A new approach to identifying faulty lines in distribution systems based on traveling wave refraction and coupling

Lu, Jiping; Li, Jian; Li, Wenyuan; Liu, Ying; Xue, Yi

doi:10.1016/j.epsr.2007.03.006

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…The parameters of the transmission lines are illustrated in Table 1. The model of VSC proposed in [41][42][43][44][45][46][47][48][49][50] has been adopted, vector control, and traditional proportional-integral controller. To obtain the training table of the NN, the system has been simulated…”

Section: Simulationmentioning

confidence: 99%

Artificial intelligence‐based short‐circuit fault identifier for MT‐HVDC systems

Hossam-Eldin

Lotfy

Elgamal³

et al. 2018

IET Generation, Transmission & Distribution

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Section: Simulationmentioning

confidence: 99%

Artificial intelligence‐based short‐circuit fault identifier for MT‐HVDC systems

Hossam-Eldin

Lotfy

Elgamal³

et al. 2018

IET Generation, Transmission & Distribution

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“…A one-terminal fault location method based on combination of traveling wave method using wavelet modulus maxima and impedance method is presented in [38][39][40]. Fault location can be determined by way of filtration of the results based on traveling wave method according to the result based on one-terminal impedance method, thus the distinction between the reflected traveling waves from the fault point and from the remote bus can be avoided.…”

Section: Identification Of the Source Of Reflected Wavementioning

confidence: 99%

Issues of One-Terminal Traveling Wave Fault Location Using Wavelet

Huang

Liu

et al. 2012

AMR

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One-terminal fault location provides many advantages including its simple principle, high relative reliability, low cost and high precision. But there still be some problems in practice, such as detection of wave front, calculation of wave velocity and identification of source of reflected wave. In order to settle the problems above, decoupling methods, acquisition of traveling wave signals, calculation of wave velocity, key factors influencing precision of fault location and so on are discussed. This paper will be of importance in the research of one-terminal fault location method and further improvement of reliability and precision.

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“…However, these kinds of faults should be detected as quickly as possible, proceeding to eliminate their source so as to avoid more severe consequences [4]. This detection is certainly difficult because of the reduced fault current magnitude in single-phase ground faults, especially with low-current faults (LCFs) produced by high resistance faults.…”

Section: Introductionmentioning

confidence: 99%

Low-current fault detection in high impedance grounded distribution networks, using residual variations of asymmetries

Sagastabeitia

Zamora

Mazón

et al. 2012

IET Gener. Transm. Distrib.

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This paper presents a new method of detecting low-current faults in high impedance grounded distribution networks, in both compensated and ungrounded medium voltage networks. Based on monitoring the residual variations of line and phase asymmetries, the proposed algorithm can be used in combination with other steady-state data-based methodologies, in order to detect the existence of a single-phase ground fault, as well as identify the faulty feeder and phase. Although it could also be used in compensated networks by means of other techniques (such as the injection of zero-sequence currents in the neutral), the algorithm described in this paper has been developed by using superposed voltages, so as to make its application possible in compensated and ungrounded distribution networks. Furthermore, the reliability of this algorithm has been extensively tested in Matlab/Simulink, considering a wide range of resistive faults, and its practical applicability has also been described.

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A new approach to identifying faulty lines in distribution systems based on traveling wave refraction and coupling

Cited by 6 publications

References 8 publications

Artificial intelligence‐based short‐circuit fault identifier for MT‐HVDC systems

Artificial intelligence‐based short‐circuit fault identifier for MT‐HVDC systems

Issues of One-Terminal Traveling Wave Fault Location Using Wavelet

Low-current fault detection in high impedance grounded distribution networks, using residual variations of asymmetries

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