Travelling Wave-Based Fault Location Scheme for Multi-End Aged Underground Cable System

Gilany, Mahmoud; Eldin, E.S.T.; Ibrahim, Doaa Khalil

doi:10.2316/journal.203.2008.2.203-3843

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…The wavelet modulus maxima method has been used to infer the original site of the partial discharge source by investigating pulse propagation along the induction motor winding [9] , to detect transient travelling waves for directional transmission line protection [18] and to locate faults for ageing underground cable systems [19] .…”

Section: Wavelet-based Singularity Detectionmentioning

confidence: 99%

A condition monitoring system for an early warning of developing faults in wind turbine electrical systems

Ma¹,

Cross²,

Qian³

2016

insight

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Section: Wavelet-based Singularity Detectionmentioning

confidence: 99%

A condition monitoring system for an early warning of developing faults in wind turbine electrical systems

Ma¹,

Cross²,

Qian³

2016

insight

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“…Another single-end positioning method is based on the velocity difference between line mode and zero mode wave. But the zero mode wave velocity is unstable with the fault distance and the traveling wave frequency, and the error is large [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Single Phase to Ground Fault Section Location Based on Characteristics of Traveling Wave Refraction and Reflection

Shi¹,

Hui²,

Gu³

et al. 2018

dteees

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Abstract. For single phase to ground fault in distribution networks, fault locating using traveling wave measured at one terminal only need to detect the arrival time of the initial wave head of the line mode and the zero mode. But the zero mode wave velocity is unstable. This paper proposes a fault section location method using only line mode traveling wave. It analyzes wave refraction and reflection performance at the fault point, the branch point and the end of the line. The path differences between reflected waves and the initial incident wave are estimated through Hilbert Huang Transform by indexing the arrival time of the initial wave and reflected waves, if the line mode wave velocity is assumed. Combined with the topology of distribution network, the possible propagation paths can be obtained to identify the fault section. The effectiveness of the proposed method is verified by experiments in the actual distribution network.

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“…These methods have good accuracy for high impedance fault but are complex and expensive to implement. A travelling wave‐based fault location scheme for underground cable system is proposed in . In this scheme, fault location is determined by wavelet transform which extracts the high‐frequency components initiated due to the fault from the voltage signal.…”

Section: Introductionmentioning

confidence: 99%

Application of extreme learning machine for underground cable fault location

Ray

Mishra

2014

Int. Trans. Electr. Energ. Syst.

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SUMMARYThis paper presents an accurate hybrid fault location technique, combining s-transform and extreme learning machine for underground power cable in distribution system. In the proposed method, one cycle sending end post fault current and voltage signal are taken for determining the fault location in an underground cable. Using s-transform, useful features are extracted, and further applying feature selection technique, redundant features are removed from the total feature set. In this paper, forward feature selection/particle swarm optimization-based feature selection method is used. Thereafter extreme learning machine is used to estimate the fault distance with the selected features. Feasibility of the proposed method has been tested for all ten types of fault on a 20-kV, 5-km underground power cable and 220-kV, 10-km underground cable with a large range of operating condition. Also the proposed method is evaluated for 220-kV, 10-km underground cable in combination with 100-km overhead line. The simulation result of the proposed fault location technique shows that the maximum absolute error of less than 0.3% and a mean error of less than 0.2% are achieved which demonstrate high accuracy and robustness. Results are compared with other fault location approaches.

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Travelling Wave-Based Fault Location Scheme for Multi-End Aged Underground Cable System

Cited by 3 publications

References 8 publications

A condition monitoring system for an early warning of developing faults in wind turbine electrical systems

A condition monitoring system for an early warning of developing faults in wind turbine electrical systems

Single Phase to Ground Fault Section Location Based on Characteristics of Traveling Wave Refraction and Reflection

Application of extreme learning machine for underground cable fault location

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