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A comprehensive evaluation of multicategory classification methods for fault classification in series compensated transmission line

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Abstract

This paper presents a new method for fault classification in series-compensated transmission line using multiclass support vector machine (MCSVM) and multi class extreme learning machine (MCELM). These methods use the information obtained from the wavelet decomposition of fault current signals for fault classification. Using MATLAB simulink, data set has been generated with different types of fault and system variables, which include the fault resistance, fault distance, load angle and fault inception angle. The proposed method has been tested on a 400-kV, 300-km transmission line under variety of fault conditions. The performance of MCSVM and MCELM is compared in terms of training time and classification accuracy. The comparisons have been made for both One-Versus-One and One-Versus-Rest methods of SVMs and ELMs. Results show that MCELMs need less training time compared to MCSVMs, and the classification accuracy of MCELMs is more or less similar to MCSVMs. The feasibility of the proposed methods is also tested on a practical 220-kV series-compensated transmission line, and the results obtained are quite promising.

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Authors and Affiliations

  1. Raja College of Engineering and Technology, Madurai, 625 020, Tamil Nadu, India

    V. Malathi

  2. National Engineering College, Kovilpatti, Tamil Nadu, India

    N. S. Marimuthu

  3. Thiagarajar College of Engineering, Madurai, Tamil Nadu, India

    S. Baskar

Authors
  1. V. Malathi
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  2. N. S. Marimuthu
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  3. S. Baskar
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Corresponding author

Correspondence to V. Malathi.

Appendix 1

Appendix 1

  • Source data at both sending and receiving ends of the line:

  • Positive sequence impedance: 1.31 + j15.0 Ω.

  • Zero sequence impedance: 2.33 + j26.6 Ω.

  • System frequency: 50 Hz.

  • Transmission line data:

  • Length of the line: 300 km

  • Voltage: 400 kV

  • Positive sequence impedance: 8.25 + j94.5 Ω

  • Zero sequence impedance: 82.5 + j308 Ω

  • Positive sequence capacitance: 13 nF/km.

  • Zero sequence capacitance: 8.5 nF/km.

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Malathi, V., Marimuthu, N.S. & Baskar, S. A comprehensive evaluation of multicategory classification methods for fault classification in series compensated transmission line. Neural Comput & Applic 19, 595–600 (2010). https://doi.org/10.1007/s00521-009-0312-9

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  • DOI: https://doi.org/10.1007/s00521-009-0312-9

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