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Classification of Lightning and Faults in Transmission Line Systems Using Discrete Wavelet Transform

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  • Pathomthat Chiradeja
  • Atthapol Ngaopitakkul

Abstract

In Thailand, electrical energy consumption has been rapidly increasing, following economic and population growth. In order to supply constant power to consumers, reliability is an important factor the electric utility needs to consider. Common disturbances that cause severe damage to transmission and distribution systems are lightning and faults. The system operator must deal with these two phenomena with speed and accuracy. Thus, this study aims to investigate the differential behaviour of transmission systems when disturbance such as lightning strikes and faults occurs in a 115-kV transmission line. The methodology consists of using the ATP/EMTP program to model the transmission system by the 115-kV Electricity Generating Authority of Thailand (EGAT) and simulate both lightning and fault signals in the system. The discrete wavelet transforms are then applied to obtain the signals in order to evaluate the characteristics and behaviour of both signals in terms of high-frequency components. The obtained data will then be used to construct the fault and lightning classification algorithm based on DWT and travelling wave theory. The proposed algorithm shows the effectiveness in classifying the fault and lightning based on the transmission system that was modelled after the actual system in Thailand. Thus, it can further improve the protection scheme and devices in terms of accuracy and reduce the response time for an operator to address the disturbance and ensure the reliability of the system in the future.

Suggested Citation

  • Pathomthat Chiradeja & Atthapol Ngaopitakkul, 2018. "Classification of Lightning and Faults in Transmission Line Systems Using Discrete Wavelet Transform," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-14, October.
  • Handle: RePEc:hin:jnlmpe:1847968
    DOI: 10.1155/2018/1847968
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    Cited by:

    1. Khalfan Al Kharusi & Abdelsalam El Haffar & Mostefa Mesbah, 2022. "Fault Detection and Classification in Transmission Lines Connected to Inverter-Based Generators Using Machine Learning," Energies, MDPI, vol. 15(15), pages 1-23, July.

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