Fault Location in the Transmission Network based on Zero-sequence Current Analysis using Discrete Wavelet Transform and Artificial Neural Network

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Dashtdar Masoud; Esmailbeag Mostafa; NAJAFI MOJTABA

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Journal: COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING) Year:2019 | Volume:10 | Issue:2 Page(s): 87-102

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Title

Fault Location in the Transmission Network based on Zero-sequence Current Analysis using Discrete Wavelet Transform and Artificial Neural Network

Author(s)

Dashtdar Masoud | Esmailbeag Mostafa | NAJAFI MOJTABA | Issue Writer Certificate

Keywords

wavelet transform Fault Location ANN WEEQ2

Abstract

In this paper, in order to fault locate in the transmission network, a discrete wavelet transform is used to extract the fault characteristics from the zero sequence current, in order to train the artificial neural network. Initially, Fortescue transform, the zero-sequence current seen from both terminals is calculated. By the wavelet transform of the high-frequency information stored in the horizontal component of zero-sequence current from both terminals, and finally by calculating the stored energy in the horizontal components, as well as extracting the maximum scale of horizontal component, we can identify certain features of fault that are suitable for training the neural network. The simulation results show that the horizontal components maximum scale as well as the energy stored in these components strongly depend on the fault resistance, type of fault and fault location. Therefore, educational data should be selected to make these changes well so that the neural network does not suffer from its diagnosis. Finally, the proposed method is implemented on the test grid whose results show the performance of the method with overall accuracy of 98. 6% and maximum estimation error of 0. 1666%.

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APA: Copy

Dashtdar, Masoud, Esmailbeag, Mostafa, & NAJAFI, MOJTABA. (2019). Fault Location in the Transmission Network based on Zero-sequence Current Analysis using Discrete Wavelet Transform and Artificial Neural Network. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), 10(2 ), 87-102. SID. https://sid.ir/paper/202988/en

Vancouver: Copy

Dashtdar Masoud, Esmailbeag Mostafa, NAJAFI MOJTABA. Fault Location in the Transmission Network based on Zero-sequence Current Analysis using Discrete Wavelet Transform and Artificial Neural Network. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)[Internet]. 2019;10(2 ):87-102. Available from: https://sid.ir/paper/202988/en

IEEE: Copy

Masoud Dashtdar, Mostafa Esmailbeag, and MOJTABA NAJAFI, “Fault Location in the Transmission Network based on Zero-sequence Current Analysis using Discrete Wavelet Transform and Artificial Neural Network,” COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), vol. 10, no. 2 , pp. 87–102, 2019, [Online]. Available: https://sid.ir/paper/202988/en

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