Fault analysis in transmission lines using neural network and wavelets

Patel, Mamta; Patel, R. N.

doi:10.1109/spin.2015.7095386

Cited by 6 publications

(4 citation statements)

References 15 publications

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“…68  Ej and Sj will be calculated for each resolution according to ( 6) & ( 7) respectively.  MESE will be calculated as given in (5), where the obtained Ej and Sj will be summed for all resolutions and the ratio between them will be obtained.…”

Section: B the Suitable Mother Wavelet Testmentioning

confidence: 99%

Short Circuit Faults Identification and Localization in IEEE 34 Nodes Distribution Feeder Based on the Theory of Wavelets

Authafa¹

2018

IJEEE

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In this paper a radial distribution feeder protection scheme against short circuit faults is introduced. It is based on utilizing the substation measured current signals in detecting faults and obtaining useful information about their types and locations. In order to facilitate important measurement signals features extraction such that better diagnosis of faults can be achieved, the discrete wavelet transform is exploited. The captured features are then utilized in detecting, identifying the faulted phases (fault type), and fault location. In case of a fault occurrence, the detection scheme will make a decision to trip out a circuit breaker residing at the feeder mains. This decision is made based on a criteria that is set to distinguish between the various system states in a reliable and accurate manner. After that, the fault type and location are predicted making use of the cascade forward neural networks learning and generalization capabilities. Useful information about the fault location can be obtained provided that the fault distance from source, as well as whether it resides on the main feeder or on one of the laterals can be predicted. By testing the functionality of the proposed scheme, it is found that the detection of faults is done fastly and reliably from the view point of power system protection relaying requirements. It also proves to overcome the complexities provided by the feeder structure to the accuracy of the identification process of fault types and locations. All the simulations and analysis are performed utilizing MATLAB R2016b version software package.

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Section: B the Suitable Mother Wavelet Testmentioning

confidence: 99%

Short Circuit Faults Identification and Localization in IEEE 34 Nodes Distribution Feeder Based on the Theory of Wavelets

Authafa¹

2018

IJEEE

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“…Power transmission lines have a broad range of faults. These fault classifications appeared in various previous articles [2][3][4][5][6][7][8][9]. There are several approaches to fault location algorithms, including various approaches regarding measurements and data processing and their proposed applications.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Fault Location Using the Retardation Method

et al. 2022

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A new method for short-circuit fault location is proposed. The method is based on instantaneous signal measurement and its first and second derivatives, which are the novel elements of the current approach. The derivatives allow associating a precise time stamp to the occurrence of the fault. Due to retardation phenomena, the difference between the times in which a signal is registered in two detectors can be used to locate the fault. We offer several mathematical models to describe the fault. Although a description of faults in terms of a lumped circuit is useful for elucidating the methods for detecting the fault, this description will not suffice to describe the fault signal propagation; hence, a distributed models is needed, which is given in terms of the telegraph equations. Those equations were used to derive a transmission line transfer function, and an exact analytical description of the fault signal propagating in the transmission line was obtained. The analytical solution was verified both by numerical simulations and experimentally.

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“…Ray and Mishra also uses post-fault of current waveform to estimate fault location and develop a system with error less than 0.29%(10) while Ghimire used post-fault voltage and current from two end method to estimate fault location(11) with less than 3.9% for impedance based method. In contrast, researcher (12)(13)(14) studies fault location in transmission line using faulted current signal. There are no significant reason of choosing post-fault signal or fault signal.…”

Section: Introductionmentioning

confidence: 99%

Steady State versus Transient Signal for Fault Location in Transmission Lines

Hashim

Osman²,

Ibrahim

et al. 2018

J. Phys.: Conf. Ser.

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Abstract. This paper focuses on determination of suitable time interval of features extraction either during steady state signal or transient signal of impedance based method to estimate the location of fault using Artificial Neural Network (ANN). Simulation studies have been carried on power system model using MATLAB & SIMULINK. The faulted current signal taken at single-ended of transmission lines are used as input in the proposed scheme. Different types of faults at different operating condition have been considered to this study. This studies extracted five features that are delta minimum to maximum, amplitude, standard deviation, energy and mean of the signal for both condition. The proposed studies is evaluated by Mean Square error (MSE) from ANN. Most researchers using steady state signal as their input and there also have researchers used transient signal as the input but there have no study or reason for choosing the signal at that condition. However, by carrying out this studies, it shows that not all features are suitable to extract during one time signal condition.

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Fault analysis in transmission lines using neural network and wavelets

Cited by 6 publications

References 15 publications

Short Circuit Faults Identification and Localization in IEEE 34 Nodes Distribution Feeder Based on the Theory of Wavelets

Short Circuit Faults Identification and Localization in IEEE 34 Nodes Distribution Feeder Based on the Theory of Wavelets

Real-Time Fault Location Using the Retardation Method

Steady State versus Transient Signal for Fault Location in Transmission Lines

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