point, the method achieves online location and line selection of fault points. A 10 kV IIDG distribution network model is simulated by using PSCAD to validate the feasibility and accuracy of the proposed fault location and phase selection method.

Research on Phase-to-phase Fault Location Method of Active Distribution Network

Due to the weak feed characteristic of active distribution networks, the sensitivity of the original fault phase selection method and the accuracy of fault location are decreased. Most of the existing fault section location methods focus on the phase selection and location of the earth fault, and there is a lack of relevant research on the location of the fault section to the phase-to-phase fault. Moreover, most of the methods need to install the signal measuring device in the system as large as possible, which is not economical. The operation condition of active distribution networks is complicated, the fault characteristics are weak, and the location result is easily affected by non-fault disturbances such as DG access capacity and location. In this paper, the phase-to-phase fault of active distribution networks is taken as the research object. Firstly, phase current and zero-sequence current combined criterion is used for fault phase selection, and then combined with the phase-frequency characteristics of mode impedance of distribution line and photovoltaic power line, a fault section location method based on transient characteristic frequency band is proposed, which is not affected by non-fault disturbance such as photovoltaic control strategy and DG access capacity and location. Simulation results show that the method is effective.

An improved high-impedance fault identification scheme for distribution networks based on kernel extreme learning machine

In distribution networks, high-impedance faults (HIFs) occur frequently and have a harmful impact on the distribution network. However, fault detection and fault phase selection of HIFs are challenging due to weak fault characteristics. Therefore, this paper proposes an improved HIF identification scheme based on a kernel extreme learning machine (KELM) that can sensitively identify HIFs and select the fault phase by adaptively extracting the weak fault characteristics. First, a fault feature extraction strategy based on discrete wavelet decomposition (DWT) and the Hilbert–Huang transform (HHT) is proposed to obtain multiple features that describe the weak fault characteristics of HIFs. Second, an XGBoost-based fault feature selection scheme is proposed for screening with sensitive characterization of HIFs. Next, a sensitive and accurate HIF identification scheme based on the improved learning algorithm (KELM) is proposed to enable accurate and sensitive HIF detection and phase selection. Finally, numerical simulations based on PSCAD/EMTDC and MATLAB were carried out, which reveals the effectiveness and accuracy of the proposed HIF identification scheme. Compared with the traditional HIF identification scheme, the proposed method exhibits conciseness and correctness.

Faulted phase selection multicriteria algorithm implemented in generic hardware for centralized P&C in smart grids

The integration of devices based on renewable energies and power electronics makes it necessary to rethink some of the methods used for protection and control in distribution and transmission grids. The difference between short circuit current contributions from renewable and conventional generators may affect protection system operation. Fault phase selection is one of the elements to be analyzed under renewable generation scenarios due to its importance in protection functions such as distance protection.The digitization of substations presents new opportunities in control and protection systems, such as functionality increase, reliability improvement, cost reduction of the installation and capacity for remote maintenance. This paper proposes a multi-criteria fault phase selection algorithm developed to be implemented in digital substations. The proposed faulted phase algorithm combines the results provided by four independent protection algorithms and has been designed to be applied in transmission power systems. Depending on the electrical variables measured in each event, quality criteria are defined to consider the strengths and weaknesses of each independent algorithm. The proposed algorithm has been implemented and tested on the centralized protection and control platform called EPICS, obtaining very satisfactory results.

Fault Location Study of Overhead Line–Cable Lines with Branches

A new fault location method based on the three-terminal travelling wave method is proposed for the fault location problem of multi-branch overhead line–cable transmission lines. Firstly, the process of fault travelling wave propagation in overhead transmission lines and the phenomenon of refraction are analysed, and an improved phase-mode transformation is introduced to decouple the electromagnetic coupling and perform fault phase selection. Secondly, the Pearson correlation coefficient is introduced to compare the similarity of the current travelling waveforms at different measurement points in order to implement fault segmentation. To solve the problems of the complexity of the fault travelling wave propagation process and the difficulty of identifying the travelling wavehead, the Hilbert–Huang transform is used to extract the fault signal characteristics, and the travelling wave arrival moment is accurately calculated by the sampling error correction method to determine the fault location. Finally, the accuracy and stability of the method are verified via a simulation test on the MATLAB/Simulink platform. The results show that the proposed positioning method combining the three-terminal travelling wave method with HHT and sampling error correction can locate the fault location more accurately, and it has good potential for application in the engineering field. It provides a new technical means for fault location in overhead transmission lines, which is expected to become one of the most important technologies in the future power system.

Instantaneous incremental current-based faulted phase selection algorithm

Instantaneous incremental current-based faulted phase selection algorithm

Ground Fault Detection of Small Resistance Grounding System Based on Improved Phase Current Abrupt Variable Method

When a high fault resistance happens in a small resistance ground system, the protection device is simple to be unsuccessful to manage. By analyzing the characteristics of positive, negative currents in the additional state of fault, it is found that the fault detection method constructed only by the phase current increment relationship has risk of misoperation, but relationship among the magnitude of phase current increment can directly reflect the phase of the ground fault. At the same time, the phase location among the fault phase voltage and the current of the unhealthy part and non-fault line is different. Therefore, a ground fault protection method based on the correlation between the phase current increment ratio and the different phase angles of fault phase voltage and current is proposed. We choose the phase with the big phase current mutation as the grounding phase, and affect the fault part by the phase difference between the fault phase voltage and the current of the line. This eliminates the risk of protection maloperation only using the relationship between the size of current increment and protection sensitivity in case of high resistance fault. It can be used for fault phase selection, location, and multi-level protection. The correctness of the way is certificated by simulation.

Phase Selection and Location Method of Generator Stator Winding Ground Fault Based on BP Neural Network

The phase selection and fault location methods of generator stator winding single-phase grounding fault are greatly affected by the transition resistance. A new phase selection and generator stator ground fault location approach based on the BP neural network is proposed in this research from a data-driven angle. This method uses a neural network to calculate the probability of three-phase fault occurrence to identify the fault phase and directly calculate the fault location that takes the amplitude and phase angle characteristics of zero-sequence voltage as input. The simulation results show that the stator ground fault phase selection and location algorithm based on the neural network can achieve correct phase selection and small positioning error, which has verified the effectiveness of the method.

Ground and phase fault classification for half-wavelength transmission lines relaying purposes

In this work, a new fault classification and phase selection methodology for half-wavelength (HWL) transmission lines is developed. Initially, the basic principles of phase currents transformations are presented. Then, an innovative faulted phase selection methodology based on the variation of those currents is developed. The behavior of the electrical quantities related to short circuits in such long lines is very different when compared to conventional lines. The faulted phase selection method employed in this work is built on the fact that those decoupled currents are expected to not vary or vary less than the others, depending on how many phases are in short circuit. The robustness of the method was analyzed considering different load conditions and fault resistances. Furthermore, different sampling rates were considered for the phase currents. Extensive simulation studies showed that the developed method can accurately identify the fault types and the faulted phase with a relatively low sample rate. Moreover, the simulation results showed that the proposed method is not affected by the presence of inter-harmonics and responds precisely with high-resistance faults. The proposed algorithm presented errors smaller than 0.04%.

Fault Phase Selection Method Based on Single-Phase Flexible Arc Suppression Device for Asymmetric Distribution Networks

The phase-to-ground admittance in distribution networks is asymmetric. This asymmetry is aggravated by the arc suppression coil, resulting in zero-sequence overvoltage. The magnitude of zero-sequence overvoltage can exceed the line-to-ground voltage, endangering the operation of electrical equipment. Moreover, after the occurrence of a single-line-to-ground fault, the change law of the three-phase voltage is affected by the zero-sequence overvoltage, leading to misjudgment of the fault phase. Accordingly, this paper proposes a fault phase selection method based on active current injection that can adapt to asymmetric distribution networks. The fault phase is selected by injecting current and calculating the equivalent power supply voltage of the faulty line without increasing the ground-fault current. The high sensitivity of the proposed fault phase selection method was verified for high impedance faults through software simulations and prototype experiments. Moreover, the zero-sequence overvoltage can be suppressed by a single-phase flexible arc suppression device during the normal operation of distribution networks. The ground-fault current can be quickly suppressed at different ground-fault locations and resistance values, ensuring the extinguishment of the ground-fault arc.

Three-Phase Fault Arc Phase Selection Based on Global Attention Temporal Convolutional Neural Network

For low-voltage three-phase systems, the deep fault arc features are difficult to extract, and the phase information has strong timing. This phenomenon leads to the problem of low accuracy of fault phase selection. This paper proposes a three-phase fault arc phase selection method based on a global temporal convolutional network. First, this method builds a low-voltage three-phase arc fault data acquisition platform and establishes a dataset. Second, the experimental data were decomposed by variational mode decomposition and analyzed in the time-frequency domain. The decomposed data are reconstructed and used as input to the model. Finally, in order to reduce the fault features lost during the causal convolution operation, the global attention mechanism is used to extract deep fault characterization to identify faults and their differences. The experimental results show that the accuracy of the three-phase arc fault arc phase selection of the model can reach 98.62%, and the accuracy of single-phase fault detection can reach 99.39%. This model can effectively extract three-phase arc fault and phase characteristics. This paper provides a new idea for series fault arc detection and three-phase fault arc phase selection research.

The Phase Selection of Three-phase Arc Fault Based on Improved TCN-LSTM

According to the increasingly severe situation of electricity safety. Aiming at the difficulty in extracting arc fault features in low-voltage three-phase systems and the inconspicuous phase distinction, a three-phase arc fault phase selection method based on improved LSTM-TCN neural network is proposed. Firstly, the structure and activation function of Long Short-Term Memory Network (LSTM) and Temporal Convolutional Network (TCN) are improved according to the experimental data. Finally, the feature vectors obtained by the improved LSTM and the improved TCN are fused to determine the arc fault and the difference. The experimental results show that the model structure proposed in this paper can effectively extract the characteristics of three-phase arc faults and phases. It is of great significance to industrial and household electrical safety.

Influence of Negative Sequence Injection Strategies on Faulted Phase Selector Performance

Renewable power is expected to increase drastically in the coming years due to the energy transition. A large part of the newly installed generators will be connected to the power system through inverters and electronic converters, whose behaviour differs from the generators connected synchronously to the network. One of the main differences is the current contribution during symmetrical and asymmetrical faults which can affect protection systems. New grid codes establish requirements for fast current injection, but the converter’s maximum current limitations during faults make it difficult to establish control strategies for such current contribution. This paper studies the performance of faulted phase selector algorithm of a commercial relay under the current contribution from renewables before unbalanced faults. Two positive and negative sequence current injection strategies in compliance with new Spanish grid code requirements are proposed and tested under fault conditions in HiL (Hardware in the Loop). Test results show that the selected injection strategy affects the fault phase identification algorithm. Furthermore, the negative sequence injection requirements established in the new grid code improve the relay performance when line-to-line faults are applied, but they are not enough to identify all fault types.

A New Method of Fault Phase Selection for Transmission Line Based on Composite Feature of Fault Current and Support Vector Machine

A New Method of Fault Phase Selection for Transmission Line Based on Composite Feature of Fault Current and Support Vector Machine

Study on a new fault phase selector in interconnection line with wind turbine based on doubly-fed induction generator’s wind farm

The fault current characteristics of wind turbine based on doubly fed induction generator (DFIGWT) is complicated. The conventional superimposed phase selectors cannot meet the requirements of phase selection in the interconnection line based on DFIGWT’s wind farm. In this paper, according to the low voltage ride-through strategy of DFIGWTs, the shortcomings of traditional superimposed phase selector are analyzed. Then, a new fault phase selector is proposed based on the amplitude ratio between superimposed phase voltage and superimposed phase-to-phase voltage. According to the proportional relationship between the superimposed phase voltage and superimposed phase-to-phase voltage in the interconnection line with DFIGWT-based wind farm, the fault phase selection coefficients are proposed. Based on the proposed fault phase selection coefficients, the fault phases under different fault conditions can be identified. Finally, the effectiveness and reliability of the proposed fault phase selector are validated by simulation. Test results show that the proposed method is not affected by the LVRT control strategies and can meet the phase selection requirements of new energy sources under different LVRT strategies conditions.

Evaluation of HVDC system's impact and quantification of synchronous compensation for distance protection

This paper presents a comprehensive evaluation of the HVDC system's impact on distance protection via systematic and realistic experimental tests, along with theoretical analysis of the root causes of the identified compromised protection performance. A methodology for quantifying the impact of Synchronous Compensation (SC) in supporting the distance protection operation is also established. In this work, the performance of two widely used physical distance protection relays have been evaluated using a realistic Hardware'In'the'Loop (HIL) testing environment, where a total of 480 cases have been tested under a wide range of system scenarios. Representative cases with compromised protection performance are selected, where issues of under/over'reach, faulted phase selection and impedance measurement are identified and analysed. Furthermore, a method for quantifying the required SC level to address the under/over'reach issues resulting from HVDC systems is presented. The method establishes the relationship between the angle difference of the two'end fault current infeeds of the protected line and the SC level. Based on this relationship, the required SC capacity to constrain the angle difference within a targeted limit can be estimated, which offers a useful tool for system operators to appropriately size the SC's capacity with additional valuable insights from the distance protection perspective.

A novel high-speed transient-based phase selector for AC transmission line connected to LCC-HVDC inverter station

Affected by commutation failure and fast control of line-commutated-converter (LCC) high-voltage direct-current (HVDC) inverter station, conventional phase selectors exist adaptability problems. In this paper, a novel faulted phase selector for AC lines connected to LCC-HVDC inverter station, based on the ratio of transient current energy, is proposed. Firstly, the inadaptability of conventional phase selection methods is briefly analyzed in this paper. Besides, the current relationship of the initial stage of the fault is immune to the commutation failure disturbance, and the current information of this stage is constructed as a transient energy ratio which is used to select the fault phase. On this basis, considering the weak amplitude characteristics of high-frequency signals, synchronous squeezed S-transform (SST) is introduced to process signals in this paper. PSCAD/EMTDC simulation results verify that the proposed phase selector can effectively avoid the DC-side commutation failure and control influence, achieve fast and reliable phase selection, and is weakly affected by the fault resistance, fault distance, initial fault angle, and noise interference.

An Ultra-High-Speed Algorithm for Fault Classification in Double Circuit Transmission Lines Using Only the First Group of Received Current Traveling Waves

This paper presents a new and very fast fault detection (FD), fault classification (FC), and fault phase selection (FPS) method, which is just based on the first group of current traveling waves (cTW) in double circuit transmission lines (DCTLs). All internal, inter-circuit faults and lightning strikes on transmission line (TL) phases and shield wires are reviewed. By the proposed algorithm, FC and FPS are performed in the shortest possible time. In this study, wavelet transform (WT) is used to extract the traveling wave (TW) caused by the fault from the current signal of one DCTL terminal, and only the first group of these waves is used for FC and PFS to increase velocity. To classify various fault types, the zero components of TWs of the two lines, which can be calculated using the conventional modal transforms and another modal transform of 6*6 dimensions defined on all six phases of the DCTL, is used. All simulations are performed in PSCAD on a 230kV grid and a DCTL of 200km length. Also, the performance of the proposed algorithm is tested under various fault and lightning conditions in the presence of white noise with different incidence angles and various fault resistances.

Faulted‐phase identification scheme for series‐compensated transmission lines during the power swing

To perform a fast faulted-phase selection under the power swing in a series compensated line with a thyristor-controlled series capacitor (TCSC) is an extreme challenge facing the transmission line protection schemes. Thus, this paper proposes a new scheme for recognizing the faulted-phase in TCSC-compensated transmission lines during the power swing. Primarily, the fault feature is extracted by using a modified Interclass correlation coefficient. The scheme utilizes the system-current samples during the fault period and system-current samples during the health state as two variables for obtaining the modified interclass correlation coefficient. Then a cumulative approach is used to enlarge the fault feature. The proposed scheme has been subjected to a wide variety of tests through different faults circumstances under different compensation levels. The experimental results have shown good performance against the high impedance/resistance fault under different TCSC-compensation levels during the power swing. Also, the results showed a distinction in terms of time response due to its simple computation process.

Fault classification and phase selector algorithm for half-wavelength transmission lines

This study presents a new phase selector algorithm and fault type classification for very long transmission lines, known as the half-wavelength lines (HWL). For this work, the Clarke components variation rate method applied to current magnitudes was used. The method was implemented in a real-time digital simulation hardware-in-the-loop (HIL) test environment. We applied different fault types at each 5% line length, obtaining Clarke component current phasors. The proposed algorithm is stable for the native behavior of the half-wavelength line, including the resonance zones and their mitigation procedures. In addition, the algorithm is immune to the fault insertion angle, fault resistance, and line loading level. Finally, the algorithm could be applied in commercial microprocessor-based relays or could be used as a post-fault analysis tool.