Abstract:Under single-line-to-ground (SLG) faults, the voltages and currents in resonant grounded systems will inevitably be distorted. To locate the faults quickly and accurately, this paper proposes a location method based on fault distortions. The faulty phase is firstly detected according to the first SLG fault feature below, and then the faulty feeder and section are detected according to the second feature below. 1) On the bus, one of the following distortions occurs. One dropped faulty-phase voltage (FPV) and tw… Show more
“…The current and voltage samples extracted, for example, recorded from digital fault recorder (DFR) installed in the power system substation, can be applied to this model for a calculated parameter. The differential equation from a basic equation form as in (7).…”
Section: Fault Location Algorithmmentioning
confidence: 99%
“…TELKOMNIKA Telecommun Comput El Control Differential equation fault location algorithm with harmonic effects in power system (Izatti Md. Amin) 685 Nowadays, one of the main concerns for power system engineers is the presence of harmonic signals that distort energy in the power industry [7], [8]. Nonlinear loads used by the consumer mainly cause harmonic distortion, such as industrial using large motor speed control appliances, arc devices like the welder, and static power converters in manufacturers of paper, textiles, steel, and others [9].…”
About 80% of faults in the power system distribution are earth faults. Studies to find effective methods to identify and locate faults in distribution networks are still relevant, in addition to the presence of harmonic signals that distort waves and create deviations in the power system that can cause many problems to the protection relay. This study focuses on a single line-to-ground (SLG) fault location algorithm in a power system distribution network based on fundamental frequency measured using the differential equation method. The developed algorithm considers the presence of harmonics components in the simulation network. In this study, several filters were tested to obtain the lowest fault location error to reduce the effect of harmonic components on the developed fault location algorithm. The network model is simulated using the alternate transients program (ATP)Draw simulation program. Several fault scenarios have been implemented during the simulation, such as fault resistance, fault distance, and fault inception angle. The final results show that the proposed algorithm can estimate the fault distance successfully with an acceptable fault location error. Based on the simulation results, the differential equation continuous wavelet technique (CWT) filter-based algorithm produced an accurate fault location result with a mean average error (MAE) of less than 5%.
“…The current and voltage samples extracted, for example, recorded from digital fault recorder (DFR) installed in the power system substation, can be applied to this model for a calculated parameter. The differential equation from a basic equation form as in (7).…”
Section: Fault Location Algorithmmentioning
confidence: 99%
“…TELKOMNIKA Telecommun Comput El Control Differential equation fault location algorithm with harmonic effects in power system (Izatti Md. Amin) 685 Nowadays, one of the main concerns for power system engineers is the presence of harmonic signals that distort energy in the power industry [7], [8]. Nonlinear loads used by the consumer mainly cause harmonic distortion, such as industrial using large motor speed control appliances, arc devices like the welder, and static power converters in manufacturers of paper, textiles, steel, and others [9].…”
About 80% of faults in the power system distribution are earth faults. Studies to find effective methods to identify and locate faults in distribution networks are still relevant, in addition to the presence of harmonic signals that distort waves and create deviations in the power system that can cause many problems to the protection relay. This study focuses on a single line-to-ground (SLG) fault location algorithm in a power system distribution network based on fundamental frequency measured using the differential equation method. The developed algorithm considers the presence of harmonics components in the simulation network. In this study, several filters were tested to obtain the lowest fault location error to reduce the effect of harmonic components on the developed fault location algorithm. The network model is simulated using the alternate transients program (ATP)Draw simulation program. Several fault scenarios have been implemented during the simulation, such as fault resistance, fault distance, and fault inception angle. The final results show that the proposed algorithm can estimate the fault distance successfully with an acceptable fault location error. Based on the simulation results, the differential equation continuous wavelet technique (CWT) filter-based algorithm produced an accurate fault location result with a mean average error (MAE) of less than 5%.
“…In distribution systems, based on engineering practices and literature studies, some characteristics and their combinations are selected to be used as main indicators for fault detection and protection, such as line voltage phasor, line current phasor, phase voltage phasor, iA-iO and voltage phasors, harmonic, frequency spectrum, travelling waves and so on [6][7][8][9][10]. The SGF has traditionally been diagnosed based on iA-iO, residual voltage, and their derived quantities, including transient and steady-state amplitude, phase's change and difference, admittance, active power, harmonic, current and waveform.…”
Non‐effectively grounded power distribution systems (NGDS) are widely used in China and other countries. However, over a long time, single‐phase‐to‐ground faults (SGF) have been misjudged or omitted by the monitoring system, threatening the security of the power supply system and human safety. Based on the reason analysis for the omitted and misjudged SGFs in NGDS, the concept of NGDS fault eigenparameters to correctly reflect fault characteristics and a method of SGF detection based on fault eigenparameters are proposed. Then, the detection mechanism of phase voltage and fault current resistive elements for SGF is revealed. The variation characteristics of typical fault parameters changing with distribution system scale (parameter) and fault transition resistance, such as residual voltage and Zero‐sequence current (iA‐iO), are analysed. The eigenparameters of SGF in certain NGDS with specific scales/parameters are also proposed, which can correctly reflect the fault characteristics under different transition resistances.
“…INGLE phase to ground (SPG) faults are the most prevalent fault in resonant grounding (RG) distribution systems [1]. To avoid phase voltage rise and insulation degradation, it is of great necessity to identify and isolate SPG faults rapidly.…”
In industrial application, the existing fault location methods of resonant grounding distribution systems suffer from low accuracy due to excessive dependence on communication, lack of field data, difficulty in artificial feature extraction and threshold setting, etc. To address these problems, this study proposes a decentralized fault section location method, which is implemented by the primary and secondary fusion intelligent switch (PSFIS) with two preloaded algorithms: autoencoder (AE) and backpropagation neural network. The relation between the transient zero-sequence current and the derivative of the transient zero-sequence voltage in each section is analyzed, and its features are extracted adaptively by using AE, without acquiring network parameters or setting thresholds. The current and voltage data are processed locally at PSFISs throughout the whole procedure, making it is insusceptible to communication failure or delay. The feasibility and effectiveness of the approach are investigated in PSCAD/EMTDC and real-time digital simulation system, which is then validated by field data. Compared with other methods, the experiment results indicate that the proposed method performs well in various scenarios with strong robustness to harsh on-site environment and roughness of data.
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